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End users' trust in data repositories: Definition and influences on trust development
Abstract
While repositories’ efforts to build trustworthy digital repositories (TDRs) led to the establishment of ISO standards, much less research has been done regarding the user’s side, despite calls for an understanding of users’ trust of TDRs. In order to learn about users’ perspectives on trust in digital repositories, the present study investigated users’ definitions of trust and factors that influence users’ trust development, particularly addressing the users of three data repositories in the United States. A total of 19 participants were interviewed in this study. The results of this study indicate that users’ definition of trust is largely based on a lack of deception, when it comes down to the specific context of data repositories. Regarding factors influencing the development of users’ trust in repositories, organizational attributes, user communities (recommendations and frequent use), past experiences, repository processes (documentation, data cleaning, and quality checking), and users’ perception of the repository roles were identified.
... In 2000, Lynch observed that "virtually all determination of authenticity or integrity in the digital environment ultimately depends on trust…yet it is elusive," and the human element of it remains elusive (Roles of Identity and Trust section). Previous studies of repositories and trust have shown that, historically, the trusted digital repository movement conceptualized trust at the repository level and did not sufficiently account for end user conceptions of trust (Bak, 2016;Donaldson & Conway, 2015;Prieto, 2009;Yoon, 2014). Contemporary standards-such as the TRUST (Transparency, Responsibility, User focus, Sustainability, and Technology) Principles and the CoreTrustSeal-still measure trustworthiness through assessments of technology, infrastructure and policy, and only address interpersonal aspects indirectly (Lin et al., 2020;CoreTrustSeal Standards and Certification Board, 2022). ...
... Since curation work is usually invisible, it is difficult to measure how curators impact end users' conceptions of trust. However, studies do show that two areas curators typically focus on-data documentation and metadata-are key to end users' evaluations of data trustworthiness (Yakel et al., 2013;Yoon, 2014Yoon, , 2017Yoon & Lee, 2019). Furthermore, human connections to a repository seem to increase end user trust. ...
... In interviews with data repository end users, Frank et al. (2017) found that end users trust data more when they feel a sense of closeness to it through connections to individual people like data producers and repository staff. Yoon (2014) likewise found that while many end users did not know how repository staff were involved in data publication, those who did identified staff expertise as important to repository trustworthiness. Overall, end users associated trustworthiness with a 'lack of deception' about the data and the decisions made throughout the data management process, which includes curation, whether end users were aware of it or not (Yoon, 2014). ...
Research about trust and transparency within the realm of research data management and sharing typically centres on accreditation and compliance. Missing from many of these conversations are the social systems and enabling structures that are built on interpersonal connections. As members of the Data Curation Network (DCN), a consortium of United States-based institutional and non-profit data repositories, we have experienced first-hand the effort required to develop and sustain interpersonal trust and the benefits it provides to curation. In this paper, we reflect on the well-documented realities of curator and labour invisibility; the importance of fostering active communities (such as the DCN); and how trust, vulnerability and connectivity among colleagues leads to better curation practices. Through an investigation into data curators in the DCN, we found that, while curation can be isolating and invisible work, having a network of trusted peers helps alleviate these burdens and makes us better curators. We conclude with practical suggestions for implementing trust and transparency in relationships with colleagues and researchers.
... Even articles about trust in repositories often fail to define it (Oliver et al., 2011;Speck, 2010) or use the dictionary definition (Price & Smith, 2011). Recently, drawing on the organization and information systems literature, several scholars have attempted to elucidate the definition of trust in digital curation and emphasized the central relationship of trust between a designated community and a repository or data (Prieto, 2009;Yoon, 2014;Yoon & Lee, 2019). Prieto draws on the organization and information systems literature to posit a user-centric conceptualization of trust in digital repositories and argues "User communities are the most valuable component in ensuring a digital repository's trustworthiness. ...
... It is important, then, to study their perceptions of trust as factors critical to the success of digital repositories" (Prieto, 2009, p. 603). Yoon (2014) employs the organization and information systems literature to help explain how data reusers conceptualize trust in data repositories. She also uses this literature to operationalize factors in her quantitative investigation of data reusers trust in data (Yoon & Lee, 2019). ...
... Garrett and Waters (1996) cite integrity as a key trustworthiness factor for digital archives, they continue "[u]sers of archived information in electronic form and of archival services relating to that information need to have assurance that a digital archives is what it says that it is and that the information stored there is safe for the long term" (Garrett & Waters, 1996, p. 23). Qualitative studies lend support to these ideas, showing users' trust is related to their perceptions that data are valid and the data repository is not misleading or deceiving (Yoon, 2013(Yoon, , 2014. For these reasons, we hypothesize that data reusers are more likely to trust a data repository when they believe it demonstrates integrity. ...
Most studies of trusted digital repositories have focused on the internal factors delineated in the Open Archival Information System (OAIS) Reference Model-organizational structure, technical infrastructure, and policies, procedures , and processes. Typically, these factors are used during an audit and certification process to demonstrate a repository can be trusted. The factors influencing a repository's designated community of users to trust it remains largely unexplored. This article proposes and tests a model of trust in a data repository and the influence trust has on users' intention to continue using it. Based on analysis of 245 surveys from quantitative social scientists who published research based on the holdings of one data repository, findings show three factors are positively related to data reuser trust-integrity, identification , and structural assurance. In turn, trust and performance expectancy are positively related to data reusers' intentions to return to the repository for more data. As one of the first studies of its kind, it shows the conceptualization of trusted digital repositories needs to go beyond high-level definitions and simple application of the OAIS standard. Trust needs to encompass the complex trust relationship between designated communities of users that the repositories are being built to serve.
... Easy access to data was one of the most influential factors in determining social scientists' satisfaction with data reuse (Faniel, Kriesberg, & Yakel, 2016). Data repositories have a long history in social science, and they are known to support easy access to and reuse of available data through value-adding activities (Daniels, Faniel, Fear, & Yakel, 2012;Yoon, 2014a). However, social scientists searched for more data than was deposited in the repositories. ...
... Reusers assess data for a good fit for the purpose of their study (Faniel, Kansa, Kansa, Barrera-Gomez, & Yakel, 2013), for data quality (Cragin & Shankar, 2006;Van House, 2002), or generally for reusability (Faniel & Jacobsen, 2010). Social scientists are also concerned with choosing good quality, trustworthy data and avoiding data with errors (Yoon, 2014a(Yoon, , 2016(Yoon, , 2017. Assessing data for each of these qualities requires different criteria; some important assessment factors which have been identified include data producers' ability to generate trustworthy data, other reusers' positive experiences using the data, and soundness of methodology used to produce data (Faniel & Jacobsen, 2010;Faniel, Kansa, Kansa, Barrera-Gomez, & Yakel, 2013;Yoon, 2017;Zimmerman, 2008). ...
... Data repositories can reduce perceived effort, enhance positive attitudes, and influence the actual behaviors of social scientists regarding data reuse. In the social science context, data repositories play an important role in data sharing and reuse, although data reuse also still occurs through personto-person exchange and interaction (e.g., Faniel & Jacobsen, 2010;Yoon, 2014a). Social science data repositories contribute to data reuse, not just through easy access to data, but also by providing value-added services which ensure current and future use of that data, such as managing provenance, correcting errors, and providing supporting documentation, all of which reduce the effort expectancy required for data reuse (Daniels et al., 2012;Fear & Donaldson, 2012). ...
Many disciplines within the social sciences have a dynamic culture of sharing and reusing data. Because social science data differ from data in the hard sciences, it is necessary to explicitly examine social science data reuse. This study explores the data reuse behaviors of social scientists in order to better understand both the factors that influence those social scientists' intentions to reuse data and the extent to which those factors influence actual data reuse. Using an integrated theoretical model developed from the theory of planned behavior (TPB) and the technology acceptance model (TAM), this study provides a broad explanation of the relationships among factors influencing social scientists' data reuse. A total of 292 survey responses were analyzed using structural equation modeling. Findings suggest that social scientists' data reuse intentions are directly influenced by the subjective norm of data reuse, attitudes toward data reuse, and perceived effort involved in data reuse. Attitude toward data reuse mediated social scientists' intentions to reuse data, leading to the indirect influence of the perceived usefulness and perceived concern of data reuse, as well as the indirect influence of the subjective norm of data reuse. Finally, the availability of a data repository indirectly influenced social scientists' intentions to reuse data by reducing the perceived effort involved.
... Given the importance of trust in data and the complexity of the landscape of data reuse, this research explores data reusers' processes of making trust judgments about data. Trust in data has received recent attention among data reuse researchers, exploring the factors that influence reusers' trust in data (e.g., Birnholtz & Bietz, 2003;Faniel & Jacobsen, 2010;Van House, 2002;Wallis et al., 2007;Zimmerman, 2008) and in data repositories (e.g., Donaldson & Conway, 2015;Yakel, Faniel, Kriesberg, & Yoon, 2013;Yoon, 2014). Although previous research provides a foundational understanding of reusers' trust in data, this study focuses on the process of trust judgment and the dynamic nature of trust as it appears during this process. ...
... Previous research also shows that reusers' trust judgments can be closely related to the data repositories from which they get the data, particularly when they know about how the data have been processed and "cooked" (Carlson & Anderson, 2007;Yoon, 2014). Other organizational attributes of repositories, such as integrity, transparency, reputation, and structural assurance that guarantees preservation and sustainability, have also been identified as important trust factors Yoon, 2014), as have reusers' perceptions and awareness of the roles of repositories (Yoon, 2014). ...
... Previous research also shows that reusers' trust judgments can be closely related to the data repositories from which they get the data, particularly when they know about how the data have been processed and "cooked" (Carlson & Anderson, 2007;Yoon, 2014). Other organizational attributes of repositories, such as integrity, transparency, reputation, and structural assurance that guarantees preservation and sustainability, have also been identified as important trust factors Yoon, 2014), as have reusers' perceptions and awareness of the roles of repositories (Yoon, 2014). ...
Data reuse refers to the secondary use of data-not for its original purpose but for studying new problems. Although reusing data might not yet be the norm in every discipline, the benefits of reusing shared data have been asserted by a number of researchers, and data reuse has been a major concern in many disciplines. Assessing data for trustworthiness becomes important in data reuse with the growth in data creation because of the lack of standards for ensuring data quality and potential harm from using poor-quality data. This research explores many facets of data reusers' trust in data generated by other researchers focusing on the trust judgment process with influential factors that determine reusers' trust. The author took an interpretive qualitative approach by using in-depth semistructured interviews as the primary research method. The study results suggest different stages of trust development associated with the process of data reuse. Data reusers' trust may remain the same throughout their experiences, but it can also be formed, lost, declined, and recovered during their data reuse experiences. These various stages reflect the dynamic nature of trust.
... The Open Archival Information System (OAIS) Reference Model, ISO 14721, provides a conceptualization and terminology for archival systems, a necessary context for DQA in RDRs (Peng et al., 2015). ISO 16363, often referred to as the Trustworthy Digital Repositories (TDR) checklist, is a well-established standard that provides audit metrics for certifying trustworthy digital repositories based on the OAIS model (Corrado, 2019;Yoon, 2014). Its companion ISO 16919 defines requirements for auditing bodies (Corrado, 2019;Yoon, 2014). ...
... ISO 16363, often referred to as the Trustworthy Digital Repositories (TDR) checklist, is a well-established standard that provides audit metrics for certifying trustworthy digital repositories based on the OAIS model (Corrado, 2019;Yoon, 2014). Its companion ISO 16919 defines requirements for auditing bodies (Corrado, 2019;Yoon, 2014). Other relevant standards identified by the literature analysis include ISO 25012 and 25024, which define quality characteristics, an evaluation process, and associated measures for data products (Gualo et al. 2021), and ISO 19115 for providing standardized metadata to users (Owens et al. 2022). ...
Data quality issues can significantly hinder research reproducibility, data sharing, and reuse. At the forefront of addressing data quality issues are research data repositories (RDRs). This study conducted a systematic analysis of data quality assurance (DQA) practices in RDRs, guided by activity theory and data quality literature, resulting in conceptualizing a data quality assurance model (DQAM) for RDRs. DQAM outlines a DQA process comprising evaluation, intervention, and communication activities and categorizes 17 quality dimensions into intrinsic and product‐level data quality. It also details specific improvement actions for data products and identifies the essential roles, skills, standards, and tools for DQA in RDRs. By comparing DQAM with existing DQA models, the study highlights its potential to improve these models by adding a specific DQA activity structure. The theoretical implication of the study is a systematic conceptualization of DQA work in RDRs that is grounded in a comprehensive analysis of the literature and offers a refined conceptualization of DQA integration into broader frameworks of RDR evaluation. In practice, DQAM can inform the design and development of DQA workflows and tools. As a future research direction, the study suggests applying and evaluating DQAM across various domains to validate and refine this model further.
... Most of the earlier work has based on self-reported data re-use and focused especially on the experiences and needs of scholars [e.g. [7][8][9][10][11][12]. However, before data citation practices are fully formalized in social sciences, log data and number of downloads are useful to measure the frequency of data re-use [5,13,14]. ...
... data about the data) is valued by the data users [8,9,12,62]. Other factors influencing the users' trust in the data archives are recommendations, frequency of use, past experiences, and perceptions of the role of the archive [10]. However, frequently downloaded datasets are probably more well-known and thus, more visible for the users. ...
The aim of this paper is to investigate the re-use of research data deposited in digital data archive in the social sciences. The study examines the quantity, type, and purpose of data downloads by analyzing enriched user log data collected from Swiss data archive. The findings show that quantitative datasets are downloaded increasingly from the digital archive and that downloads focus heavily on a small share of the datasets. The most frequently downloaded datasets are survey datasets collected by research organizations offering possibilities for longitudinal studies. Users typically download only one dataset, but a group of heavy downloaders form a remarkable share of all downloads. The main user group downloading data from the archive are students who use the data in their studies. Furthermore, datasets downloaded for research purposes often, but not always, serve to be used in scholarly publications. Enriched log data from data archives offer an interesting macro level perspective on the use and users of the services and help understanding the increasing role of repositories in the social sciences. The study provides insights into the potential of collecting and using log data for studying and evaluating data archive use.
... Other studies have focused on trust in repositories and databases as complex systems. Yoon (2013) found that users' perceptions of digital repositories' trustworthiness were influenced by actions, such as quality checking and provision documentation, taken by the repository, as well as being shaped both by the user's past experiences and by a repository's reputation in the user communities. In a study comparing archaeologists' and social scientists' use of data repositories, Yakel et al. (2013) found variations between disciplines regarding what factors shaped users' trust in the repositories. ...
... Researchers' strategies also vary regarding what components of IODP systems they emphasize when considering sample trustworthiness and what facets of each component they emphasize. The components that researchers focus on when making trust judgments about physical samples are similar to those found in studies of how researchers trust in data: the methods used to produce data (Faniel and Jacobsen, 2010;Faniel and Yakel, 2011;Faniel et al., 2012;Fear and Donaldson, 2012), the competence of data producers (Van House, 2002a,b;Jirotka et al., 2005;Faniel et al., 2013), and the systems used to manage and curate datasets Yoon, 2013). ...
In recent years, research funding agencies, universities, and governments have become increasingly concerned with promoting the reuse of research datasets. Enabling researchers to evaluate the trustworthiness and fitness-for-use of research datasets produced by others is critical for facilitating the reuse of these datasets. Understanding how researchers make these evaluations is crucial for developing digital infrastructure and tools, such as data repositories and metadata schema, in a way that better supports researchers in making these evaluations. Physical samples such as rocks are critical for generating datasets in many scientific domains. Often, samples are collected on field expeditions conducted by large infrastructural projects. These projects comprise many human and non-human components that affect the quality and integrity of samples. However, little is known about whether and how prospective dataset users evaluate the samples' trustworthiness and sample collection processes underlying these datasets. Researchers‘strategies for evaluating sample trustworthiness are explored through a longitudinal qualitative case study (ethnographic observation, interviews (n = 66), and document analysis) of subseafloor biosphere research, an earth sciences domain. Domain researchers use rock samples collected on research cruises conducted by the International Ocean Discovery Program (IODP). Subseafloor biosphere researchers are primarily concerned about samples being compromised by microbiological contamination. Researchers vary regarding the components of IODP infrastructure they consider when evaluating sample trustworthiness. These components include methods to process samples, people handling samples, IODP policies and procedures, and IODP organizational politics. Researchers‘strategies vary according to their disciplinary background, with microbiologists employing more fine-grained judgments about methods; whether researchers have participated in IODP expeditions, with those who have employing more fine-grained judgments about people involved; and whether researchers have ever been involved in organizing cruises or serving on IODP committees, with those who have employing more fine-grained judgments about many aspects of cruises. Researchers who make less complex decisions may be prone to erroneously trusting contaminated samples; researchers who make more complex decisions may be prone to erroneously discarding uncontaminated samples. The paper concludes by considering implications for the design of digital infrastructures to support researchers in evaluating sample trustworthiness.
... Aktuell verfügbare Daten deuten weiters darauf hin, dass die Bereitstellung, Nutzung und auch der Einsatz von Sekundärdaten stark von den Einstellungen und den Verhaltensweisen der Forschenden abhängig sind und keine einheitliche Entwicklung in den Sozialwissenschaften stattfindet, die Forschung und Lehre an die veränderten Rahmenbedingungen annähert (Yoon 2014a;Tenopir et al. 2011 ...
... Dazu gehören das weite Feld der Anreize und Negativanreizez.B. Preise -, genauso wie Standards und Normen von Förderorganisationen, Zeitschriftenverlagen sowie Fachgesellschaften (DiMaggio und Powell 1983;Scott 2014 Diese Meinung spiegelt sich auch in den Entwicklungen der letzten 20 Jahre wider (Marcial und Hemminger 2010). Teile der Wissenschaftscommunity fordern, dass Forschungsdaten, die mit öffentlichen Mitteln generiert werden, allen interessierten Parteien frei und offen zugänglich sein müssten (Arzberger et al. 2004 (Cragin et al. 2010;Daniels et al. 2012;Yakel et al. 2013;Yoon 2014a (Campbell et al. 2002;Kim und Adler 2015;Louis et al. 2002;Tenopir et al. 2011;Vickers 2011;Wallis et al. 2013). Die Sekundärdatennutzung bzw. ...
The report covers the DA(ta) SH(aring) - 2020 survey study, which dealt with issues of data sharing, data managment as well as data (re-)use in the Austrian social sciences.
The german language report is a comprehensive overview over the empirical results of the study.
... Trust and trustworthiness are the basis of human interaction: trust is the act of putting faith in or taking a risk about a person or object, while trustworthiness is a characteristic or attribute of the trustee (Akter, D'Ambra and Ray, 2011;Kelton, Fleischmann and Wallace, 2008;Yoon, 2014). Wynne (1992) disagrees that trustworthiness is an intrinsic attribute of any person, arguing instead that trust and trustworthiness are instead relational based upon social relationships between people. ...
... This refects the interaction-based nature of data repository-data user trust development over time. Prior work on trust development has focused on certifying repository and data trustworthiness (Donaldson and Conway, 2015;Yakel, Faniel, Kriesberg and Yoon, 2013;Yoon, 2014). ...
The decision to allow users access to restricted and protected data is based on the development of trust in the user by data repositories. In this article, I propose a model of the process of trust development at restricted data repositories, a model which emphasizes the increasing levels of trust dependent on prior interactions between repositories and users. I find that repositories develop trust in their users through the interactions of four dimensions – promissory, experience, competence, and goodwill – that consider distinct types of researcher expertise and the role of a researcher’s reputation in the trust process. However, the processes used by repositories to determine a level of trust corresponding to data access are inconsistent and do not support the sharing of trusted users between repositories to maximize efficient yet secure access to restricted research data. I highlight the role of a researcher’s reputation as an important factor in trust development and trust transference, and discuss the implications of modelling the restricted data access process as a process of trust development.
... Studying how users' experiences influenced their perceptions of trust in data repositories, Yoon 14 found that "users' awareness of repositories' roles or functions can be one factor for developing users' trust". Users often trust repositories based on their own experiences, repository practices and reputation, and on the experiences of other community members 9,14,15 . ...
... Studying how users' experiences influenced their perceptions of trust in data repositories, Yoon 14 found that "users' awareness of repositories' roles or functions can be one factor for developing users' trust". Users often trust repositories based on their own experiences, repository practices and reputation, and on the experiences of other community members 9,14,15 . Users' trust in data is also associated with their trust in the archive from which the content was obtained 16 . ...
As information and communication technology has become pervasive in our society, we are increasingly dependent on both digital data and repositories that provide access to and enable the use of such resources. Repositories must earn the trust of the communities they intend to serve and demonstrate that they are reliable and capable of appropriately managing the data they hold. Following a year-long public discussion and building on existing community consensus , several stakeholders, representing various segments of the digital repository community, have collaboratively developed and endorsed a set of guiding principles to demonstrate digital repository trustworthiness. Transparency, Responsibility, User focus, Sustainability and Technology: the TRUST Principles provide a common framework to facilitate discussion and implementation of best practice in digital preservation by all stakeholders.
... Given the range of organizations involved in curating video records of practice, we were interested in exploring issues of trust in the repositories and the data. Previous studies have focused on more traditional data and repositories and trust (Donaldson & Conway, 2015;Yakel, Faniel, Kriesberg & Yoon, 2013) or research data that is more numerical or textual (Yoon, 2014). In the management information systems literature, trust in institutions is linked to data quality, but this research centers on for-profit organizations (Lee, Strong, Kahn & Wang, 2002). ...
... In addition to preserving, curating and providing access to data (Corti, 2011;Giarlo, 2013), one of the primary aims of data repositories is "to facilitate communication, collaboration and interactions" among data producers and reusers (Chowdhury, 2010). The responsibility to meet the needs of repository reusers beyond mere access to data (Russell & Day, 2010;Yoon, 2014) may be in conflict with some of the ways that repositories are structured. ...
This paper applies Pirson and Malhotra's (2011) framework for organizational trust to data reuse in an educational context. Their framework delineates stakeholders along two axes: depth of the interactions (e.g., shallow or deep) and the locus of the relationship (e.g., internal or external). We analyzed 139 survey responses and 44 in-depth interviews with users of repositories holding video records of practice. We found that factors such as data quality, co-production of data between the repository and data producer, responsiveness of staff, and transparency of curation processes influenced trust, and that responsiveness and transparency were of particular importance for trust development for users with deeper interactions and a more internal loci of relationships to repositories.
... Users need contextual information about collection methods, instrumentation, other analyses, and how variables are defined and measured (Curty, 2016;Faniel, Kansa, et al., 2013;Kern & Mathiak, 2015;Yoon, 2014a). When necessary, researchers turn to other sources to develop the necessary context (Fielding & Fielding, 2008), consulting colleagues, codebooks (Faniel & Yakel, 2017) or bibliographies . ...
A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval.
... Bak (2016), was of the view that "the notion of trust within trustworthy digital repositories standards culture is itself evolving in the positive direction that emphasizes user perceptions of trust rather than seeking to establish objective evidence of trust". Yoon (2014) also emphasized that much attention has been paid to establishment of ISO standards towards trustworthy digital repositories, with very little attention on the users who are equally important. It is important for data repositories to maximize research outcomes and facilitate collaboration and sharing, as well as, ensuring the quality of the data and accompanying services (Mehnert et al., 2019). ...
In support of the open science movement and as a signatory of the Berlin Declaration, the Cape Peninsula University of Technology has since 2013 developed various systems, infrastructures and workflows to support open access and good research data management practices at the institution, providing a highly functional environment. Institutional policies that include a Research Data Management Policy and an Open Access Policy, data deposit guidelines and data deposit platforms are currently in place and utilized by affiliated postgraduate students and researchers from faculties, research units and entities as well as researchers from academic support units in alignments with FAIR principles. The strategy of a requirement that postgraduate students must submit their research data together with their theses for graduation purposes has increased the advocacy and publishing of datasets and includes the supervisors as part of the review process. The purpose of this paper is therefore to highlight the initial developmental trajectory and what was achieved to date. This includes the selection of the platform through the ilifu project in the Western Cape, the implementation and strengthening of the repository review workflows to include a number of key role players to ensure the quality and integrity of the data as well as ethics approval checks, the development of the data management planning tool and a recent upgrade to include a section for POPIA compliancy, advocacy, training and processes that the institution has embarked on to secure the research data platform through proper preservation methodologies/approaches as a preservation platform was recently procured. Some challenges will be discussed and how those were addressed. The paper will also outline the process of how the institution embarked on applying to have the data repository certified as trustworthy through an international institution, the CoreTrustSeal, and will outline this near three-year journey to work towards achieving their 17 requirements.
... Addressing uncertainty is one of the preconditions for building trust in data (Yoon 2014). Uncertainty arises due to lack of information or due to the gap that exists between the information possessed and the information required (Tushman and Nadler 1978). ...
Organisations are increasingly leveraging self-service analytics to empower business users to independently access, analyse, and interpret data for informed decision-making. Amid the surge in self-service adoption, whether business users trust the data for self-service analytics is a key concern for organisations. Drawing on information processing theory (IPT), we propose a framework that links building trust in data through data governance with uncertainty and ambiguity in a self-service environment and decision-making performance. The details of the framework explain how organisations may address uncertainty and ambiguity in the self-service environment by identifying the self-service needs, building data governance mechanisms to meet those needs, and using self-service analytics to make informed business decisions. Our study contributes to business analytics literature by examining how data governance plays a pivotal role in building trust in data to enable self-service analytics.
... Trust is defined as "a: Assured reliance on the character, ability, strength, or truth of someone or something [and] b: One in which confidence is placed" (Merriam-Webster 2021). Trust remains a challenging concept to operationalize, in part because its definition and characterization differ by discipline, goal, and unit of analysis (Rousseau et al. 1998;Gambetta 1988;Yoon 2014). Mayer et al. (1995) derive three attributes, now widely used (cf. ...
Historical instrumental weather observations are vital to understanding past, present, and future climate variability and change. However, the quantity of historical weather observations to be rescued globally far exceeds the resources available to do the rescuing. Which observations should be prioritized?
Here we formalize guidelines help make decision on rescuing historical data. Rather than wait until resource-intensive digitization is done to assess the data’s value, insights can be gleaned from the context in which the observations were made and the history of the observers. Further insights can be gained from the transcription platforms used and the transcribers involved in the data rescue process, without which even the best historical observations can be mishandled. We use the concept of trust to help integrate and formalize the guidelines across the lifecycle of data rescue, from the original observation source to the transcribed data element. Five cases of citizen science-based historical data rescue, two from Canada and three from Australia, guide us in constructing a trust checklist. The checklist assembles information from the original observers and their observations to the current transcribers and transcription approaches they use. Nineteen elements are generated to help future data rescue projects answer the question of whether resources should be devoted to rescuing historical meteorological material under consideration.
... 7 In both cases, repositories-organizations or other governing entities-manage content, infrastructure, governance, access, and attribution, often on behalf of various contributors and in the public interest. [8][9][10][11][12][13] For example, trusted health information (or data) brokers are called such because they ensure the integrity of data and appropriate access to information. 14 Collaborative knowledge engineering and knowledge management, while distinct disciplinary fields, are critical to the knowledge ecosystem and both require formal and informal agreements addressing compliance of knowledge artifacts with accepted industry standards and expected functionality. ...
Introduction
While data repositories are well‐established in clinical and research enterprises, knowledge repositories with shareable computable biomedical knowledge (CBK) are relatively new entities to the digital health ecosystem. Trustworthy knowledge repositories are necessary for learning health systems, but the policies, standards, and practices to promote trustworthy CBK artifacts and methods to share, and safely and effectively use them are not well studied
Methods
We conducted an online survey of 24 organizations in the United States known to be involved in the development or deployment of CBK. The aim of the survey was to assess the current policies and practices governing these repositories and to identify best practices. Descriptive statistics methods were applied to data from 13 responding organizations, to identify common practices and policies instantiating the TRUST principles of Transparency, Responsibility, User Focus, Sustainability, and Technology
Results
All 13 respondents indicated to different degrees adherence to policies that convey TRUST. Transparency is conveyed by having policies pertaining to provenance, credentialed contributors, and provision of metadata. Repositories provide knowledge in machine‐readable formats, include implementation guidelines, and adhere to standards to convey Responsibility. Repositories report having Technology functions that enable end‐users to verify, search, and filter for knowledge products. Less common TRUST practices are User Focused procedures that enable consumers to know about user licensing requirements or query the use of knowledge artifacts. Related to Sustainability, less than a majority post describe their sustainability plans. Few organizations publicly describe whether patients play any role in their decision‐making.
Conclusion
It is essential that knowledge repositories identify and apply a baseline set of criteria to lay a robust foundation for their trustworthiness leading to optimum uptake, and safe, reliable, and effective use to promote sharing of CBK. Identifying current practices suggests a set of desiderata for the CBK ecosystem in its continued evolution
... User's confidence, 11. "Lack of deception", 12. Independent review, 13. Reuse (Giarlo 2013, Yoon 2014, Daraio et al. 2016). ...
Digital information search tools are ubiquitous and more than ever
embedded in the activities of our everyday lives. Search engines, such as Google,
help us to find relevant information, solve problems, and support our decision-making.
This paper shows important trends in a wider framework of Fourth
Industrial Revolution and web generations. On a level of digital information
search tools, trends and emergent technologies are described in more detail and
accompanied by recent examples of tools.
It is of critical importance to recognize possible challenges of algorithmic
culture today and in the future. We describe some of the related problems and
underline that ethical norms and legal frameworks must be incorporated to
ensure that technologies will not become even more authoritative and powerful
as they are now.
... This relationship between user confidence in preservation devices and confidence in the digital content of those devices has been modeled for digital archives in general (Donaldson, 2019) and formalized as an ISO standard (Open Archival Information System, ISO 14721:2012). Empirical studies, such as those by Yakel et al. (2013) or Yoon (2014), have led to a better understanding of some of the key factors of trust or mistrust in data repositories. Among these factors, three appear to be particularly important: the transparency of the system, the guarantee (promise) of long-term preservation (sustainability), and the reputation of the institution that manages and/or hosts the system. ...
The outburst of the COVID-19 pandemic has boosted the need for seamless, unrestricted, fast, and free access to the latest research results on the virus, on its treatment, prevention, protocols, and so on. Open access to publications and research data, suddenly, became self-evident, not only for researchers in life and medical sciences but also for politicians, journalists, and society as a whole. At the same time, this sudden awareness triggered another debate on the quality and, moreover, the trustworthiness of this mass of information made available most often without any form of quality control (peer review). Thousands of datasets from research on COVID-19 and related topics have already been deposited on data repositories. Our chapter discusses the issue of the quality and trustworthiness of research data in data repositories using examples from the ongoing pandemic. It offers insights into some fundamental concepts and summarizes recommendations for quality assurance and evaluation of research data.
... Trustworthiness of research data repositories is highlighted, since they should, for example, encourage trust among researchers who may still have reservations against data sharing (Klump, 2017). Researchers' trust in a research data repository is influenced by several factors, including the validity and accuracy of datasets in its collection and the documentation processes it adopts (Yoon, 2014). Organizational aspects also factor into trustworthiness, for example the ability to preserve datasets long-term. ...
Structured metadata are of particular importance in the context of facilitating research data (re-)use. Although research data repositories create and manage metadata records, existing research offers limited insights into the relationship between repositories and metadata for research data. Therefore, in conducting a quantitative assessment informed by metadata quality requirements, this thesis aims at making distinctive features of metadata for research data visible, specifying the potential influence of repository characteristics on metadata, and exploring changes to metadata records. The analysis showed variations in metadata completeness across repositories. Within repositories, metadata descriptions are relatively homogenous. These findings suggest that repositories have developed distinctive and consistent practices for describing data. On average, descriptions comprise 487.3 characters, and 5.52 years passed between the year a dataset was published and the metadata record was registered. Differences in the completeness of metadata records, description length and timeliness were significant across repository types and certification status, whereas differences in collection homogeneity were not significant. Overall, most metadata records in the sample were changed, which conforms with the conceptualization of metadata for research data as dynamic and changeable objects. Differences in the number of changes are significant across repository types.
... However, these instruments define trustworthiness in terms of descriptive programmatic or technological attributes, rather than operational outcomes of those programs or technologies (Dryden 2011). Thus, trustworthiness is a quality best associated with preservation management, rather than exploitive consumption of resources preserved through that management (Yoon 2014). In other words, trustworthiness primarily measures what preservation managers do (Xie and Matusiak 2016), not the stakeholder-facing experiential affordances enabled by that doing. ...
Digital preservation fulfills a critical role in the digital continuity of individual, institutional, and cultural memory. It is important for archival stewards and stakeholders to know whether or not those activities have been successful in order to deploy finite programmatic resources most relevantly, effectively, and productively. While preservation trustworthiness has been subject to extensive examination, the complementary evaluative quality of success has received less critical consideration. This study looks at how the preservation community ascribes meaning to the concept of success through attitudinal norms tacitly embedded in domain discourse. These are recovered through qualitative content analysis of selected preservation policy statements, which act as public affirmations of the archival service “contract” regarding stewardship intention and reciprocal stakeholder expectation. Success is a measure of the alignment between anticipated outcomes and actual preserved state resulting from intentional intervention. Communicological critique of the norms illuminates why the measure of success remains problematic and suggests avenues by which metrical practice can be augmented to enhance its evaluative power. This includes repositioning evaluative prerogatives to incorporate concern for the persistence not only of authentic digital information objects but also legitimate communicative experiences.
... Customer loyalty, impacted by trust, may lead to re-purchase intention [19]. In general, trust becomes essential for future actions, when a lack of knowledge exists in an individual or group of people and the situation would demand dependency to someone else who is believed to own experience and expertise in the related fields [20]. ...
... The elements of trust also include the lineage, version, and error rate of data, and the fact that they are understood and acceptable [49]. In the case of data repositories, the perception of trust is based largely on a "lack of deception" [50]. Figure 1 shows the relationships between elements of trust, where the numbed elements of the figure are the following ones: ...
This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.
... It is essential, then, that there is quality control of all digitally developed materials, with a particular emphasis on those shared on the Internet (Mizzaro 2003;Gordillo Mendez, Barra Arias, and Quemada Vives 2018;Idiegbeyan-Ose et al. 2016; Ayuso García and Martínez Navarro 2006). So it is contemplating in numerous studies over the past 20 years (Palavitsinis, Manouselis, and Sánchez-Alonso 2017), placing the quality control as an essential to maintain user confidence in repositories, digital libraries and other resources on the network factor (Yoon 2014). Any failure in the quality of a document is replicated and extended by being shared on the network. ...
The representation of musical information through notation systems is a process of multidimensional nature, of high complexity , and which is subject to a practically infinite level of casuistry. The translation of these processes into the digital domain has meant an unprecedented revolution for the recording and dissemination of musical information. This translation implies the development of systems that allow the most significant possible amount of data to be recorded flexibly and rigorously, making it possible to adapt to potential contexts while at the same time collecting the most specific aspects. The processes of transcription and creation of digital scores depend to a large extent on the degree of expertise of the user and the criteria adopted by the user in the process. The present work proposes a tool to analyze the formal quality of the electronic scores produced from the LilyPond system with the aim of detecting in an automated way the syntactic errors that may occur in the transcription, as well as to adapt the criteria by which they are governed according to the needs or requirements of each institution. This tool has been developed as an extension of the SonarQube platform. Its development and future application can allow the control of the quality of the records that make up the collections in repositories and digital music libraries. Also, its can allow to assist the professionals to create music score following the quality metrics.
... The identified trust building behaviors will be later converted into design features and interface design objects to be used in communication and collaboration systems (Morita & Burns, 2014), has dimensions that are predictability, integrity and benevolence (Darrough, 2006), included repository functions, transparency, structural assurance to include guarantees of preservation and sustainability (Yoon, 2014), three dimension of trust consist of integrity, benevolence and ability (Robbin & Judge, 2013), relationships, community, cooperation and mutual commitment that characterize social capital (Asiaei & Jusoh, 2015). ...
The main objective of this research is to explore capabilities related to trust, self-efficacy, intellectual capital and job satisfaction at head-hunter companies in Indonesia. Development of human resources needs to be done through the strengthening of intellectual capital. Intellectual capital is needed head-hunter in improving company performance. The key to successful head-hunter companies if it has human resources that have added value, especially strong intellectual capital. Research sampling was conducted on 253 candidates who utilize head-hunter services an effort to develop themselves. Quantitative research was developed by utilizing structural equation modeling. Research model developed head-hunter companies that describes intellectual capital as research findings refers to previous model of research. This finding concludes that trust and self-efficacy have significant influence on intellectual capital. Another conclusion stated that intellectual capital has significant effect on job satisfaction. The concept states that intellectual capital can be integrated in global perspective as framework for developing an organization.
... A 'trusted custodian' and a 'trusted repository' are simply mechanisms for preserving the record's authenticity and reliability. The impacts on public trust made by broader human interactions with the record (by researchers, users and communities) are largely unexplored (Sundqvist 2011;Yoon 2014Yoon , 2017. Understandings of trust across sociology, philosophy and psychology do not take an object (i.e. a record) as their starting point for definition and exploration, but focus on how trust operates in human relationships. ...
Government departments and agencies around the world routinely collect administrative data produced by citizen interaction with the state. The UK government increasingly frames data as an ‘asset’. The potential in administrative data can be exploited by sharing and linking across datasets, but when the rhetoric of the benefits of data sharing is bound up in commercial exploitation, trustworthy motivations for sharing data come into question. Such questions are framed around two apparently conflicting public goods. The public good in re-using data to increase government efficiency and to enhance research is set against the public good in protecting privacy. Privacy is a collective as well as an individual benefit, enabling the public to participate confidently in citizen-state interactions. Balancing these public goods is challenging given rapidly evolving technology and data science. The analysis presented here draws on research undertaken by the authors as part of the Administrative Data Research Centre in England. Between 2014 and 2017, four case studies were conducted on government administrative data across education, transport, energy and health. The purpose of the research was to examine stakeholder perspectives in relation to administrative data sharing and re-use. The themes of trust, risk and consent were chosen to articulate the research questions and analysis: this article focuses on the findings related to trust. It explores the notion of trust in the collection, analysis, linkage and re-use of routinely collected government administrative data in England. It seeks to demonstrate that securing public trust in data initiatives is dependent on a broader balance of trust between a network of actors involved in data sharing and use.
... Users need contextual information about collection methods, instrumentation, other analyses, and how variables are defined and measured (Curty, 2016;Faniel, Kansa, et al., 2013;Kern & Mathiak, 2015;Yoon, 2014a). When necessary, researchers turn to other sources to develop the necessary context (Fielding & Fielding, 2008), consulting colleagues, codebooks (Faniel & Yakel, 2017) or bibliographies . ...
A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval.
... For her part, Yoon [41] (p. 17) indicates that, in her survey, data repository users based their definition of trust largely on a "lack of deception". ...
There is worldwide interest in the potential of open science to increase the quality, impact, and benefits of science and research. More recently, attention has been focused on aspects such as transparency, quality, and provenance, particularly in regard to data. For industry, citizens, and other researchers to participate in the open science agenda, further work needs to be undertaken to establish trust in research environments. Based on a critical review of the literature, this paper examines the issue of trust in an open science environment, using virtual laboratories as the focus for discussion. A trust framework, which has been developed from an end-user perspective, is proposed as a model for addressing relevant issues within online research data services and tools.
... Previous studies also confirm that data practices and behaviors may vary due to the disciplinary or scholarly communities' influences (e.g., Birnholtz & Bietz, 2003;Carlson & Anderson, 2007;Faniel, Barrera-Gomez, Kriesberg, & Yakel, 2013;Rolland & Lee, 2013) because data sharing and reuse are an ingrained practice in some disciplinary traditions (Borgman et al., 2012;Faniel & Jacobsen, 2010). Infrastructure for data sharing and reuse also influences the researchers' data practices, since social science has a long history of supporting data sharing and reuse through data repositories and relevant policies (Cragin, Palmer, Carlson, & Witt, 2010;Daniels, Faniel, Fear, & Yakel, 2012;Yakel, Faniel, Kriesberg, & Yoon, 2013;Yoon, 2014a). Thus, employing a holistic and multidimensional approach is critical for understanding the complexity of data practices and the factors that drive or hinder data sharing and reuse. ...
The discipline of social science has unique research norms and cultures regarding data sharing and reuse that can be affected by complex factors related to context, time and dependence on human subjects. Compared with STEM disciplines, social sciences emphasize the protection of study participants and observees. Extra effort is required from reusers to preserve data interconnectedness in order to guarantee the data's understandability and informative value. In this panel, the panelists will present their research findings and provide perspective on social science data sharing and reuse, including factors that may influence data reuse behavior, researchers' trust judgment in data for data reuse, and infrastructural barriers and incentives for data sharing among social scientists. This panel aims to provide an overview of the current state of social science data reuse and sharing, and, in collaboration with panel participants, elicit topics for future research. It also proposes a practical agenda to develop alternative incentives for individual researchers, and potential ways in which data sharing and reuse can be improved, coordinated, and encouraged among social scientists. Copyright
The open data movement is often touted as a sweeping strategy to democratize science, promote diverse data reuse, facilitate reproducibility, accelerate innovation, and much more. However, the potential perils of open data are seldom examined and discussed in equal measure to these promises. As we continue to invest in open data, we need to study the full spectrum of what open data facilitates in practice, which can then inform future policy and design decisions. This paper aims to address this gap by presenting an investigative digital ethnography of one contrarian community, anthropogenic climate change (ACC) skeptics, to describe how they process, analyze, preserve, and share data. Skeptics often engage in data reuse similar to conventional data reusers, albeit for unconventional purposes and with varying degrees of trust and expertise. The data practices of ACC skeptics challenge the assumption that open data is universally beneficial. These findings carry implications for data repositories and how they might curate data and design databases with this type of reuse in mind.
Purpose
The impact of innovative web portals on users, from access to application, is gaining interest as the global call for increased data availability gains momentum. This study reports on the perceptions of portal end users about usage and access to digital data across a range of fields of practice.
Design/methodology/approach
Data were collected and analysed from interviews ( n = 132) and email feedback ( n = 235) from end users of interoperable spatial knowledge web portals.
Findings
Data reveal that users attribute importance to ease of access and applicability, and to confidence and trust in data. The acquisition of data assists with reducing knowledge silos, facilitates knowledge sharing and decision-making. Digital data portals enable the building of stronger collaborations between different groups of individuals and communities leading to improved outcomes and more positive developments across varied discipline and practice areas.
Practical implications
Recommendations for developing online portals to optimise knowledge transfer and associated benefits, for users, are offered.
Originality/value
By collecting extensive qualitative data drawn from the experiences of end users of digital data portals, this paper provides new insights, thereby addressing a knowledge gap in the published literature about the use of technology uptake and the application of online data for practice and industry benefit.
The landscape of data repositories is very varied and heterogeneous. The issue of trust is at the heart of the development of research data repositories – trust in both the content and the quality of the facility. In computing, a repository is a centralized and organized store of data. It can be one or more databases where files are located for distribution over the network or a place directly accessible to users. The cost of this equipment has led research communities to collaborate around data collection and thus to set up a system of data standardization and dissemination. Data repositories contribute to the mechanism of research data publishing. This chapter proposes that considering data repositories as digital devices, that is, as tools for mediating scientific information between producers and users. The actual use of a new device or technology is affected by several factors, including perceived usefulness, ease of use, quality of services and results.
This bibliography presents over 225 selected English-language articles and books that are useful in understanding the publication and citation of research data. It also provides limited coverage of closely related topics, such as research data identifiers (e.g., DOI) and scholarly metrics. Most sources have been published from January 2009 through December 2021. It includes full abstracts for works under certain Creative Commons Licenses. It is also available as a website (http://digital-scholarship.org/citation/citation.htm), which includes a Google Translate link. This work is licensed under a Creative Commons Attribution 4.0 International License. Keywords: altmetrics, data citation, data journals, data publication, data reuse, data sharing, data sharing policies, Digital Object Identifiers, funding agency requirements, open access, open access journals, open science, peer review, persistent identifiers, scholarly metrics, research data, research data management, research data publishing, scholarly journals, and scholarly publishing.
Trustworthy data repositories ensure the security of their collections. We argue they should also ensure the privacy of researcher and research subject data. We demonstrate the use of a privacy impact assessment (PIA) to evaluate potential privacy risks to researchers using the ICPSR’s Researcher Passport as a case study. We present our workflow and discuss potential privacy risks and mitigations for those risks. [A previous version of this article is available as an IDCC2020 Conference Paper]
Preface The Research Data Curation and Management Bibliography includes over 800 selected English-language articles and books that are useful in understanding the curation of digital research data in academic and other research institutions. The "digital curation" concept is still evolving. In "Digital Curation and Trusted Repositories: Steps toward Success," Christopher A. Lee and Helen R. Tibbo define digital curation as follows: Digital curation involves selection and appraisal by creators and archivists; evolving provision of intellectual access; redundant storage; data transformations; and, for some materials, a commitment to long-term preservation. Digital curation is stewardship that provides for the reproducibility and re-use of authentic digital data and other digital assets. Development of trustworthy and durable digital repositories; principles of sound metadata creation and capture; use of open standards for file formats and data encoding; and the promotion of information management literacy are all essential to the longevity of digital resources and the success of curation efforts.1 The Research Data Curation and Management Bibliography covers topics such as research data creation, acquisition, metadata, provenance, repositories, management, policies, support services, funding agency requirements, open access, peer review, publication, citation, sharing, reuse, and preservation. It is highly selective in its coverage. The bibliography does not cover conference proceedings, digital media works (such as MP3 files), editorials, e-mail messages, interviews, letters to the editor, presentation slides or transcripts, technical reports. unpublished e-prints, or weblog postings. Most sources have been published from January 2009 through December 2019; however, a limited number of earlier key sources are also included. The bibliography has links to included works. URLs may alter without warning (or automatic forwarding) or they may disappear altogether. Where possible, this bibliography uses Digital Object Identifier System (DOI) URLs. DOIs are not rechecked after initial validation. Publisher systems may have temporary DOI 3 resolution problems. Should a link be dead, try entering it in the Internet Archive Wayback Machine. Abstracts are included in this bibliography if a work is under a Creative Commons Attribution License (BY and national/international variations), a Creative Commons public domain dedication (CC0), or a Creative Commons Public Domain Mark and this is clearly indicated in the publisher’s current webpage for the article. Note that a publisher may have changed the licenses for all articles on a journal’s website but not have made corresponding license changes in journal’s PDF files. The license on the current webpage is deemed to be the correct one. Since publishers can change licenses in the future, the license indicated for a work in this bibliography may not be the one you find upon retrieval of the work. Unless otherwise noted, article abstracts in this bibliography are under a Creative Commons Attribution 4.0 International License, https://creativecommons.org/licenses/by/4.0/. Abstracts are reproduced as written in the source material. 1 Christopher A. Lee and Helen R. Tibbo, "Digital Curation and Trusted Repositories: Steps Toward Success," Journal of Digital Information 8, no. 2 (2007). https://journals.tdl.org/jodi/index.php/jodi/article/view/229
This chapter acquaints the reader with the general and often changing nature of research on data quality. It is emphasized that research data quality is closely related to business data; however, the goals of scholarly research have become different, especially as the environments shaping the two are different. From among data quality’s attributes, trust receives particular attention. Technical and scientific quality, the relationship of data quality to data reuse, and other quality factors are also examined, including big data quality, intrinsic and extrinsic data quality, and the semiotic representation of quality attributes, as well as their time-related dimensions and retrievability. Although data reuse was addressed in an earlier chapter, its relationship to data quality is touched on in this chapter as well. Sharing the previously mentioned origin with data quality and being closely associated with it, data governance is also portrayed.
Purpose
This study examined how the qualities of both data and documents of existing datasets can contribute to researchers' satisfaction of data reuse, and how it affects their data reuse intentions mediated by attitudinal and normative beliefs of data reuse.
Design/methodology/approach
A combined theoretical framework integrating IS (Information Systems) Success Model and the Theory of Planned Behavior (TPB) was utilized to develop the research model of researchers' data reuse, which was evaluated using structural equation modeling based on 820 survey responses from STEM disciplines in the US.
Findings
This study found that both data and document qualities significantly contribute to researchers' satisfaction of data reuse. Then, their satisfaction significantly increases perceived usefulness and subjective norm of data reuse, and it decreases perceived risk associated with data reuse. Finally, both perceived usefulness and subjective norm significantly increases their data reuse intentions.
Research limitations/implications
The combined theoretical framework integrating IS success model and TPB provides a new theoretical lens in understanding researchers' data reuse behaviors affected by the qualities of both data and documents.
Practical implications
The findings of this study provided several practical implications in promoting and facilitating researchers' data reuse behaviors by improving data and document qualities of existing datasets.
Originality/value
This is one of the initial studies focusing on the roles of data and document qualities in researchers' data reuse, and it provides a systematic view of how data and document qualities influence researchers' data reuse mediated by their satisfaction of data reuse and attitudinal and normative beliefs.
This selective bibliography presents over 800 English-language articles and books. It covers topics such as research data creation, metadata, provenance, repositories, management, policies, support services, funding agency requirements, open access, peer review, publication, citation, sharing, reuse, and preservation. It is also available as a paperback PDF file (https://www.digital-scholarship.org/rdcmb/rdcmb.pdf) and a website (https://www.digital-scholarship.org/rdcmb/rdcmb-web.htm), which includes a Google Translate link. Most sources were published from 2009 through 2019. It includes full abstracts for works under certain Creative Commons Licenses. This work is licensed under a Creative Commons Attribution 4.0 International License. (See also the Research Data Sharing and Reuse Bibliography and the Research Data Publication and Citation Bibliography.) Keywords: academic libraries, altmetrics, data citation, data curation, data journals, data preservation, data privacy, data publication, data repositories, data reuse, data sharing, data sharing policies, Digital Object Identifiers, peer review, ethical data sharing, geospatial data, funding agency requirements, open access, open access journals, open science, persistent identifiers, research data, research data management, research data metadata, research data publishing, research data metadata, research data services, research data training, research libraries, scholarly journals, scholarly metrics, and scholarly publishing.
Data reuse has recently become significant in academia and is providing new impetus for academic research. This prompts two questions: What precisely is the data reuse process? What is the connection between each participating element? To address these issues, 42 studies were reviewed to identify the stages and primary data reuse elements. A meta‐synthesis was used to locate and analyze the studies, and inductive coding was used to organize the analytical process. We identified three stages of data reuse—initiation, exploration and collection, and repurposing—and explored how they interact and form iterative characteristics. The results illuminated the data reuse at each stage, including issues of data trust, data sources, scaffolds, and barriers. The results indicated that multisource data and human scaffolds promote reuse behavior effectively. Further, two data and information search patterns were extracted: reticular centripetal patterns and decentralized centripetal patterns. Three paths with elements cooperating through flexible functions and motivated by different action items were identified: data centers, human scaffolds, and publications. This study supports improvements for data infrastructure construction, data reuse, and data reuse research by providing a new perspective on the effect of information behavior and clarifying the stages and contextual relationships between various elements.
This article investigates data reuse or the secondary analysis of qualitative data, specifically video records of practice in education, which are used to study the complex cognitive, social, and logistical issues involved in teaching and learning processes. It examines reuse through the lens of the invisibilities experienced by educational researchers who perform secondary analysis on video records of practice. Drawing on 22 in-depth interviews with educational researchers, we examine how they conceptualize secondary analysis of qualitative video data and cope with invisibilities in the data. For example, knowing the original research question was not sufficient: reusers needed to understand more about the intentionality of the data producer. They also sought more information on the reflexivity of the original researcher and how this influenced data production. Additionally, reusers discussed the creation of evidence from the video during secondary analysis as teaching and learning themselves entail invisible processes.
Investments in research that produce scientific and scholarly data can be leveraged by enabling the resulting research data products and services to be used by broader communities and for new purposes, extending reuse beyond the initial users and purposes for which the data were originally collected. Submitting research data to a data repository offers opportunities for the data to be used in the future, providing ways for new benefits to be realized from data reuse. Improvements to data repositories that facilitate new uses of data increase the potential for data reuse and for gains in the value of open data products and services that are associated with such reuse. Assessing and certifying the capabilities and services offered by data repositories provides opportunities for improving the repositories and for realizing the value to be attained from new uses of data. The evolution of data repository certification instruments is described and discussed in terms of the implications for the curation and continuing use of research data.
Background
Funding agencies and research journals are increasingly demanding that researchers share their data in public repositories. Despite these requirements, researchers still withhold data, refuse to share, and deposit data that lacks annotation. We conducted a meta-synthesis to examine the views, perspectives, and experiences of academic researchers on data sharing and reuse of research data.
Methods
We searched the published and unpublished literature for studies on data sharing by researchers in academic institutions. Two independent reviewers screened citations and abstracts, then full-text articles. Data abstraction was performed independently by two investigators. The abstracted data was read and reread in order to generate codes. Key concepts were identified and thematic analysis was used for data synthesis.
Results
We reviewed 2005 records and included 45 studies along with 3 companion reports. The studies were published between 2003 and 2018 and most were conducted in North America (60%) or Europe (17%). The four major themes that emerged were data integrity, responsible conduct of research, feasibility of sharing data, and value of sharing data. Researchers lack time, resources, and skills to effectively share their data in public repositories. Data quality is affected by this, along with subjective decisions around what is considered to be worth sharing. Deficits in infrastructure also impede the availability of research data. Incentives for sharing data are lacking.
Conclusion
Researchers lack skills to share data in a manner that is efficient and effective. Improved infrastructure support would allow them to make data available quickly and seamlessly. The lack of incentives for sharing research data with regards to academic appointment, promotion, recognition, and rewards need to be addressed.
Purpose
The purpose of this paper is to quantitatively examine factors of trust in data reuse from the reusers’ perspectives.
Design/methodology/approach
This study utilized a survey method to test the proposed hypotheses and to empirically evaluate the research model, which was developed to examine the relationship each factor of trust has with reusers’ actual trust during data reuse.
Findings
This study found that the data producer ( H1 ) and data quality ( H3 ) were significant, as predicted, while scholarly community ( H3 ) and data intermediary ( H4 ) were not significantly related to reusers’ trust in data.
Research limitations/implications
Further disciplinary specific examinations should be conducted to complement the study findings and fully generalize the study findings.
Practical implications
The study finding presents the need for engaging data producers in the process of data curation, preferably beginning in the early stages and encouraging them to work with curation professionals to ensure data management quality. The study finding also suggests the need for re-defining the boundaries of current curation work or collaborating with other professionals who can perform data quality assessment that is related to scientific and methodological rigor.
Originality/value
By analyzing theoretical concepts in empirical research and validating the factors of trust, this study fills this gap in the data reuse literature.
This bibliography presents over 750 English-language articles, books, and technical reports. It covers topics such as research data creation, acquisition, metadata, provenance, repositories, management, policies, support services, funding agency requirements, open access, peer review, publication, citation, sharing, reuse, and preservation. Most sources were published from 2009 through 2018. It is also available as a website with a Google Translate link (https://tinyurl.com/k4vvzz68). This work is licensed under a Creative Commons Attribution 4.0 International License. This bibliography has been superseded by the 2021 Research Data Curation and Management Bibliography (https://tinyurl.com/3rec6ejn), which covers over 800 works.
Digital information is fragile, yet access to digital information over time is a critical underpinning of core values and functions in our society, from open government to research and scholarship. Digital preservation research has focused on identifying technical, economic, and organizational sources of risk and has relied on an assumption that individuals will behave in rational and predictable ways in response to the same information. This article asserts that viewing digital preservation as a process that takes place in complex social contexts is just as important as thinking about digital preservation in terms of technological or economic issues. This is particularly important for understanding how individuals involved in digital preservation construct their understanding of risk because social factors influence how people construct their understanding of, and behave in response to, risk information. The author proposes an eight‐factor model for the social construction of risk, which includes: communication, complexity, expertise, organizations, political culture, trust, uncertainty, and vulnerability. The article demonstrates how these factors influence individuals as they construct their understanding of risk in the context of digital preservation and how this in turn affects digital preservation decisions.
This column examines the issue of trust in digital repositories, especially ones with a digital preservation component. The concept of trust is important for repositories that have a mission to provide designated communities with long-term access to data that is deposited in there repository. Many repository administrators and other digital preservationists have looked at trusted digital repository certifications such as the CoreTrustSeal as one way to help build trust but it is not clear how much members of the designated community are influenced by certifications. However, even if the designated community is not directly influenced by certifications, repositories who meet the requirements and go through the process of being certified with the CoreTrustSeal or other certifications may have a better foundation to grow trust upon.
Digital preservation is a complex field that is rapidly maturing and increasingly focusing on content as well as the human element of digital preservation. This conceptual article examines a number of digital preservation models meeting a variety of needs created by different communities. Given the guidance these models have afforded digital preservation, considering the present, and looking to the future, this article proposes a tri-partite model for thinking about digital preservation in an era of robust community involvement: the Digital Preservation Triad. The Triad focuses on 1) Management, including elements relating to documentation and human resources; 2) Technology; and 3) Content.
This study explores the factors that influence the data reuse behaviors of scientists and identifies the generalized patterns that occur in data reuse across various disciplines. This research employed an integrated theoretical framework combining institutional theory and the theory of planned behavior. The combined theoretical framework can apply the institutional theory at the individual level and extend the theory of planned behavior by including relevant contexts. This study utilized a survey method to test the proposed research model and hypotheses. Study participants were recruited from the Community of Science's (CoS) Scholar Database, and a total of 1,528 scientists responded to the survey. A multilevel analysis method was used to analyze the 1,237 qualified responses. This research showed that scientists' data reuse intentions are influenced by both disciplinary level factors (availability of data repositories) and individual level factors (perceived usefulness, perceived concern, and the availability of internal resources). This study has practical implications for promoting data reuse practices. Three main areas that need to be improved are identified: Educating scientists, providing internal supports, and providing external resources and supports such as data repositories.
The increasing concern for the availability of scientific data has resulted in a number of initiatives promoting the archival and curation of datasets as a legitimate research outcome. Among them, dataset repositories fill the gap of providing long-term preservation of diverse kinds of data along with its meta-descriptions, and support citation. Unsurprisingly, the concern for quality arises as in the publication of papers. However, repositories support a larger variety of use cases, and many of them implement minimal control on the data uploaded by users. An approach to tackle with quality control in repositories is that of letting communities of users to filter the relevant resources for them, at the same time providing some form of trust to users of the data. However, there is a lack of knowledge of the extent to which this social approach that relies on communities self-organizing actually contributes to the effective organization inside repositories. This paper reports the results of a study on the Zenodo repository, describing its main contents and how communities have emerged naturally around the deposited contents.
Providing proof of the trustworthiness of the digital contents, supported by digital objects, goes through the reconstruction of information which could address replication of preserving repositories, heterogeneity in the maintenance approaches, and differences of the technological applications. In this research will be investigated how to use Semantic Web technology for providing technological evidence, about custody chain, ensuring that the digital content is what it was purported to be at its creation time.
There is almost universal agreement that scientific data should be shared for use beyond the purposes for which they were initially collected. Access to data enables system-level science, expands the instruments and products of research to new communities, and advances solutions to complex human problems. While demands for data are not new, the vision of open access to data is increasingly ambitious. The aim is to make data accessible and usable to anyone, anytime, anywhere, and for any purpose. Until recently, scholarly investigations related to data sharing and reuse were sparse. They have become more common as technology and instrumentation have advanced, policies that mandate sharing have been implemented, and research has become more interdisciplinary. Each of these factors has contributed to what is commonly referred to as the "data deluge". Most discussions about increases in the scale of sharing and reuse have focused on growing amounts of data. There are other issues related to open access to data that also concern scale which have not been as widely discussed: broader participation in data sharing and reuse, increases in the number and types of intermediaries, and more digital data products. The purpose of this paper is to develop a research agenda for scientific data sharing and reuse that considers these three areas.
Information in the form of digital objects faces numerous threats to its integrity, authenticity and security. In the worst cases this can result in total lossaccessibility and usability. Physical aging of storage media, separation of information from its original data carriers, and rapid changes in the technical infrastructure required to interpret digital objects represent key challenges for long-term preservation.
Arguably, the most critical time frame for organizational participants to develop trust is at the beginning of their relationship. Using primarily a cognitive approach, we address factors and processes that enable two organizational parties to form relatively high trust initially. We propose a model of specific relationships among several trust-related constructs and two cognitive processes. The model helps explain the paradoxical finding of high initial trust levels in new organizational relationships.
ISO 16363:2012, Space Data and Information Transfer Systems - Audit and Certification of Trustworthy Digital Repositories (ISO TRAC), outlines actions a repository can take to be considered trustworthy, but research examining whether the repository’s designated community of users associates such actions with trustworthiness has been limited. Drawing from this ISO document and the management and information systems literatures, this paper discusses findings from interviews with 66 archaeologists and quantitative social scientists. We found similarities and differences across the disciplines and among the social scientists. Both disciplinary communities associated trust with a repository’s transparency. However, archaeologists mentioned guarantees of preservation and sustainability more frequently than the social scientists, who talked about institutional reputation. Repository processes were also linked to trust, with archaeologists more frequently citing metadata issues and social scientists discussing data selection and cleaning processes. Among the social scientists, novices mentioned the influence of colleagues on their trust in repositories almost twice as much as the experts. We discuss the implications our findings have for identifying trustworthy repositories and how they extend the models presented in the management and information systems literatures.
ABSTRACT: Trust is a key enabler of cooperative human actions. Three main deficiencies about our current knowledge of trust are addressed by this paper. First, due to widely divergent conceptual definitions of trust, the literature on trust is in a state of construct confusion. Second, too little is understood about how trust forms and on what trust is based. Third, little has been discussed about the role of emotion in trust formation. To address the first deficiency, this paper develops a typology of trust. The rest of the paper addresses the second and third deficiencies by proposing a model of how trust is initially formed, including the role of emotion. Dispositional, interpersonal, and impersonal (system) trust are integrated in the model. The paper also clarifies the cognitive and emotional bases on which interpersonal trust is formed in early relationships. The implications of the model are drawn for future research.
This paper examines the role of trust in organizational response to crisis. Based on prior research and interviews with 33 top managers during a period of industry crisis, trust is conceptualized in terms of four dimensions: competence, openness, concern, and reliability. Trust at the group, organizational, and interorganizational levels is hypothesized to be positively related to decentralization of decision making, undistorted communication, and collaboration within and between organizations during crisis. Trust is also hypothesized to be positively related to organizational performance.
Reform efforts increasingly promote collaboration – admonishing principals to include both teachers and parents in democratic decision processes and encouraging teachers to work toward greater collaboration with their colleagues. The hypotheses that the level of collaboration was related to the level of trust was supported in bivariate correlational analyses. There was a significant link between collaboration with the principal and trust in the principal, collaboration with colleagues and trust in colleagues, and collaboration with parents and trust in parents. Canonical correlation reinforced the importance of trust in predicting the overall level of collaboration within a school. Among the set of trust variables, trust in clients was most influential in predicting the set of collaboration variables. Collaboration with parents was the most potent of the collaboration variables in this analysis. These finding argue for the importance of trust in nurturing collaborative relationships.
Prior research on organizational trust has not rigorously examined the context specificity of trust nor distinguished between the potentially varying dimensions along which different stakeholders base their trust. As a result, dominant conceptualizations of organizational trust are overly generalized. Building on existing research on organizational trust and stakeholder theory, we introduce a more nuanced perspective on the nature of organizational trust. We develop a framework that distinguishes between organizational stakeholders along two dimensions: depth of the relationship (deep or shallow) and locus (internal or external). The framework identifies which of six dimensions of trustworthiness (benevolence, integrity, managerial competence, technical competence, transparency, and identification) will be relevant to which stakeholder type. We test the predictions of our framework using original survey data from 1,298 respondents across four stakeholder groups from four different organizations. The results reveal that the relevant dimensions of trustworthiness vary systematically across different stakeholder types and provide strong support for the validity of the depth and locus dimensions.
Our task is to adopt a multidisciplinary view
of trust within and between firms, in an effort to
synthesize and give insight into a fundamental
construct of organizational science. We seek to
identify the shared understandings of trust
across disciplines, while recognizing that the
divergent meanings scholars bring to the study
of trust also can add value.
The article examines the issues surrounding the audit and certification of digital repositories in light of the work that the RLG/NARA Task Force did to draw up guidelines and the need for these guidelines to be validated.
The authors integrate theory developed in several disciplines to determine five cognitive processes through which industrial buyers can develop trust of a supplier firm and its salesperson. These processes provide a theoretical framework used to identify antecedents of trust. The authors also examine the impact of supplier firm and salesperson trust on a buying firm's current supplier choice and future purchase intentions. The theoretical model is tested on data collected from more than 200 purchasing managers. The authors find that several variables influence the development of supplier firm and salesperson trust. Trust of the supplier firm and trust of the salesperson (operating indirectly through supplier firm trust) influence a buyer's anticipated future interaction with the supplier. However, after controlling for previous experience and supplier performance, neither trust of the selling firm nor its salesperson influence the current supplier selection decision.
This article examines what is implied by the term “trusted” in the phrase “trusted digital repositories.” Digital repositories should be able to preserve electronic materials for periods at least comparable to existing preservation methods. Our collective lack of experience with preserving digital objects and consensus about the reliability of our technological infrastructure raises questions about how we should proceed with digital-based preservation practices, an emerging role for academic libraries and archival institutions. This article reviews issues relating to building a trusted digital repository, highlighting some of the issues raised and possible solutions proposed by the authors in their work of implementing and acculturating a digital repository at Rutgers University Libraries.
In this article we contend that trust can be conceptualized as four distinct and ordered forms - shallow dependence, shallow interdependence, deep dependence, and deep interdependence - determined by the nature of the interdependence between trusting parties. We argue that both the risks that trusting parties assume and the mechanisms for mitigating those risks emerge as a function of the form of interdependence in the relationship. By reviewing research in which trust is a central component, we illustrate the elements of this model and examine its implications.
Purpose
Digital repositories offer a great benefit to people in a variety of settings, especially since an ever‐increasing amount of information is being gathered, transmitted, and preserved through various technologies. The purpose of this paper is to underscore trust as a critical element in the infrastructure of digital repositories and to look more closely at trusted digital repositories from the perspective of the user communities for which they are designed.
Design/methodology/approach
The paper looks to the literature in reviewing the concept of trust and its role in an online environment. Attention is then paid to trusted digital repositories, with close examination of the user communities’ perceptions of trust and the impact of these perceptions. Special attention is given to users within the academic community.
Findings
While digital repositories may be trustworthy because of adherence to technological standards, accepted practices, and mechanisms for authenticating the authorship and accuracy of their content, it is ultimately their respective stakeholders – both those who deposit and use content – whose perceptions play a central role in ensuring a digital repository's trustworthiness.
Research limitations/implications
A future empirical study would be beneficial in order to measure perceptions of trust as contributing factors to the trustworthiness of digital repositories.
Practical implications
This paper provides a useful resource for persons wishing to review the topic of trusted digital repositories or increase their awareness in this area.
Originality/value
This paper offers a focused look at various levels of trust as they relate to the dissemination of scholarly communication in the academic world, particularly through institutional repositories.
Scholars in various disciplines have considered the causes, nature, and effects of trust. Prior approaches to studying trust are considered, including characteristics of the trustor, the trustee, and the role of risk. A definition of trust and a model of its antecedents and outcomes are presented, which integrate research from multiple disciplines and differentiate trust from similar constructs. Several research propositions based on the model are presented.
It is expected that authors will provide citations for all papers referenced in their writings. The necessity of providing citations for data is not so widely recognized. Proponents of the data-sharing movement have advocated the citation of datasets in order to recognize contributions and enhance access. This study examines a sample of papers from the Inter-University Consortium for Political and Social Research (ICPSR) Bibliography of Data-Related Literature that are based on secondary analysis of datasets available in the ICPSR data archive to determine the data citation practices of authors. The results indicate that many authors fail to cite the data used in secondary analysis studies. Possible reasons for the dismal state of data citation practices are considered, including the recent introduction of data into the scholarly record and its marginalization as an information format. Updating citation practices to include datasets will support data sharing and foster responsible scholarship.
A considerable amount of research has examined trust since our 1995 publication. We revisit some of the critical issues that we addressed and provide clarifications and extensions of the topics of levels of analysis, time, control systems, reciprocity, and measurement. We also recognize recent research in new areas of trust, such as affect, emotion, violation and repair, distrust, international and cross-cultural issues, and context-specific models, and we identify promising avenues for future research.
The purpose of this article is to analyse how the concept of trust is approached and defined in various disciplines, in order to reach a generally acceptable definition that could be used in business research. An interdisciplinary approach is chosen because the concept seems to be used somewhat differently, depending on the context and the disciplinary eyeglass of the author in question. Also, much of the business research on trust has its roots in social psychology, economics or philosophy. It is hoped that an analysis of the various levels and dimensions of trust as well as an enumeration and differentiation of the related constructs will advance the study of this significant but complex phenomenon, and that a more accurate usage and a better understanding of the various dimensions and levels of the concept can be accomplished. Empirical documentation of the factors generating trust lies outside the scope of this article. Nor is a universal definition of trust constructed, since such a thing is deemed impossible, but a working definition for business contexts∗ is proposed.
The authors integrate theory developed in several disciplines to determine five cognitive processes through which industrial buyers can develop trust of a supplier firm and its salesperson. These processes provide a theoretical framework used to identify antecedents of trust. The authors also examine the impact of supplier firm and salesperson trust on a buying firm's current supplier choice and future purchase intentions. The theoretical model is tested on data collected from more than 200 purchasing managers. The authors find that several variables influence the development of supplier firm and salesperson trust. Trust of the supplier firm and trust of the salesperson (operating indirectly through supplier firm trust) influence a buyer's anticipated future interaction with the supplier. However, after controlling for previous experience and supplier performance, neither trust of the selling firm nor its salesperson influence the current supplier selection decision.
This paper describes the general approach nestor - the German "Network of Expertise in Long-Term Storage of Digital Resources" has taken in order to design a catalogue of criteria for trusted digital repositories used for long-term preservation issues. Further developments are intended to led to the implementation of evaluation schemas and a formal certification process for trusted digital repositories.
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