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Open Data for Science, Policy, and the Public Good: Open Data
Abstract
Supporters of open data believe that free and complete access to research data is beneficial for science, public policy, and society. In environmental science and policy, open data systems can enable relevant research and inform evidence-based governmental decisions. This article examines the unlikely case of Brazil's National Institute for Space Research's transition toward an open data model. Considering Brazil's young democracy, incipient practice of government transparency and accountability, and lacking a tradition of science-policy dialogue, this case is a striking example of how open data can support public debate by making information about forest cover widely available. The case shows the benefits and challenges of developing such open data systems, and highlights the various forms of accessibility involved in making data available to the public.
... Data sharing practices and accompanying infrastructures on which they depend (Sá & Grieco, 2016) have been long-established in certain fields, such as economics, but are relatively nascent in others. Data itself is increasingly recognized as research output, and like other research outputs, there have been many efforts to develop ways of capturing their contributions to the advancement of knowledge. ...
... Data sharing may be better facilitated by the robust alignment of data sharing rationales, reward and incentive structures, policy, and technical components that support their operationalization (Borgman, 2016;Sá & Grieco, 2016). Data sharing can be incentivized through funding or journal policies that require data sharing (Borgman, 2012;Zuiderwijk et al., 2020), and advocacy and social influence (Zuiderwijk et al., 2020). ...
... Yoon & Kim, 2020), as was a sense that data being collected might in some way be of use or interest to others (Wallis et al., 2013). Technological advancements can support open science by reducing barriers to storing and sharing data (Haak et al., 2020;Molloy, 2011;Sá & Grieco, 2016). Peer-reviewed "data papers" can also contribute to both the sharing and reward aspects by reframing data production and citation within the traditional scholarly communication process (Huang & Jeng, 2022;Molloy, 2011;Sá & Grieco, 2016). ...
Open data is receiving increased attention and support in academic environments, with one justification being that shared data may be re-used in further research. But what evidence exists for such re-use, and what is the relationship between the producers of shared datasets and researchers who use them? Using a sample of data citations from OpenAlex, this study investigates the relationship between creators and citers of datasets at the individual, institutional, and national levels. We find that the vast majority of datasets have no recorded citations, and that most cited datasets only have a single citation. Rates of self-citation by individuals and institutions tend towards the low end of previous findings and vary widely across disciplines. At the country level, the United States is by far the most prominent exporter of re-used datasets, while importation is more evenly distributed. Understanding where and how the sharing of data between researchers, institutions, and countries takes place is essential to developing open research practices.
... Group business disseminates information to improve their research activities. [Gura, 2013], Open Access and Open Data [Bernius, 2010;Sa, Grieco, 2016;Piedra, Suárez, 2018;Arza et al., 2017;Cardoso et al., 2009]. The election of the tool depends on the business goals, resources and the time of innovation. ...
... It is worth mentioning that the validation of collaborative practices also involves a depth study of IP and IP policies in open innovation strategies [Hagedoorn, Zobel, 2015;Lichtenthaler, 2010;Bianchi et al., 2015;Bravo-Ibarra et al., 2014]. The development of these policies turns governments also in important actors of the OS and OI process [Sa, Grieco, 2016;Yoon, 2017;Freitas, Dacorso, 2014]. How OS and OI are addressed in a particular territory has a strong cultural dependence. ...
... This paper proposes the following Framework (Figure 2), so that innovation can be achieved by the connection between OS and OI. Open science is connected to policy makers because scientific knowledge contributes to the development of economic policy [Sa, Grieco, 2016;Arza et al., 2017;Freitas, Dacorso, 2014]. Open innovation encourages the relationship between business, research institutes and the government, and it creates an organizational structure to connect business, university and policy makers. ...
Open innovation allows partnerships between business through knowledge sharing. The mission of open science is to encourage information sharing about academic research. The purpose of this paper is to demonstrate the relevance of open science to open innovation and vice versa, especially in the context of emerging economies. Furthermore, it aims to show the results of the intersection between university and innovation companies. The methodology was based on a systematic literature review to understand how researchers have been studying the subject. It also focuses on the relevance of open innovation and open science to business management and information science fields. Therefore, the connection between open science and open innovation is fundamental to encourage partnership between business and university. This kind of partnership contributes to the economy of developing countries, so business can become more competitive.
... Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement [1][2][3][4] a particular standpoint to fulfil certain aims or express certain views on the nature of the topic and how it is to be investigated, and the effective evaluation of these documents in relation to the research being proposed" [27]. One of the systematic literature review approach's main advantages lies in its rigor and the applied processes' overall transparency [28]. ...
... Offer individuals the opportunity to better understand the social and physical world in which we all live [50] Provide decision-makers with the necessary facts to address complex, often trans-national problems [50] Encourage validation and verification of research results [2,56] and enable falsification [11] Help to identify errors and discourage research fraud [8,9] Permitting in-depth public scrutiny by making it easier to analyze, process and combine data [19] Encourage multiple perspectives [8,42] and allow other researchers to explore new interpretations of data [17,56], ask new questions [57] and test different hypotheses [42] Allow valuable resources to contribute far beyond their original analysis [9] Facilitating other researchers' ability to pursue new lines of research [57] Facilitating comparisons between methods and sites [57] Data reuse can lead to more findings from the same dataset and increase the knowledge in the field [17] Personal drivers / intrinsic motivations: better science, move the field forward more quickly and easily [48] Sense of responsibility about acceleration of scientific research [55] Usability [48] Possibility to better advance the area of research [52] Size of the research community and the extent to which data is viewed as a tremendous asset [52] Encourage economic development, spur innovation [2] Identify synergies [11] Accelerated scientific progress [11,17,57] and contributing to the advancement of research [18,42] Gaining new insight for data-driven research [19] Enable citizen science and encourage public activism [1] Improved discoverability [9,17] Extending research from prior results [56] A focus on best work through data availability [9] Generation of new datasets, information, and knowledge when data from various sources are combined [19] Educating researchers about the consumer side of open data practices [17] The ability to review works derived from the dataset [56] Lack of concerns about ethics and commercial potential of data [48] Facilitating conditions ICT facilitation (internet hosts per person, percentage of computers per household, continued rate of growth of chip, storage, and network technology capacity) [50] Financial arrangements (and budgets) [50] and financial resources [11,41] Infrastructure [17,57], appropriately designed technological infrastructure [50] Financial barriers: loss of potential licensing revenue that would accrue to inventors of patentable discoveries [1] Appropriate information systems [47] Technical challenges [17,50] Richer investment of funding, labors, scale, and infrastructure [57] Lack of appropriate infrastructure [57] Availability of (large) data repositories [13,17,41,42,47] and archives [13] Lack of a data repository [42] The ability to grow storage and access capabilities and still operate reliably and efficiently [2] Lack of facilitating platforms [48] (Continued ) ...
... Offer individuals the opportunity to better understand the social and physical world in which we all live [50] Provide decision-makers with the necessary facts to address complex, often trans-national problems [50] Encourage validation and verification of research results [2,56] and enable falsification [11] Help to identify errors and discourage research fraud [8,9] Permitting in-depth public scrutiny by making it easier to analyze, process and combine data [19] Encourage multiple perspectives [8,42] and allow other researchers to explore new interpretations of data [17,56], ask new questions [57] and test different hypotheses [42] Allow valuable resources to contribute far beyond their original analysis [9] Facilitating other researchers' ability to pursue new lines of research [57] Facilitating comparisons between methods and sites [57] Data reuse can lead to more findings from the same dataset and increase the knowledge in the field [17] Personal drivers / intrinsic motivations: better science, move the field forward more quickly and easily [48] Sense of responsibility about acceleration of scientific research [55] Usability [48] Possibility to better advance the area of research [52] Size of the research community and the extent to which data is viewed as a tremendous asset [52] Encourage economic development, spur innovation [2] Identify synergies [11] Accelerated scientific progress [11,17,57] and contributing to the advancement of research [18,42] Gaining new insight for data-driven research [19] Enable citizen science and encourage public activism [1] Improved discoverability [9,17] Extending research from prior results [56] A focus on best work through data availability [9] Generation of new datasets, information, and knowledge when data from various sources are combined [19] Educating researchers about the consumer side of open data practices [17] The ability to review works derived from the dataset [56] Lack of concerns about ethics and commercial potential of data [48] Facilitating conditions ICT facilitation (internet hosts per person, percentage of computers per household, continued rate of growth of chip, storage, and network technology capacity) [50] Financial arrangements (and budgets) [50] and financial resources [11,41] Infrastructure [17,57], appropriately designed technological infrastructure [50] Financial barriers: loss of potential licensing revenue that would accrue to inventors of patentable discoveries [1] Appropriate information systems [47] Technical challenges [17,50] Richer investment of funding, labors, scale, and infrastructure [57] Lack of appropriate infrastructure [57] Availability of (large) data repositories [13,17,41,42,47] and archives [13] Lack of a data repository [42] The ability to grow storage and access capabilities and still operate reliably and efficiently [2] Lack of facilitating platforms [48] (Continued ) ...
Both sharing and using open research data have the revolutionary potentials for forwarding scientific advancement. Although previous research gives insight into researchers' drivers and inhibitors for sharing and using open research data, both these drivers and inhibitors have not yet been integrated via a thematic analysis and a theoretical argument is lacking. This study's purpose is to systematically review the literature on individual researchers' drivers and inhibitors for sharing and using open research data. This study systematically analyzed 32 open data studies (published between 2004 and 2019 inclusively) and elicited drivers plus inhibitors for both open research data sharing and use in eleven categories total that are: 'the researcher's background', 'requirements and formal obligations', 'personal drivers and intrinsic motivations', 'facilitating conditions', 'trust', 'expected performance', 'social influence and affiliation', 'effort', 'the researcher's experience and skills', 'legislation and regulation', and 'data characteristics.' This study extensively discusses these categories, along with argues how such categories and factors are connected using a thematic analysis. Also, this study discusses several opportunities for altogether applying, extending, using, and testing theories in open research data studies. With such discussions, an overview of identified categories and factors can be further applied to examine both researchers' drivers and inhibitors in different research disciplines, such as those with low rates of data sharing and use versus disciplines with high rates of data sharing plus use. What's more, this study serves as a first vital step towards developing effective incentives for both open data sharing and use behavior.
... Furthermore, by publishing their findings with maximum transparency, OD can elicit great attention to global scientific collaboration, bring new opportunities to research, and eventually increase the efficiency of the global innovation system (Gold, 2021). In addition, OD not only contributes to scientific development, but also is beneficial for the public, and the whole of society because research data have become a common resource from which business, government and the whole of society can extract value, such as open data systems which can enable relevant research and inform evidence-based governmental decisions (Sá & Grieco, 2016). ...
... First, we found that the OD policy has significantly increased the citation performance of the articles in the first four years after publication, and a series of robustness checks confirmed the findings. This research suggested that the OD policy could significantly and positively affect the academic impact of articles in the short term, which is consistent with prior studies on this topic (Inkpen et al., 2021;Molloy, 2011;Piwowar & Vision, 2013;Sá & Grieco, 2016). Journals should consider enforcing the data-sharing policy to accelerate scientific communication and to improve the development of science, especially for the case of China which is troubled by academic fraud. ...
Unlabelled:
Data sharing is an important part of open science (OS), and more and more institutions and journals have been enforcing open data (OD) policies. OD is advocated to help increase academic influences and promote scientific discovery and development, but such a proposition has not been elaborated on well. This study explores the nuanced effects of the OD policies on the citation pattern of articles by using the case of Chinese economics journals. China Industrial Economics (CIE) is the first and only Chinese social science journal so far to adopt a compulsory OD policy, requiring all published articles to share original data and processing codes. We use the article-level data and difference-in-differences (DID) approach to compare the citation performance of articles published in CIE and 36 comparable journals. Firstly, we find that the OD policy quickly increased the number of citations, and each article on average received 0.25, 1.19, 0.86, and 0.44 more citations in the first four years after publication respectively. Furthermore, we also found that the citation benefit of the OD policy rapidly decreased over time, and even became negative in the fifth year after publication. In conclusion, this changing citation pattern suggests that an OD policy can be double edged sword, which can quickly increase citation performance but simultaneously accelerate the aging of articles.
Supplementary information:
The online version contains supplementary material available at 10.1007/s11192-023-04684-8.
... The information challenges and scientific opportunities presented by expanding availability of scientific data at both large and small scale are numerous (Borgman, 2015;Hey, Tansley, and Tolle, 2009). Sharing and using datasets across domains, while often essential to research involving the convergence of scientific disciplines, can be especially challenging (Parsons et al., 2011;Sá & Grieco, 2016). This research studies the role of data in the "converging" environmental health community by studying these researchers' use of data stored in disciplinary-based repositories outside their own discipline. ...
... The multitude of data challenges researchers face include managing, sharing, discovering, and reusing data, and these challenges can be particularly notable when it comes to sharing or reusing data beyond one's own discipline (Borgman, 2015;Tenopir et al., 2011;Tenopir et al., 2015;Pasquetto, Randles, & Borgman, 2017;Sá & Grieco, 2016). Making data available supports the foundation of science-the reproducibility of scientific results. ...
Open science data benefit society by facilitating convergence across domains that are examining the same scientific problem. While cross-disciplinary data sharing and reuse is essential to the research done by convergent communities, so far little is known about the role data play in how these communities interact. An understanding of the role of data in these collaborations can help us identify and meet the needs of emerging research communities which may predict the next challenges faced by science. This paper represents an exploratory study of one emerging community, the environmental health community, examining how environmental health research groups form, collaborate, and share data. Five key insights about the role of data in emerging research communities are identified and suggestions are made for further research.
... The Flowminder-WorldPop partnership follows an open model when it comes to data sourcing and the sharing of insights; all the output data are to the largest possible extent openly available for download, but the collaboration itself is limited to a bilateral agreement between the University of Southampton and the Flowminder Foundation. We base our distinction between open and closed data partnerships on the more general discussion of open/closed data (Janssen, Charalabidis, & Zuiderwijk, 2012;Open Data Institute, 2013;Sa & Grieco, 2016). According to Dietrich and colleagues (2018), open data can be described as "data that can be freely used, re-used and redistributed by anyone-subject only, at most, to the requirement to attribute and share-alike." ...
... The openness of data partnerships can impact in how far relevant initiatives are transparent about how they source, analyze, and distribute development data. While the open data literature usually assumes that open data imply higher levels of transparency (Janssen et al., 2012;Sa & Grieco, 2016), we caution that this does not need to be the case in the context of data partnerships. Although the push toward open data within government has resonated with calls for more transparency and accountability, one can have open data initiatives without much transparency (Lourenço, 2015). ...
This article examines the legitimacy attached to different types of multi-stakeholder data partnerships occurring in the context of sustainable development. We develop a framework to assess the democratic legitimacy of two types of data partnerships: open data partnerships (where data and insights are mainly freely available) and closed data partnerships (where data and insights are mainly shared within a network of organizations). Our framework specifies criteria for assessing the legitimacy of relevant partnerships with regard to their input legitimacy as well as their output legitimacy. We demonstrate which particular characteristics of open and closed partnerships can be expected to influence an analysis of their input and output legitimacy.
... Open research data is a critical theme of science and an essential policy for governments to push the development of open science (Novotny, 2019). Unlike general open data (e.g., government or commercial data), open research data focuses on the data used in a research study (Cowan et al., 2014;Sa & Grieco, 2016). Data sharing, an essential precondition for activities in open research data (Tenopir et al., 2015), should consists of deposition, preservation, and annotation of datasets, enabling other scientists to create new science based on the same datasets (Imker et al., 2021;Tenopir et al., 2011). ...
This paper explores the effect of publishing a data paper in the Open Access journal Data in Brief ( DIB ) on the citation counts of the related research paper. Using regression analysis, citation content analysis and a survey method, we investigate whether research papers with a related data paper have higher citation counts and the potential reasons. After controlling variables that correlate with the citation counts, research papers with a related data paper were found to have higher citation counts than those published in the same issue of the same journal. Next, we explored the causal relationship between the two variables by surveying the corresponding authors of 618 papers who shared datasets in DIB from 2014 to 2021. The results show that the authors acknowledge the benefits of sharing data in DIB , including citation increase and career reputation enhancement. We further explored how the data papers in DIB increase the citations of the related research papers by using citation content analysis. We found that scientists co‐cite the data papers and their related research papers for the purpose of reusing the underlying data or portraying a better understanding of the underlying data and related research articles.
... In Brazil, open science has been promoted through data portals in recent years. Such is the case for INPE, which has been carrying out space studies since 1971 and is considered one of the first to offer information on its space observations with open science practice initiatives[62]. The INPE catalog contains historical data since 1973, which allows monitoring of environmental, urban and water changes. ...
Atmospheric data are collected by researchers every day. Campaigns such as GOAmazon 2014/2015 and the Amazon Tall Tower Observatory collect essential data on aerosols, gases, cloud properties, and meteorological parameters in the Brazilian Amazon basin. These data products provide insights and essential information for analyzing and predicting natural processes. However, in Brazil, it is estimated that more than 80% of the scientific data collected are not published due to the lack of web portals that collect and store these data. This makes it difficult, or even impossible, to access and integrate the data, which can result in the loss of significant amounts of information and significantly affect the understanding of the overall data. To address this problem, we propose a data portal architecture and open data deployment that enable Big Data processing, human interaction, and download-oriented approaches with tools that help users catalog, publish and visualize atmospheric data. Thus, we describe the architecture developed, based on the experience of the Atmospheric Radiation Measurement Data Center, which incorporates the principles of FAIR, the infrastructure and content management system for managing scientific data. The portal partial results were tested with environmental data from contaminated areas at the University of São Paulo. Overall, this data portal creates more shared knowledge about atmospheric processes by providing users with access to open environmental data.
... Luckily, the open data policies changed the guidelines for the * Corresponding author. distribution and availability of satellite images, which resulted in an abundance of free of charge Earth observation data (Showstack, 2014, Sá and Grieco, 2016. The open access to satellite data benefits the development of remote sensing methods that exploit temporal information, like time series analysis and classification (Kuenzer et al., 2015). ...
Remote sensing has been an essential tool in combating deforestation. However, the ever-rising deforestation rates require new remote sensing techniques. This paper presents a study to determine the effects on the accuracy of the data analysis of varying the number of satellite observations, using a Random Forest classification algorithm. We carried out experiments on the Landsat-8 data cube with 22 images and developed an automatic sampling system based on PRODES to generate the labeled time series. We split the time series dataset to build data subsets with different number of observations. The results showed that a fewer number of observations negatively effects the accuracy of the RF algorithm when analyzing deforested areas, but not forest areas. The RF classifiers were compared using a random test data set, where all classifiers presented an Overall Accuracy (OA), Balanced Accuracy (BA), and f1-score (F1) above 97%. In the first evaluation, the variation in the number of observations appears to cause little influence on the classification accuracy. The analysis used the reference map to contrast the RF classifier’s results. The results showed that the best results in OA occurred with fewer observations. The best performance of 96% happened with four observations. We evaluated the performance of the classes, deforestation, and forest individually. The results showed that a fewer number of observations had negative effects on the accuracy of the RF algorithm when analyzing deforested areas, but not forest areas. Finally, we evaluated the visual quality of the land cover maps produced.
... An oft-claimed benefit of Open Research (OR) is that it affords access to scientific outputs to those outside academia, and in doing so, allows for greater use of science within evidence-based policy-making (Sá and Grieco 2016;Davis and Walters 2011;ElSabry 2017). 1 Yet to date, little attention has been paid to substantiating the extent to which this access changes policy-making processes. Responding to this evidence gap, this paper investigates the extent to which OR plays a role in the integration of scientific evidence into policy, via qualitative work with researchers working at the sciencepolicy interface. ...
Proponents of Open Research often assert that it can support evidence-based policy-making by making scientific outputs more readily available to policy-makers and other policy actors, yet there is little empirical work to support or deny this claim. This paper fills this void by reporting the results of a qualitative study with researchers who regularly work at the science-policy interface. We found that there is little evidence that Open Research products, namely Open Access and open data, which aim at increasing access and transparency, are useful in integrating science into policy-making. Instead, we found that the cognitive accessibility of research outputs is more important than their physical accessibility, and that inclusive and collaborative Open Research processes, like upstream engagement, co-creation and Citizen Science, are most effective at doing so.
... Open data, as Molloy (2011) Although open science knowledge has brought numerous advantages, the transfer of knowledge and data is not without problems. Our literature review shows that reported problems of transfer of open science knowledge include issues with absorptive capacity of users (Gans et al., 2017), and operations in data management such as open portal management, meeting user demands or managing continued, dedicated, and budgetary planning and supports (Arzberger et al., 2004;Sá & Grieco, 2016). Bonn and Pinxten (2020) argue that scientists continue to withhold data, even in fields that are upheld as exemplars of openness, and this is because of a trade-off between advancing science and advancing careers: although researchers generally express their willingness to contribute to open science knowledge and data portals, they find hard to dedicate more time to improve the data. ...
Open science knowledge has significant value, yet this value can only be realised if the knowledge is accessible, findable and retrievable. Although it is well-documented that detailed metadata are important, the more critical point is what factors are more important and worth of more investments and managerial efforts. We collect data from a major Australian science repository and show that: compared to traditional factors, including metadata richness, contributor network and reputation, age, and fields of research, the topicality of datasets’ keywords has a more significant power deciding whether the datasets become top-downloaded datasets. Among traditional factors, metadata completeness has the strongest positive effect. We thus provide theoretical and practical insights about how to increase retrievals, unlocking greater value for users.
... This brings the open data concept, which can be defined as providing everyone access, use, and redistribute data free of charge without any restrictions [2][3][4]. As a result of observing many advantages: transparency, participation, self-empowerment, accountability, collaboration, trust, legitimacy, improvement of civil rights, corruption prevention [4][5][6][7][8] [9] as well as improving operational capacity, reducing the red tape on bureaucracy, and providing innovative practices [4,6,[10][11][12][13][14], open data initiatives have been increased in the organizations. While the recent history of open data is inspired and affected by the open-source movement, open innovation, and open access, the Open Government Directive declared by Barak Obama Administration on the United States of America in 2009 made governments and business became highly interested CMMI , developed by Carnegie Mellon University, is a model aiming to improve the ability of organizations to manage the supply, development, and maintenance processes of their products and services by guiding their processes [30]. ...
Governments and organizations want to reap observed open data benefits like trust, participation, collaboration, transparency, anti-corruption, decreased bureaucracy, and improved organizational capacity and innovative practices. However, they face challenges during this transition since they need a holistic roadmap, including where to start and what to do to utilize the open data concept. To satisfy this need, we developed a theoretically grounded and methodologically rigorous process reference model for the open data domain to assess the current situation and provide a road map for improvements. The open data process reference model (OD-PRM), consisting of 23 open data-specific process definitions with a comprehensive perspective on the domain, is developed based upon the ISO/IEC 330xx family of standards. Owing to the OD-PRM, an organization's open data process capability and maturity levels can be assessed based on ISO/IEC 3300xx to provide a current level assessment and a roadmap for improvement to implement, use, maintain, and publish open data in a standardized manner.
... Few studies have been found referring to ImazonGeo, which is an important system in generating data that enables analysis by society, assisting in constructing and developing public policies [46][47][48] . The Mann-Kendall test results obtained here show a trend for the increase in deforestation over the years evaluated and an increase in polygons, except for polygons from PRODES. ...
The guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann–Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo.
... The effects of digitalization, from the perspective of implications for accountability, can be split into two main categories: (i) increased improvements to policies and services, thanks to the use of new data or new digital forms of accountability (e.g., Sa & Grieco, 2016;Zhao et al., 2016) and (ii) increased transparency, accountability, legitimacy, and trust in governments (e.g., Mendieta & Alonso, 2017). ...
This study discusses the current state of the art and future directions of research on digitalization, accountability, and accounting in public services. Through a systematic literature review, we investigate 232 articles published between 1998 and the first quarter of 2020. These studies are analyzed looking at the implications of the increasing digitalization of the public realm for the (i) production of data, (ii) consumption of data, and (iii) their subsequent effects. Based upon this analysis, we identify the following emerging critical digital accountability issues and related future research avenues: the potential for dialogic and horizontal, multicentric accountability; the blurring of accountability roles and boundaries; the increasing relevance of translation processes and translators’ roles—and the need to ensure accountability in such translations; the need to pay stronger attention to social equity and inclusivity implications of digitalization.
... Thirdly, it is necessary to facilitate access to RS data to broaden the user base, also by implementing open and user-friendly environments to handle data [268]. This issue concerns particularly forest management in developing countries considering that expertise in RS data acquisition and analysis is mainly held by stakeholders of wealthier countries [269]. Part I of the present review [3] reported on how UAV-RS research studies are poor in places where the forest heritage is enormous (especially in Africa and South America)-technology transfer is essential, but, in these cases, its success does not depend only on researchers' efforts but involves all forestry stakeholders, especially public organisms. ...
Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community. Due to the progress in platforms and sensors and the opening of the dedicated market, unmanned aerial vehicle–remote sensing (UAV–RS) is improving its key role in the forestry sector as a tool for sustainable management. The use of UAV (Unmanned Aerial Vehicle) in precision forestry has exponentially increased in recent years, as demonstrated by more than 600 references published from 2018 until mid-2020 that were found in the Web of Science database by searching for “UAV”+“forest”. This result is even more surprising when compared with similar research for “UAV”+“agriculture”, from which emerge about 470 references. This shows how UAV–RS research forestry is gaining increasing popularity. In Part II of this review, analyzing the main findings of the reviewed papers (227), numerous strengths emerge concerning research technical issues. UAV–RS is fully applicated for obtaining accurate information from practical parameters (height, diameter at breast height (DBH), and biomass). Research effectiveness and soundness demonstrate that UAV–RS is now ready to be applied in a real management context. Some critical issues and barriers in transferring research products are also evident, namely,(1) hyperspectral sensors are poorly used, and their novel applications should be based on the capability of acquiring tree spectral signature especially for pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible and open-source tools that can foster researcher activities and support technology transfer among all forestry stakeholders, and (3) a clear lack exist in sensors and platforms interoperability for large-scale applications and for enabling data interoperability.
... Non-linear methods have greater predictive capacity for school performance and constitute a methodology to be explored in Brazil, where only few studies are available [36] opposing to the world scenario, where such tools have been widely used to detect factors related to school performance by many ways [24,[37][38][39][40]. Educational data can assist in the formation of tools for educational monitoring, as is already the case in the environmental area [41]. The use of Data Science has proven to be a form of differential analysis, which has allowed companies to maximize their productivity and profits. ...
Educational indicators are metrics that assist in assessing the quality of the educational system. They are often associated with economic and social factors suggested to contribute to good school performance, however there is no consensus on the impact of these factors. The main objective of this work was to evaluate the factors related to school performance. Using a data set composed by Brazilian schools' performance (IDEB), socioeconomic and school structure variables, we generated different models. The non-linear model predicted the best performance, measured by the error and determination coefficient metrics. The het-erogeneity of the importance of the variable between school cycles and regions of the country was detected, this effect may contribute to the development of public educational policies.
... Research output is therefore not only expected to serve the public good (Hazelkorn and Gibson, 2019), but a broad view of the social contract conceptually situates scientific knowledge generated with public funds within the public trust (Schroeder et al., 1989;Gibbons, 1999;Hetland, 2017;Krishna, 2020; for important exceptions, see Fox, 2020). Advocacy for Open Science has grown in recent decades (Sá and Grieco, 2016;Cribb and Sari, 2010;Piwowar et al., 2018;NASEM, 2018) but even when scholarly publications are open access, empirical findings too often remain behind a paywall of jargon. As such, institutions, funding agencies, professional societies, and individual scholars increasingly recognize the importance of science communication (hereafter SciComm) and informal STEM education to reach learners, clinicians, policy-makers, and other members of the general public (Beaulieu et al., 2018;Jessani et al., 2018;Bell, 2016;National Science Board, 2011;Yuan et al., 2019). ...
March Mammal Madness is a science outreach project that, over the course of several weeks in March, reaches hundreds of thousands of people in the United States every year. We combine four approaches to science outreach – gamification, social media platforms, community event(s), and creative products – to run a simulated tournament in which 64 animals compete to become the tournament champion. While the encounters between the animals are hypothetical, the outcomes rely on empirical evidence from the scientific literature. Players select their favored combatants beforehand, and during the tournament scientists translate the academic literature into gripping “play-by-play” narration on social media. To date ~1100 scholarly works, covering almost 400 taxa, have been transformed into science stories. March Mammal Madness is most typically used by high-school educators teaching life sciences, and we estimate that our materials reached ~1% of high-school students in the United States in 2019. Here we document the intentional design, public engagement, and magnitude of reach of the project. We further explain how human psychological and cognitive adaptations for shared experiences, social learning, narrative, and imagery contribute to the widespread use of March Mammal Madness.
... From the analysis of existing shared neuroimaging data sets, Poldrackh and Gorgolewsk (2014) pointed that data sharing generated lots of benefits, including: maximizing the contribution of research subjects, enabling new questions, enhancing reproducibility, improving research practices, test bed for new analysis methods, reducing the cost of doing science, and protecting valuable scientific resources. Sa and Grieco (2016) pointed that open research data not only contributed to scientific development but also enabled science-policy dialogue helpful to scientific decision-making. ...
To encourage research transparency and replication, more and more journals have been requiring authors to share original datasets and analytic procedures supporting their publications. Does open data boost journal impact? In this article, we report one of the first empirical studies to assess the effects of open data on journal impact. China Industrial Economics (CIE) mandated authors to open their research data in the end of 2016, which is the first to embrace open data among Chinese journals and provides a natural experiment for policy evaluation. We use the data of 37 Chinese economics journals from 2001 to 2019 and apply synthetic control method to causally estimate the effects of open data, and our results show that open data has significantly increased the citations of journal articles. On average, the current- and second-year citations of articles published with CIE have increased by 1 ~ 4 times, and articles published before the open data policy also benefited from the spillover effect. Our findings suggest that journals can leverage compulsory open data to develop reputation and amplify academic impacts.
... While the arguments advanced as to why data should remain closed are to be expected from the viewpoint of individual actors, collectively they arouse "…a sense of mistrust in complex, impenetrable models and enigmatic datasets" (Pfenninger et al., 2017, p. 213). Moreover, the calls for open data are consistent with the calls for public sector transparency and accountability (Sá & Grieco, 2016). ...
Following the trenchant criticism of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report concerning the lack of transparency in integrated assessment models (IAMs), much attention has been given to addressing this issue in the preparation of the Sixth Assessment Report (AR6). The issue of IAM transparency has been an ongoing concern for approximately two decades regarding the cloaking of value‐laden assumptions and output uncertainties. Due to the opaque nature of IAMs, the credibility of modeling results and the associated policy recommendations are patently limited, with policymakers inevitably having reservations as to the robustness of modeling outcomes given the deficit of information regarding the underlying assumptions. In an attempt to address the issue of a lack of transparency concerning IAM usage by the IPCC, a database containing the climate mitigation scenario ensemble which underpinned the Special Report on Global Warming of 1.5°C was made publicly available, the IAMC 1.5°C Scenario Explorer database. Despite this database, the omission of critical model input data and accompanying supporting documentation from its content fails to fulfill its raison d'être, that is to say, to ensure reproducibility and transparency. If the issue of IAM transparency is not fully addressed in the upcoming AR6 with respect to the provision of IAM input data, accompanied by supporting documentation, then the IPCC will have failed to meet its own declared commitment for this assessment cycle.
This article is categorized under:
• Integrated Assessment of Climate Change > Integrated Assessment Modeling
Abstract
Illustrated by Owen Li, PhD.
... The open data movement not only pressures the government to release data that had previously been controlled by the government; it also offers new opportunities for participation from citizens (Clarke & Margetts, 2014). It is argued that open data can facilitate scientific research and knowledge accumulation (Sá & Grieco, 2016), promote transparency and accountability (Mayernik, 2017), and inform citizens to make better choices in their daily lives (Keserū & Chan, 2015). Despite its promise, there is a lack of empirical evidence about the actual use and impact of open data. ...
The disclosure of public information is an important issue in government practice. Freely used and accessible data produced by government bodies presumably encourages citizen participation and makes government more transparent and accountable. However, there is limited evidence that citizens would take advantage of open data and on what drives that usagee. This study expands the technology acceptance model to take into account citizens’ perception of open data’s potential societal risks as well as potential advantages to society and the advantages of delivering positive social outcomes. The analysis of results fromof an online survey conducted in Taiwan in May 2017 confirms that a majority of respondents agree that open crime data has advantages compared with aggregate-level statistical data, while risks involved in the adoption of open crime data is are indeed a concern for a majority of respondents. Both help to explain citizens’ intentions of using to use open crime data. Citizens’ perception of usefulness is positively related to their intention to use open data. However, perceived ease of use of open crime data is not significantly associated with the intention to use open crime data directly. Future research should consider other ways to reach citizens who do not use the internet regularly. A better understanding of citizens’ responses to open data helps government design continued improvements to open data.
... New opportunities for real-time insights into behavioral patterns are appearing, as evidenced by the rise of epidemiology and population studies (Rotily et al, 2012), the addition of IT departments in all public hospitals (they are mandatory by law) and the widespread addition of smart health insurance cards. In many other areas (e.g. the environment, urban planning), availability of data has encouraged public debate and evidence-based government decisions (Sá, & Grieco, 2016). In theory, the dissemination of administrative data and performance information has the potential to enable external actors such as patient associations and the public to evaluate, sometimes reorient, public programs. ...
... Access to data, and particularly to open data, can be beneficial for science, public policy and society, and can inform evidence-based governmental decisions (Sá & Grieco, 2016;Sivarajah et al., 2016). Open data may be obtained from governments, publicly funded research organisations and private organisations (Vercamer, Steurtewagen, Van den Poel, & Vermeulen, 2016), as well as from social media (Kalampokis, Hausenblas, & Tarabanis, 2011;Poel et al., 2015) and sensors (Poel et al., 2015). ...
This article describes how virtual research environments (VREs) offer new opportunities for researchers to analyse open data and to obtain new insights for policy making. Although various VRE-related initiatives are under development, there is a lack of insight into how VREs support collaborative open data analysis by researchers and how this might be improved, ultimately leading to input for policy making to solve societal issues. This article clarifies in which ways VREs support researchers in open data analysis. Seven cases presenting different modes of researcher support for open data analysis were investigated and compared. Four types of support were identified: 1) ‘Figure it out yourself’, 2) ‘Leading users by the hand’, 3) ‘Training to provide the basics’ and 4) ‘Learning from peers’. The author provides recommendations to improve the support of researchers’ open data analysis and to subsequently obtain new insights for policy making to solve societal challenges.
... El creciente interés por los Open Data va ligado, por una parte, a que la sociedad disponga de una información beneficiosa para la investigación y, consecuentemente, a una mejora de la política pública y de la sociedad (Sá 2016), y por otra parte a la implantación de una política de transparencia en el ejercicio del gobierno público (Gunnlaugsdottir 2016), unida ésta a un código ético para la práctica de dicha transparencia (Oztoprak 2016). La tecnología (TIC) permite que avancemos en establecer unas relaciones próximas e inmediatas entre gobiernos y ciudadanos. ...
La transparencia en el sector público cubre muchos ámbitos, además de la propia administración pública. La normativa española ha regulado recientemente, tanto a nivel estatal como de los gobiernos autonómicos, los criterios para implementar un gobierno transparente que garantice la confianza de los ciudadanos con sus gobernantes. Se analiza si el sistema de la gestión de la transparencia ha asegurado una independencia frente al poder ejecutivo, y si ese sistema permite realizar auditorías confiables, especialmente independientes, que inspeccionen el grado de cumplimiento de la transparencia en el sector público
... Outside of the climate change literature, however, a number of other themes arise in regard to the role of evidence-based policymaking and scientist engagement in the process overall. In particular, researchers have analyzed both the factors that influence the engagement of science in the policy justification process, and how this engagement can be advanced in the field of science and technology policy in particular (Bhushan 2015;Costa, Desmarais, and Hird 2016a;Sá and Grieco 2016;Howieson and Taylor 2016). Policymakers are much more likely to utilize scientific research when attempting to justify regulatory decisions that attract attention from outside actors, including the media, policy elites, and the general public and, as a result, determine that scientific research is extremely valuable to policymakers when the saliency of the regulation in question is high (Costa, Desmarais, and Hird 2016b). ...
The societal impacts of scientific and technological advances – whether desirable or undesirable – have been one of the primary foci of contemporary policy research, much of which employs distinct interdisciplinary approaches. In this paper, we seek to characterize the topical, methodological, theoretical, and geographical trends of recent science and technology policy studies. Utilizing reputable scholarly journals within the related subfield of policy science, we review the recent research articles on science and technology policy as they relate to policy development, while paying particular attention to capturing any systemic patterns of trends. We conclude with a discussion of the various ramifications of our findings for future research directions and, in the process, highlight issues including technological innovation and diffusion, science and technology for sustainable energy development, evidence-based decision-making, and information technology and cyber security.
... Distributing data is not only a technological issue. It contains organizational models and research practices, and also it involves institutional, legal and economic factors [25]. Many scientific journals maintain the reveal of experimental data therefore data can be reused, reproduced and confirmed [7]. ...
Background: Research Software is a concept that has been only recently clarified. In this paper we address the need for a similar enlightenment concerning the Research Data concept.
Methods: Our contribution begins by reviewing the Research Software definition, which includes the analysis of software as a legal concept, followed by the study of its production in the research environment and within the Open Science framework. Then we explore the challenges of a data definition and some of the Research Data definitions proposed in the literature.
Results: We propose a Research Data concept featuring three characteristics: the data should be produced (collected, processed, analyzed, shared & disseminated) to answer a scientific question, by a scientific team, and has yield a result published or disseminated in some article or scientific contribution of any kind.
Conclusions: The analysis of this definition and the context in which it is proposed provides some answers to the Borgman’s conundrum challenges, that is, which Research Data might be shared, by whom, with whom, under what conditions, why, and to what effects. They are completed with answers to the questions: how? and where?
Background: Numerous mechanisms exist to incentivise researchers to share their data. This scoping review aims to identify and summarise evidence of the efficacy of different interventions to promote open data practices and provide an overview of current research.
Methods: This scoping review is based on data identified from Web of Science and LISTA, limited from 2016 to 2021. A total of 1128 papers were screened, with 38 items being included. Items were selected if they focused on designing or evaluating an intervention or presenting an initiative to incentivise sharing. Items comprised a mixture of research papers, opinion pieces and descriptive articles.
Results: Seven major themes in the literature were identified: publisher/journal data sharing policies, metrics, software solutions, research data sharing agreements in general, open science ‘badges’, funder mandates, and initiatives.
Conclusions: A number of key messages for data sharing include: the need to build on existing cultures and practices, meeting people where they are and tailoring interventions to support them; the importance of publicising and explaining the policy/service widely; the need to have disciplinary data champions to model good practice and drive cultural change; the requirement to resource interventions properly; and the imperative to provide robust technical infrastructure and protocols, such as labelling of data sets, use of DOIs, data standards and use of data repositories.
Background: Research Software is a concept that has been only recently clarified. In this paper we address the need for a similar enlightenment concerning the Research Data concept.
Methods: Our contribution begins by reviewing the Research Software definition, which includes the analysis of software as a legal concept, followed by the study of its production in the research environment and within the Open Science framework. Then we explore the challenges of a data definition and some of the Research Data definitions proposed in the literature.
Results: We propose a Research Data concept featuring three characteristics: the data should be produced (collected, processed, analyzed, shared & disseminated) to answer a scientific question, by a scientific team, and has yield a result published or disseminated in some article or scientific contribution of any kind.
Conclusions: The analysis of this definition and the context in which it is proposed provides some answers to the Borgman’s conundrum challenges, that is, which Research Data might be shared, by whom, with whom, under what conditions, why, and to what effects. They are completed with answers to the questions: how? and where?
Background: Numerous mechanisms exist to incentivise researchers to share their data. This scoping review aims to identify and summarise evidence of the efficacy of different interventions to promote open data practices and provide an overview of current research.
Methods: This scoping review is based on data identified from Web of Science and LISTA, limited from 2016 to 2021. A total of 1128 papers were screened, with 38 items being included. Items were selected if they focused on designing or evaluating an intervention or presenting an initiative to incentivise sharing. Items comprised a mixture of research papers, opinion pieces and descriptive articles.
Results: Seven major themes in the literature were identified: publisher/journal data sharing policies, metrics, software solutions, research data sharing agreements in general, open science ‘badges’, funder mandates, and initiatives.
Conclusions: A number of key messages for data sharing include: the need to build on existing cultures and practices, meeting people where they are and tailoring interventions to support them; the importance of publicising and explaining the policy/service widely; the need to have disciplinary data champions to model good practice and drive cultural change; the requirement to resource interventions properly; and the imperative to provide robust technical infrastructure and protocols, such as labelling of data sets, use of DOIs, data standards and use of data repositories.
An index of the release of open government data, published in 2016 by the Open Knowledge Foundation, shows that there is significant variability in the country's supply of this public good. What explains these crosscountry differences? Adopting an interdisciplinary approach based on data science and economic theory, we developed the following research workflow. First, we gather, clean, and merge different datasets released by institutions such as the Open Knowledge Foundation, World Bank, United Nations, World Economic Forum, Transparency International, Economist Intelligence Unit, and International Telecommunication Union. Then, we conduct feature extraction and variable selection founded on economic domain knowledge. Next, we perform several linear regression models, testing whether crosscountry differences in the supply of open government data can be explained by differences in the country's economic, social, and institutional structures. Our analysis provides evidence that the country's civil liberties, government transparency, quality of democracy, efficiency of government intervention, economies of scale in the provision of public goods, and the size of the economy are statistically significant to explain the crosscountry differences in the supply of open government data. Our analysis also suggests that political participation, sociodemographic characteristics, and demographic and global income distribution dummies do not help to explain the country's supply of open government data. In summary, we show that crosscountry differences in governance, social institutions, and the size of the economy can explain the global distribution of open government data.
Open data are freely accessible online, available to be reused. They can be used for the development of applications which improve citizens’ life. A way to boost the development of innovative applications is by hosting hackathons, workshops and conferences. Apparently, as far as entrepreneurship, open data impact on economic growth, innovation, empowerment and new or improved products and services. There is limited previous research not only on what motivates the developers to participate in open data competitions, but also on the benefits and challenges which are caused from the use of open data. Furthermore, researches focus on factors that affect nascent entrepreneurs’ decision to create a startup but researchers in the field of open data and hackathons relative researches are limited. The purpose of this chapter is to present a theoretical framework in order to examine the impact of motivations, benefits and barriers of the use of open data in the participation in hackathons and to develop a startup based on their applications.
Riparian vegetation is a central component of the hydrosystem. As such, it is often subject to management practices that aim to influence its ecological, hydraulic or hydrological functions. Remote sensing has the potential to improve knowledge and management of riparian vegetation by providing cost-effective and spatially continuous data over wide extents. The objectives of this review were twofold: to provide an overview of the use of remote sensing in riparian vegetation studies and to discuss the transferability of remote sensing tools from scientists to managers. We systematically reviewed the scientific literature (428 articles) to identify the objectives and remote sensing data used to characterize riparian vegetation. Overall, results highlight a strong relationship between the tools used, the features of riparian vegetation extracted and the mapping extent. Very high-resolution data are rarely used for rivers longer than 100 km, especially when mapping species composition. Multi-temporality is central in remote sensing riparian studies, but authors use only aerial photographs and relatively coarse resolution satellite images for diachronic analyses. Some remote sensing approaches have reached an operational level and are now used for management purposes. Overall, new opportunities will arise with the increased availability of very high-resolution data in understudied or data-scarce regions, for large extents and as time series. To transfer remote sensing approaches to riparian managers, we suggest mutualizing achievements by producting open-access and robust tools. These tools will then have to be adapted to each specific project, in collaboration with managers.
Purpose
The purpose of this study is to discuss the possibility of setting up a platform for inclusive policymaking process drawing upon the blockchain concept. The study posits that blockchain also has great potentials in non-financial applications, such as in policymaking, where there is a need for bottom-up approaches with more decentralized, distributed and evidence-based processes.
Design/methodology/approach
The study makes use of an analogy-based creative design methodology. The design science paradigm has its roots in engineering and the sciences of the artificial (Simon, 1996). As a problem-solving paradigm for solving complex engineering issues, design science seeks to create innovations that define the ideas, practices, technical capabilities and products through which the analysis, design, implementation and use of information systems can be effectively and efficiently accomplished. In the present study, the policy development theories and the logic of blockchain are synthesized to prepare a task model for the “IdeaChain” concept as a platform for creating, sharing and validating novel ideas as well as converting them into policies or new ventures through the funding mechanisms.
Findings
The IdeaChain concept is designed and demonstrated through its use in the domain of science, technology and innovation (STI) policy, which can be extended to cover all innovative activities linking the whole process from their emergence, funding, development, implementation and impact upon policy.
Originality/value
Blockchain is mostly discussed in literature with its impact on financial sector. IdeaChain is the first attempt to explore the potentials of blockchain in STI policymaking.
Open data are freely accessible online, available to be reused. They can be used for the development of applications which improve citizens’ life. A way to boost the development of innovative applications is by hosting hackathons, workshops and conferences. Apparently, as far as entrepreneurship, open data impact on economic growth, innovation, empowerment and new or improved products and services. There is limited previous research not only on what motivates the developers to participate in open data competitions, but also on the benefits and challenges which are caused from the use of open data. Furthermore, researches focus on factors that affect nascent entrepreneurs’ decision to create a startup but researchers in the field of open data and hackathons relative researches are limited. The purpose of this chapter is to present a theoretical framework in order to examine the impact of motivations, benefits and barriers of the use of open data in the participation in hackathons and to develop a startup based on their applications.
The emerging practice of open science, which makes the entire process of a scientific investigation available, could extend membership of the research community to new, public audiences, who do not have access to science’s long-established trust mechanisms. This commentary considers if the structures that enable scientists to trust each other, and the public to trust scientists, are enriched by the open science approach. The completeness of information provided by open science, whether as a replacement for or complement to older systems for establishing trust within science, makes it a potentially useful “trust technology.”
This paper presents a methodology for detecting deforestation activities in a near real time using Terra MODIS data. The proposed methodology, named " DETER " Project (" Detecção em Tempo Real do Desflorestamento na Amazônia " – Real Time Deforestation Detection in Amazonia), is based on the PRODES Digital methodology that uses the Landsat TM and/or ETM+ images. Then DETER methodology consists on generating fraction images, segmentation of soil fraction images, classification using non supervised approach, mapping and editing the classified image, using MODIS daily data. The PRODES Digital and DETER projects are part of the " Estimate of deforestation in Amazonia " activities performed annually by Instituto Nacional de Pesquisas Espaciais (INPE). DETER project is providing information about the deforestation occurring through the year and then PRODES Digital is mapping and estimating the annual deforestation. Therefore these informations are consistent between these two projects and useful for the Government Organizations Actions. These informations are available in the INPE/PRODES Website (http://www.obt.inpe.br/prodes/).
Despite the development of Open Data platforms, the wider deployment of Open Data still faces significant barriers. It requires identifying the obstacles that have prevented e-government bodies either from implementing an Open Data strategy or from ensuring its sustainability.This paper presents the results of a study carried out between June and November 2012, in which we analyzed three cases of Open Data development through their platforms, in a medium size city (Rennes, France), a large city (Berlin, Germany), and at national level (UK). It aims to draw a clear typology of challenges, risks, limitations, barriers, all terms used by the different stakeholders with diverse meanings and based on different motivations. Indeed the issues and constraints faced by re-users of public data differ from the ones encountered by the public data providers. Through the analysis of the experiences in opening data, we attempt to identify how barriers were overcome and how risks were managed. Beyond passionate debates in favor or against Open Data, we propose to consider the development of an Open Data initiative in terms of risks, contingency actions, and expected opportunities. We therefore present in the next sections the risks to Open Data organized in 7 categories: (1) governance, (2) economic issues, (3) licenses and legal frameworks, (4) data characteristics, (5) metadata, (6) access, and (7) skills.
Several movements have emerged related to the general idea of promoting 'openness' in science. Research councils are key institutions in bringing about changes proposed by these movements, as sponsors and facilitators of research. In this paper we identify the approaches used in Canada, the US and the UK to advance open science, as a step towards understanding how policy in this area is evolving. The findings highlight three broad patterns across the countries, showing that open science is supported not only be the activities of individual research councils, but also through government mandates and inter-council cooperation. These patterns involve efforts to create a digital infrastructure for open science, to foster open access, and to support open data initiatives.
Although there have been many recent calls for increased data sharing, the majority of environmental scientists do not make
their individual data sets publicly available in online repositories. Current data-sharing conversations are focused on overcoming
the technological challenges associated with data sharing and the lack of rewards and incentives for individuals to share
data. We argue that the most important conversation has yet to take place: There has not been a strong ethical impetus for
sharing data within the current culture, behaviors, and practices of environmental scientists. In this article, we describe
a critical shift that is happening in both society and the environmental science community that makes data sharing not just
good but ethically obligatory. This is a shift toward the ethical value of promoting inclusivity within and beyond science.
An essential element of a truly inclusionary and democratic approach to science is to share data through publicly accessible
data sets.
The aim of this study is to report the use of TerraAmazon in the Andean region. For this purpose we selected the mid-watershed of the Chama River located in the Mérida state in Venezuela, the changes in the forest cover were assessed using Landsat images between the time periods 1988-2002 and 2002-2014. To set up the system we built a data base PostGresSQL, the conceptual framework, access control, phase control, project, control rules, categories. We built the year 0 (1988) using the linear spectral mixing model (LSMM), deriving from this process we obtain the vegetation, shadow and soil cover. The soil cover was segment and further used to interpret the composition of 453 remaining forest and non-forest areas, on this categories there were identified the gains and losses for the year 1 (2002), the same process was done for the year 2 (2014). In the analyzed period (26 yr) 27% of the forest cover remains without change, the lower and mid part of the wathershed was the area with higher changes particularly in the sub-watershed Albarregas and Mucujún, and also in the micro-watersheds La Portuguesa, Montalban y La Mesa, this area is cover mainly by the ecological units sub-deciduos montane forest, lower montane cloud forest and the also by the principal urban areas of the Chama watershed.
Ideas of open access, open data and open science are transforming the world of scientific inquiry as we speak. Every day thousands of ordinary citizens are engaging in data collection and data processing, giving rise to the new field of citizen science. Never before has the technology enabled scientists to reach out to such vast numbers of collaborators and show their work to the public. From pattern recognition in Hubble space telescope images of distant galaxies to field observations of migration patterns of birds in the rural areas of United States, the possibilities are countless. Certainly this new trend poses important problems and challenges, but it is also obvious that wide acceptance of citizen science can lead not only to great scientific results, but to the popularization of scientific method among the public. In the paper we examine the current state of citizen science, we outline some of the most interesting and difficult challenges in leading scientific projects on such scale, and we present typologies of citizen science projects. We also provide a survey of ICT tools available for citizen science projects.
Millions of hectares of humid tropical forest are lost each year. Here we introduce the ForestWatchers project, a citizen cyberscience initiative that proposes to involve citizens around the globe in monitoring deforestation. ForestWatchers combines volunteered thinking with participatory sensing. In the project's volunteered thinking segment, volunteers with their own smartphones, tablets and notebooks, are asked to use a Web interface to review satellite images of forested regions, and confirm whether automatic assignments of forested and deforested regions are correct. In the participatory sensing segment, citizens are invited to contribute numerous types of data on the status of forested areas, such as pictures, videos or sound records. As the first forest-monitoring program to directly involve lay citizens in tropical forest monitoring, the ForestWatchers project aims at providing volunteer-assisted deforestation assessment for countries, regions or communities that do not have the necessary infrastructure or manpower to do so otherwise.
The monitoring of forests is an essential tool for countries that adopt as public policy the preservation of its forests (especially those located in tropical regions such as Brazil, Central Africa and Southeast Asia), allowing better management and supervision of forest resources. Since 1988, with the PRODES project, INPE has been monitoring and producing annual rates of deforestation for the Brazilian Amazon. From the year 2002, these estimates started to be produced by digital classification of images using the SPRING software wich riqueired independent data bases, creating a complex operational environment, which increased even more in complexity by the use of imagery from other satellites, CBERS and DMC necessary to ensure the availability of data from to map periodic deforestation. TerraAmazon System was developed to simplify this scenario, working on a more robust, integrated and secure database structure, allowing the concurrent use of the same basic spatial information, structured in topology rules and access controls. This paper presents the potential of the TerraAmazon system for monitoring of deforested areas in a stretch of Gabon territory, Central Africa.
Background
With mounting global environmental, social and economic pressures the resilience and stability of forests and thus the provisioning of vital ecosystem services is increasingly threatened. Intensified monitoring can help to detect ecological threats and changes earlier, but monitoring resources are limited. Participatory forest monitoring with the help of “citizen scientists” can provide additional resources for forest monitoring and at the same time help to communicate with stakeholders and the general public. Examples for citizen science projects in the forestry domain can be found but a solid, applicable larger framework to utilise public participation in the area of forest monitoring seems to be lacking. We propose that a better understanding of shared and related topics in citizen science and forest monitoring might be a first step towards such a framework.
Methods
We conduct a systematic meta-analysis of 1015 publication abstracts addressing “forest monitoring” and “citizen science” in order to explore the combined topical landscape of these subjects. We employ ‘topic modelling’, an unsupervised probabilistic machine learning method, to identify latent shared topics in the analysed publications.
Results
We find that large shared topics exist, but that these are primarily topics that would be expected in scientific publications in general. Common domain-specific topics are under-represented and indicate a topical separation of the two document sets on “forest monitoring” and “citizen science” and thus the represented domains. While topic modelling as a method proves to be a scalable and useful analytical tool, we propose that our approach could deliver even more useful data if a larger document set and full-text publications would be available for analysis.
Conclusions
We propose that these results, together with the observation of non-shared but related topics, point at under-utilised opportunities for public participation in forest monitoring. Citizen science could be applied as a versatile tool in forest ecosystems monitoring, complementing traditional forest monitoring programmes, assisting early threat recognition and helping to connect forest management with the general public. We conclude that our presented approach should be pursued further as it may aid the understanding and setup of citizen science efforts in the forest monitoring domain.
Expanding on recent debates in environmental governance and political science, we show that the relation between environmental transparency and public accountability is far from linear and politically neutral. This is particularly true in moments of environmental crises, when transparency regimes are most likely to emerge as an integral part of the palette of blame-avoidance strategies of accountors in their attempt to disqualify accountees’ perceptions of environmental harm and irreparable loss. Drawing upon the sociological approach to the study of transparency regimes, we discuss the emergence and evolution over time of deforestation monitoring in Brazil, a transparency regime based on GIS and Remote Sensing, and led by the Brazilian National Institute for Space Research (INPE) since 1989. We arrive at three conclusions. First, the evolution of transparency regimes is conflictual, culturally-embedded and emergent. Second, the relation between accountors and accountees is not stable but includes switches over time as blame-avoidance strategies unfold. Finally, solutions in a blame-game are temporary and may cause a future crisis, as the social context changes and becomes incompatible with the transparency regime of the day.
The emerging practice of open science, which makes the entire process of a scientific investigation available, could extend membership of the research community to new, public audiences, who do not have access to science’s long-established trust mechanisms. This commentary considers if the structures that enable scientists to trust each other, and the public to trust scientists, are enriched by the open science approach. The completeness of information provided by open science, whether as a replacement for or complement to older systems for establishing trust within science, makes it a potentially useful “trust technology.”
This paper examines the possibilities that information and communication technology (ICT) provides for the achievement of environmental sustainable development – one of the key millennium development goals (MDGs). We base our paper on primary and secondary empirical data pertaining to the history of the governance of the Brazilian Amazon and the role of geographic information systems (GISs) in the region. Specifically, we argue that in order for the MDG to be achieved what is required is a thorough understanding of the differing institutional logics that have surrounded the past and current use of GIS in the Amazon region. We will argue that due to conflicting institutional logics the changes that have taken place in relation to the MDG of sustainability should be understood as being both emergent and contested. We will claim that the design and use of ICTs reflects the ways in which these conflicting logics are worked out at any moment in time. We conclude that in order for ICT to contribute to the MDGs, it is important to attend to the historical and contested institutional context and the potential for ICTs to be enacted in unanticipated ways.
Data and information produced by government-funded, public-interest science is a global public good caught between two different trends. On the one hand, the Internet provides valuable new opportunities for overcoming geographic limitations and the promise of unprecedented open access to public information for research on a global basis. On the other hand, there are growing restrictions on the availability and use of public data and information arising from the privatization and commercialization of such sources. This countervailing trend undermines the traditional scientific cooperative and sharing ethos. It diminishes the public domain and open access to such global public goods and leads to a host of lost opportunity costs at both the national and international levels. To address these issues the International Council for Science (ICSU), the United Nations Educational, Scientific and Cultural Organization (UNESCO), the U.S. National Academies, the Committee on Data for Science and Technology (CODATA), and the International Council for Scientific and Technical Information (ICSTI) jointly organized this symposium, which was held on March 10-11, 2003, at UNESCO headquarters in Paris. The symposium brought together policy experts and managers from the government and academic sectors in both developed and developing countries to do the following: (1) describe the role, value, and limits that the public domain and open access to digital data and information have in the context of international research; (2) identify and analyze the various legal, economic, and technological pressures on the public domain in digital data and information and their potential effects on international research; and (3) review the existing and proposed approaches for preserving and promoting the public domain and open access to scientific and technical data and information on a global basis, with particular attention to the needs of developing countries.
Describes documents produced at the United Nations Conference and the Global Forum: The Rio Declaration, a statement of broad principles to guide national conduct on environmental protection and development; treaties on climate change and biodiversity; forest principles statement; and Agenda 21, a presentation of work plans for sustainable development. Products of the nongovernmental organizations meetings are also discussed. (MCO)
Major efforts are currently under way to develop e-infrastructures for research. At the same time, there have been a number of calls for research in the digital realm to foster 'openness', for example in 'open access' policies. This paper explores the relation between e-infrastructures and open science, and argues that there are a number of factors apart from research policy that will shape e-research. These include not only the legal and economic environment, but also the ethos of science, 'open' initiatives outside of research, the momentum of large technological systems, and the activism of experts and wider social movements. The paper assesses the strengths and weaknesses of these factors, as well as the tensions and confluences between openness and e-infrastructures.
The preservation of the world's rain forests is one of the major environmental challenges of our generation. Rain forests are home to a large portion of the world's biodiversity, and play a major role in climate regulatio n and in the hydrological cycle of the Earth. Despite their biological richness and ecol ogical importance, most of the world's rain forests are under increasing pressure of defore station caused by human actions. Deforestation is particularly intense in countr ies with large-scale agricultural production, such as Brazil and Indonesia. In the Brazilia n Amazonia, which covers an area of 4 million km 2 , 17% of the original forest has been cleared, according to the Brazilian deforestation monitoring system, developed by t he Brazilian National Institute for Space Research (INPE). Science Magazine called the Brazilian system "the envy of the world", but warned that, in spite of recent improvem ents in forest monitoring,
he digital revolution has transformed the accumulation of properly curated public research data into an essential upstream resource whose value increases with use. The potential contributions of such data to the creation of new knowledge and downstream economic and social goods can in many cases be multiplied exponentially when the data are made openly available on digital networks. Most developed countries spend large amounts of public resources on research and related scientific facilities and instruments that generate massive amounts of data. Yet precious little of that investment is devoted to promoting the value of the resulting data by preserving and making them broadly available. The largely ad hoc approach to managing such data, however, is now beginning to be understood as inadequate to meet the exigencies of the national and international research enterprise. The time has thus come for the research community to establish explicit responsibilities for these digital resources. This article reviews the opportunities and challenges to the global science system associated with establishing an open data policy.
Access to and sharing of data are essential for the conduct and advancement of science. This article argues that publicly funded research data should be openly available to the maximum extent possible. To seize upon advancements of cyberinfrastructure and the explosion of data in a range of scientific disciplines, this access to and sharing of publicly funded data must be advanced within an international framework, beyond technological solutions. The authors, members of an OECD Follow-up Group, present their research findings, based closely ontheir report to OECD, on key issues in data access, as well as operating principles and management aspects necessary to successful data access regimes.
Ecology is a synthetic discipline benefiting from open access to data from the earth, life, and social sciences. Technological
challenges exist, however, due to the dispersed and heterogeneous nature of these data. Standardization of methods and development
of robust metadata can increase data access but are not sufficient. Reproducibility of analyses is also important, and executable
workflows are addressing this issue by capturing data provenance. Sociological challenges, including inadequate rewards for
sharing data, must also be resolved. The establishment of well-curated, federated data repositories will provide a means to
preserve data while promoting attribution and acknowledgement of its use.
Climate data are dramatically increasing in volume and complexity, just as the users of these data in the scientific community
and the public are rapidly increasing in number. A new paradigm of more open, user-friendly data access is needed to ensure
that society can reduce vulnerability to climate variability and change, while at the same time exploiting opportunities that
will occur.
The objective of this paper is to provide near real time information about deforestation detection (DETER) in the entire Brazilian Amazon using MODIS high temporal resolution images. It is part of the operational deforestation monitoring project to estimate the annual deforestation rate in the Brazilian Amazon (PRODES). A rapid deforestation detection method was designed to support land use policies in this region. In order to evaluate the proposed method a test site was selected covering a Landsat ETM+ scene (227/68) located in Mato Grosso State. For this purpose a multitemporal series of MODIS surface reflectance images (MOD09) and the corresponding ETM+ images from June to October 2002 were analyzed. It was found that small deforested areas (lower than 15 ha) were detected by MODIS images with lower accuracy when compared with ETM+ images. As the deforested areas increase MODIS and ETM+ results tend to converge. This procedure showed to be adequate to operationally detect and monitor deforested areas and has been used since 2004 as part of a government plan to control the Amazon deforestation.
Open Data (OD) is an emerging term in the process of defining how scientific data may be published and re-used without price or permission barriers. Scientists generally see published data as belonging to the scientific community, but many publishers claim copyright over data and will not allow its re-use without permission. This is a major impediment to the progress of scholarship in the digital age. This article reviews the need for Open Data, shows examples of why Open Data are valuable, and summarizes some early initiatives in formalizing the right of access to and re-use of scientific data.
Brazil has waged a successful war on tropical deforestation, and other countries are trying to follow its lead. But victory remains fragile.
In this article, based on data collected through interviews and a workshop, the benefits and adoption barriers for open data have been derived. The results suggest that a conceptually simplistic view is often adopted with regard to open data, which automatically correlates the publicizing of data with use and benefits. Also, five “myths” concerning open data are presented, which place the expectations within a realistic perspective. Further, the recommendation is provided that such projects should take a user's view.
This article contends that although the environmental policy formation process in Brazil has been opened to new actors since the democratic transition, social sectors with clientelistic ties to the state still tend to dominate some policy arenas. To illustrate this argument, the article examines the evolution of policy formation in the case of metallurgical development in the Grande Carajás area in eastern Amazonia (Brazil) from an advocacy coalition perspective. The study maps out the roles of the main actors in the dominant and minority advocacy coalitions in this policy subsystem and their role in shaping the policies affecting this issue. Research shows that despite efforts of the minority coalition to politicize the issue and introduce some proenvironment policy reforms, actors in the main coalition have been able to dominate the policy formation process and stall meaningful reform. The results have been detrimental to environmental conservation in the region.
We must all accept that science is data and that data are science, and thus provide for, and justify the need for the support of, much-improved data curation. (Hanson, Sugden, & Alberts, 2011)
Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice.
In response to the United Nations Framework Convention on Climate Change (UNFCCC) process investigating the technical issues surrounding the ability to reduce greenhouse gas (GHG) emissions from deforestation in developing countries, this paper reviews technical capabilities for monitoring deforestation and estimating emissions. Implementation of policies to reduce emissions from deforestation require effective deforestation monitoring systems that are reproducible, provide consistent results, meet standards for mapping accuracy, and can be implemented at the national level. Remotely sensed data supported by ground observations are key to effective monitoring. Capacity in developing countries for deforestation monitoring is well-advanced in a few countries and is a feasible goal in most others. Data sources exist to determine base periods in the 1990s as historical reference points. Forest degradation (e.g. from high impact logging and fragmentation) also contribute to greenhouse gas emissions but it is more technically challenging to measure than deforestation. Data on carbon stocks, which are needed to estimate emissions, cannot currently be observed directly over large areas with remote sensing. Guidelines for carbon accounting from deforestation exist and are available in approved Intergovernmental Panel on Climate Change (IPCC) reports and can be applied at national scales in the absence of forest inventory or other data. Key constraints for implementing programs to monitor greenhouse gas emissions from deforestation are international commitment of resources to increase capacity, coordination of observations to ensure pan-tropical coverage, access to free or low-cost data, and standard and consensual protocols for data interpretation and analysis.
Environmental policies often strongly depend on environmental monitoring data, yet these increasing datasets are not always used effectively in enacting and implementing public policy. We propose a science–policy data model that defines the conditions that facilitate the use of environmental monitoring data for policy and which could help scientists and policymakers diagnose impediments in the link between science and policy and work more effectively together to use monitoring data in environmental policy. The model includes two parts: (1) criteria for scientific monitoring data to become useful information for public policy; (2) a “data compact,” a relationship between senior scientists and midlevel policymakers that enables translation of environmental monitoring data into knowledge useful for public policy. We compare the model against two case studies in the air quality literature: ozone depleting substances and acid precipitation. Finally, we use the model to assess the potential of a newly developing area that we are researching, use of satellite remote sensing data for fine particulate matter transboundary policy.
This article examines recent e-science initiatives through the lens of the concept of 'research technologies'. It has been argued that e-science research, which makes use of advanced computing tools to share distributed resources via networks, changes the disciplinary nature of research towards greater interdisciplinarity and paves the way for the increasing globalization of research. However, these claims need to be instantiated in concrete research practices. The essay therefore presents three examples of research projects where these two features can be demonstrated. More generally these three projects - in social science hyperlink analysis, high-energy physics, and astronomy - are examples of 'research technologies', which, it has been argued, are often a radical source of innovation. The article describes how the three projects illustrate these arguments about research technologies, but also how this concept is limited as e-science research is still ongoing. The conclusion assesses how the notion of research technologies is useful for understanding how networked computing technologies are changing the current landscape of knowledge production.
Earth scientists need better incentives, rewards and mechanisms to achieve free and open data exchange, says David Carlson.
Image segmentation based on the shade fraction of a Landsat TM image was effective in measuring the areal extent of Amazonian deforestation. The shade fraction image derived from spectral mixture models was related to the forest canopy structure. Dense tropical forest have a medium proportion of shade within their canopy while deforested areas (bare soil, pasture, and/or regrowth)have a comparatively small proportion. Comparison of image segmentation results with conventional techniques showed visual agreement. Even though additional tests are necessary to validate this approach for large areas, the technical soundness of the approach has been demonstrated. Pages: 535-541
Open Data (OD) is an emerging term in the process of defining how scientific data may be published and re-used without price or permission barriers. Scientists generally see published data as belonging to the scientific community, but many publishers claim copyright over data and will not allow its re-use without permission. This is a major impediment to the progress of scholarship in the digital age. This article reviews the need for Open Data, shows examples of why Open Data are valuable and summarises some early initiatives in formalising the right of access to and re-use of scientific data.
Deforestation produces a significant amount of greenhouse gas emissions through burning, clearing, and decay. But exactly
how much? (Read more.)
It represents half of the world's rainforest and is home to one-third of
Earth's species, yet the Amazon has one of the highest rates of
deforestation. Jeff Tollefson looks at efforts to curb the problem.
June 27). Desmatamento na Amazônia não traz surpresa, afirma Marina Silva. Retrieved from <http://www.inpe.br/noticias/namidia/verclipping.php?id=2628>
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DETERring deforestation in the Brazilian Amazon: Environmental monitoring and law enforcement
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monitoring and law enforcement. San Francisco: Climate Policy Initiative: N ucleo de Avaliação de Pol ıticas
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