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Open Data for Science, Policy, and the Public Good: Open Data

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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.

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... 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 ) ...
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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.
... 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. ...
Article
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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.
... 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). ...
Article
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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.
... 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]. ...
... 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). ...
Article
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.
... 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. ...
Article
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.
... 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. ...
... 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). ...
Article
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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.
... 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. ...
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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.
... 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). ...
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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.
... 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. ...
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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.
... 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. ...
Article
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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.
... 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). ...
Article
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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.
... 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. ...
Article
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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.
... 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). ...
Article
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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.
... 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]. ...
Chapter
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.
... 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. ...
Chapter
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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.
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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.
Article
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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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)
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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.
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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.
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Earth scientists need better incentives, rewards and mechanisms to achieve free and open data exchange, says David Carlson.
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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.
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Deforestation produces a significant amount of greenhouse gas emissions through burning, clearing, and decay. But exactly how much? (Read more.)
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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.
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