Cynthia Hudson-Vitale, H. Hadley, Jennifer E. Moore, L. Johnston, Wendy A. Kozlowski, J. Carlson, Mara Blake, Joel Herndon
Niche and proprietary data formats used in cutting-edge research and technology have specific curation considerations and challenges. The increased demand for subject liaisons, library archivists, and digital curators to curate this variety of data types created locally at an institution or organization poses difficulties. Subject liaisons possess discipline knowledge and expertise for a given domain or discipline and digital curation experts know how to properly steward data assets generally. Yet, a gap often exists between the expertise available within the organization and local curation needs. While many institutions and organizations have expertise in certain domains and areas, oftentimes the heterogeneous data types received for deposit extend beyond this expertise. Additionally, evolving research methods and new, cutting-edge technology used in research often result in unfamiliar and niche data formats received for deposit. Knowing how to ‘get-started’ in curating these file types and formats can be a particular challenge. To address this need, the data curation community have been developing a new set of tools - data curation primers. These primers are evolving documents that detail a specific subject, disciplinary area or curation task, and that can be used as a reference or jump-start to curating research data. This paper will provide background on the data curation primers and their content detail the process of their development, highlight the data curation primers published to date, emphasize how curators can incorporate these resources into workflows, and show curators how they can get involved and share their own expertise.
{"title":"Extending the Research Data Toolkit: Data Curation Primers","authors":"Cynthia Hudson-Vitale, H. Hadley, Jennifer E. Moore, L. Johnston, Wendy A. Kozlowski, J. Carlson, Mara Blake, Joel Herndon","doi":"10.2218/ijdc.v15i1.713","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.713","url":null,"abstract":"Niche and proprietary data formats used in cutting-edge research and technology have specific curation considerations and challenges. The increased demand for subject liaisons, library archivists, and digital curators to curate this variety of data types created locally at an institution or organization poses difficulties. Subject liaisons possess discipline knowledge and expertise for a given domain or discipline and digital curation experts know how to properly steward data assets generally. Yet, a gap often exists between the expertise available within the organization and local curation needs. \u0000While many institutions and organizations have expertise in certain domains and areas, oftentimes the heterogeneous data types received for deposit extend beyond this expertise. Additionally, evolving research methods and new, cutting-edge technology used in research often result in unfamiliar and niche data formats received for deposit. Knowing how to ‘get-started’ in curating these file types and formats can be a particular challenge. To address this need, the data curation community have been developing a new set of tools - data curation primers. These primers are evolving documents that detail a specific subject, disciplinary area or curation task, and that can be used as a reference or jump-start to curating research data. This paper will provide background on the data curation primers and their content detail the process of their development, highlight the data curation primers published to date, emphasize how curators can incorporate these resources into workflows, and show curators how they can get involved and share their own expertise.","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91317039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Open research is predicated upon seamless access to curated research data. Major national and European funding schemes, such as Horizon Europe, strongly encourage or require publicly funded data to be FAIR - that is, Findable, Accessible, Interoperable, Reusable (Wilkinson, 2016). What underpins such initiatives are the many data organizations and repositories working with their stakeholders and each other to establish policies and practices, implement them, and do the curatorial work to increase the available, discoverability, and accessibility of high quality research data. However, such work has often been invisible and underfunded, necessitating creative and collaborative solutions. In this paper, we briefly describe how one such case from social science data: the processing of the Eurobarometer data set. Using content analysis of administrative documents and interviews, we detail how European data archives managed the tensions of curatorial work across borders and jurisdictions from the 1970s to the mid-2000s, the challenges that they faced in distributing work, and the solutions they found. In particular, we look at the interactions of the Council of European Social Science Data Archives (CESSDA) and social science data organizations (DO) like UKDA, ICPSR, and GESIS and the institutional and organizational collaborations that made Eurobarometer “too big to fail”. We describe some of the invisible work that they underwent in the past in making data in Europe findable, accessible, interoperable, and conclude with implications for “frictionless” data access and reuse today.
{"title":"Inter-Organisational Coordination Work in Digital Curation: the Case of Eurobarometer","authors":"K. Eschenfelder, K. Shankar","doi":"10.2218/ijdc.v15i1.707","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.707","url":null,"abstract":"\u0000Open research is predicated upon seamless access to curated research data. Major national and European funding schemes, such as Horizon Europe, strongly encourage or require publicly funded data to be FAIR - that is, Findable, Accessible, Interoperable, Reusable (Wilkinson, 2016). What underpins such initiatives are the many data organizations and repositories working with their stakeholders and each other to establish policies and practices, implement them, and do the curatorial work to increase the available, discoverability, and accessibility of high quality research data. However, such work has often been invisible and underfunded, necessitating creative and collaborative solutions. \u0000In this paper, we briefly describe how one such case from social science data: the processing of the Eurobarometer data set. Using content analysis of administrative documents and interviews, we detail how European data archives managed the tensions of curatorial work across borders and jurisdictions from the 1970s to the mid-2000s, the challenges that they faced in distributing work, and the solutions they found. In particular, we look at the interactions of the Council of European Social Science Data Archives (CESSDA) and social science data organizations (DO) like UKDA, ICPSR, and GESIS and the institutional and organizational collaborations that made Eurobarometer “too big to fail”. We describe some of the invisible work that they underwent in the past in making data in Europe findable, accessible, interoperable, and conclude with implications for “frictionless” data access and reuse today. \u0000 \u0000 ","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82981472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent privacy scandals such as Cambridge Analytica and the Nightingale Project show that data sharing must be carefully managed and regulated to prevent data misuse. Data protection law, legal frameworks, and technological solutions tend to focus on controller responsibilities as opposed to protecting data subjects from the beginning of the data collection process. Using a case study of how data subjects can be better protected during data curation, we propose that a co-created data commons can protect individual autonomy over personal data through collective curation and rebalance power between data subjects and controllers.
{"title":"Co-Creating Autonomy: Group Data Protection and Individual Self-determination within a Data Commons","authors":"Janis Wong, Tristan Henderson","doi":"10.2218/ijdc.v15i1.714","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.714","url":null,"abstract":"\u0000Recent privacy scandals such as Cambridge Analytica and the Nightingale Project show that data sharing must be carefully managed and regulated to prevent data misuse. Data protection law, legal frameworks, and technological solutions tend to focus on controller responsibilities as opposed to protecting data subjects from the beginning of the data collection process. Using a case study of how data subjects can be better protected during data curation, we propose that a co-created data commons can protect individual autonomy over personal data through collective curation and rebalance power between data subjects and controllers. \u0000 \u0000 ","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85106359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelle Lindlar, Pia Rudnik, Sarah Jones, Laurence Horton
This paper explores models, concepts and terminology used in the Research Data Management and Digital Preservation communities. In doing so we identify several overlaps and mutual concerns where the advancements of one professional field can apply to and assist another. By focusing on what unites rather than divides us, and by adopting a more holistic approach we advance towards collective curation and preservation strategies.
{"title":"\"You say potato, I say potato\" Mapping Digital Preservation and Research Data Management Concepts towards Collective Curation and Preservation Strategies","authors":"Michelle Lindlar, Pia Rudnik, Sarah Jones, Laurence Horton","doi":"10.2218/ijdc.v15i1.728","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.728","url":null,"abstract":"\u0000This paper explores models, concepts and terminology used in the Research Data Management and Digital Preservation communities. In doing so we identify several overlaps and mutual concerns where the advancements of one professional field can apply to and assist another. By focusing on what unites rather than divides us, and by adopting a more holistic approach we advance towards collective curation and preservation strategies. \u0000 \u0000 ","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75949355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The University of Bristol Research Data Service was set up in 2014 to provide support and training for academic staff and postgraduate researchers in all aspects of research data management. As part of this, the data.bris Research Data Repository was developed to provide a publication platform for research data generated at the University of Bristol. Initially launched in 2015 to provide open access to data, since 2017 it has also been possible to publish access-controlled datasets containing sensitive data via this platform. The vast majority (90%) of datasets published are openly accessible, but there has been steady demand for access-controlled release of datasets containing information that is ethically or commercially sensitive. These cases require careful management of additional risk: for example, where datasets contain information on human participants, balancing the risk of re-identification with the need to provide robust data that maximises research value through re-use. Many groups within the University of Bristol (for example, the Avon Longitudinal Study of Parents and Children) have extensive experience and expertise in this area, but it became apparent that there was a need to provide additional support for researchers who were not able to draw on the experience of these established groups. This practice paper describes the process of setting up a dedicated service to provide training and basic disclosure risk assessments in order to address these skills gaps, and outlines lessons learnt and future directions for the service.
{"title":"Extending Support for Publishing Sensitive Research Data at the University of Bristol","authors":"Zosia Beckles","doi":"10.2218/ijdc.v15i1.712","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.712","url":null,"abstract":"\u0000The University of Bristol Research Data Service was set up in 2014 to provide support and training for academic staff and postgraduate researchers in all aspects of research data management. As part of this, the data.bris Research Data Repository was developed to provide a publication platform for research data generated at the University of Bristol. Initially launched in 2015 to provide open access to data, since 2017 it has also been possible to publish access-controlled datasets containing sensitive data via this platform. \u0000The vast majority (90%) of datasets published are openly accessible, but there has been steady demand for access-controlled release of datasets containing information that is ethically or commercially sensitive. These cases require careful management of additional risk: for example, where datasets contain information on human participants, balancing the risk of re-identification with the need to provide robust data that maximises research value through re-use. Many groups within the University of Bristol (for example, the Avon Longitudinal Study of Parents and Children) have extensive experience and expertise in this area, but it became apparent that there was a need to provide additional support for researchers who were not able to draw on the experience of these established groups. This practice paper describes the process of setting up a dedicated service to provide training and basic disclosure risk assessments in order to address these skills gaps, and outlines lessons learnt and future directions for the service. \u0000","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76828077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Database migration is a crucial aspect of digital collections management, yet there are few best practices to guide practitioners in this work. There is also limited research on the patterns of use and processes motivating database migrations. In the “Migrating Research Data Collections” project, we are developing these best practices through a multi-case study of database and digital collections migration. We find that a first and fundamental problem faced by collection staff is a sheer lack of documentation about past database migrations. We contribute a discussion of ways information professionals can reconstruct missing documentation, and some three approaches that others might take for documenting migrations going forward. [This paper is a conference pre-print presented at IDCC 2020 after lightweight peer review.]
{"title":"Three Approaches to Documenting Database Migrations","authors":"A. Thomer, A. J. Rayburn, Allison R. B. Tyler","doi":"10.2218/ijdc.v15i1.726","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.726","url":null,"abstract":"\u0000Database migration is a crucial aspect of digital collections management, yet there are few best practices to guide practitioners in this work. There is also limited research on the patterns of use and processes motivating database migrations. In the “Migrating Research Data Collections” project, we are developing these best practices through a multi-case study of database and digital collections migration. We find that a first and fundamental problem faced by collection staff is a sheer lack of documentation about past database migrations. We contribute a discussion of ways information professionals can reconstruct missing documentation, and some three approaches that others might take for documenting migrations going forward. \u0000 \u0000[This paper is a conference pre-print presented at IDCC 2020 after lightweight peer review.]","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81908855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ixchel M. Faniel, A. Austin, S. Kansa, Eric C. Kansa, Jennifer Jacobs, Phoebe France
Archaeological excavations are comprised of interdisciplinary teams that create, manage, and share data as they unearth and analyse material culture. These team-based settings are ripe for collective curation during these data lifecycle stages. However, findings from four excavation sites show that the data interdisciplinary teams create are not well integrated. Knowing this, we recommended opportunities for collective curation to improve use and reuse of the data within and outside of the team.
{"title":"Identifying Opportunities for Collective Curation During Archaeological Excavations","authors":"Ixchel M. Faniel, A. Austin, S. Kansa, Eric C. Kansa, Jennifer Jacobs, Phoebe France","doi":"10.2218/ijdc.v15i1.699","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.699","url":null,"abstract":"Archaeological excavations are comprised of interdisciplinary teams that create, manage, and share data as they unearth and analyse material culture. These team-based settings are ripe for collective curation during these data lifecycle stages. However, findings from four excavation sites show that the data interdisciplinary teams create are not well integrated. Knowing this, we recommended opportunities for collective curation to improve use and reuse of the data within and outside of the team.","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87324695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
João Aguiar Castro, Cristiana Sofia Pereira Landeira, J. Silva, Cristina Ribeiro
As researchers are increasingly seeking tools and specialized support to perform research data management activities, the collaboration with data curators can be fruitful. Yet, establishing a timely collaboration between researchers and data curators, grounded in sound communication, is often demanding. In this paper we propose manual content analysis as an approach to streamline the data curator workflow. With content analysis curators can obtain domain-specific concepts used to describe experimental configurations in scientific publications, to make it easier for researchers to understand the notion of metadata and for the development of metadata tools. We present three case studies from experimental domains, one related to sustainable chemistry, one to photovoltaic generation and another to nanoparticle synthesis. The curator started by performing content analysis in research publications, proceeded to create a metadata template based on the extracted concepts, and then interacted with researchers. The approach was validated by the researchers with a high rate of accepted concepts, 84 per cent. Researchers also provide feedback on how to improve some proposed descriptors. Content analysis has the potential to be a practical, proactive task, which can be extended to multiple experimental domains and bridge the communication gap between curators and researchers. [This paper is a conference pre-print presented at IDCC 2020 after lightweight peer review.]
{"title":"Role of Content Analysis in Improving the Curation of Experimental Data","authors":"João Aguiar Castro, Cristiana Sofia Pereira Landeira, J. Silva, Cristina Ribeiro","doi":"10.2218/ijdc.v15i1.705","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.705","url":null,"abstract":"\u0000As researchers are increasingly seeking tools and specialized support to perform research data management activities, the collaboration with data curators can be fruitful. Yet, establishing a timely collaboration between researchers and data curators, grounded in sound communication, is often demanding. In this paper we propose manual content analysis as an approach to streamline the data curator workflow. With content analysis curators can obtain domain-specific concepts used to describe experimental configurations in scientific publications, to make it easier for researchers to understand the notion of metadata and for the development of metadata tools. We present three case studies from experimental domains, one related to sustainable chemistry, one to photovoltaic generation and another to nanoparticle synthesis. The curator started by performing content analysis in research publications, proceeded to create a metadata template based on the extracted concepts, and then interacted with researchers. The approach was validated by the researchers with a high rate of accepted concepts, 84 per cent. Researchers also provide feedback on how to improve some proposed descriptors. Content analysis has the potential to be a practical, proactive task, which can be extended to multiple experimental domains and bridge the communication gap between curators and researchers. \u0000[This paper is a conference pre-print presented at IDCC 2020 after lightweight peer review.] \u0000","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75644201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rebecca D. Frank, Kara Suzuka, Eric E. Johnson, E. Yakel
This paper explores the tension between the tools that data reusers in the field of education prefer to use when working with qualitative video data and the tools that repositories make available to data reusers. Findings from this mixed-methods study show that data reusers utilizing qualitative video data did not use repository-based tools. Rather, they valued common, widely available tools that were collaborative and easy to use.
{"title":"Tool Selection Among Qualitative Data Reusers","authors":"Rebecca D. Frank, Kara Suzuka, Eric E. Johnson, E. Yakel","doi":"10.2218/ijdc.v15i1.710","DOIUrl":"https://doi.org/10.2218/ijdc.v15i1.710","url":null,"abstract":"This paper explores the tension between the tools that data reusers in the field of education prefer to use when working with qualitative video data and the tools that repositories make available to data reusers. Findings from this mixed-methods study show that data reusers utilizing qualitative video data did not use repository-based tools. Rather, they valued common, widely available tools that were collaborative and easy to use. \u0000 ","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79283173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. D. Cosmo, Morane Gruenpeter, B. Marmol, Alain Monteil, Laurent Romary, J. Sadowska
Software has become an indissociable support of technical and scientific knowledge. The preservation of this universal body of knowledge is as essential as preserving research articles and data sets. In the quest to make scientific results reproducible, and pass knowledge to future generations, we must preserve these three main pillars: research articles that describe the results, the data sets used or produced, and the software that embodies the logic of the data transformation. The collaboration between Software Heritage (SWH), the Center for Direct Scientific Communication (CCSD) and the scientific and technical information services (IES) of The French Institute for Research in Computer Science and Automation (Inria) has resulted in a specified moderation and curation workflow for research software artifacts deposited in the HAL the French global open access repository. The curation workflow was developed to help digital librarians and archivists handle this new and peculiar artifact - software source code. While implementing the workflow, a set of guidelines has emerged from the challenges and the solutions put in place to help all actors involved in the process.
{"title":"Curated Archiving of Research Software Artifacts: Lessons Learned from the French Open Archive (HAL)","authors":"R. D. Cosmo, Morane Gruenpeter, B. Marmol, Alain Monteil, Laurent Romary, J. Sadowska","doi":"10.2218/IJDC.V15I1.698","DOIUrl":"https://doi.org/10.2218/IJDC.V15I1.698","url":null,"abstract":"Software has become an indissociable support of technical and scientific knowledge. The preservation of this universal body of knowledge is as essential as preserving research articles and data sets. In the quest to make scientific results reproducible, and pass knowledge to future generations, we must preserve these three main pillars: research articles that describe the results, the data sets used or produced, and the software that embodies the logic of the data transformation. \u0000The collaboration between Software Heritage (SWH), the Center for Direct Scientific Communication (CCSD) and the scientific and technical information services (IES) of The French Institute for Research in Computer Science and Automation (Inria) has resulted in a specified moderation and curation workflow for research software artifacts deposited in the HAL the French global open access repository. The curation workflow was developed to help digital librarians and archivists handle this new and peculiar artifact - software source code. While implementing the workflow, a set of guidelines has emerged from the challenges and the solutions put in place to help all actors involved in the process.","PeriodicalId":87279,"journal":{"name":"International journal of digital curation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73948301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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