Pub Date : 2021-01-19DOI: 10.7191/JESLIB.2021.1188
Wanda Marsolek, Katie Barrick, S. J. Brown, Kristi Bergland, C. Bakker, Shanda L Hunt
Inspired by Reid Boehm’s presentation “Beyond Pronouns: Caring for Transgender Medical Research Data to Benefit All People,” at the Research Data Access and Preservation Summit (RDAP) in March 2018, four librarians from the University of Minnesota (UMN) set out to create a LibGuide to support research on transgender topics as a response to Boehm’s identification of insufficient traditional mechanisms for describing, securing, and accessing data on transgender people and topics. This commentary describes the process used to craft the LibGuide, "Library Resources for Transgender Topics," including assembling a team of interested library staff, defining the scope of the project, interacting with stakeholders and community partners, establishing a workflow, and designing an ongoing process to incorporate user feedback.
{"title":"Two Years in the Making: Library Resources for Transgender Topics","authors":"Wanda Marsolek, Katie Barrick, S. J. Brown, Kristi Bergland, C. Bakker, Shanda L Hunt","doi":"10.7191/JESLIB.2021.1188","DOIUrl":"https://doi.org/10.7191/JESLIB.2021.1188","url":null,"abstract":"Inspired by Reid Boehm’s presentation “Beyond Pronouns: Caring for Transgender Medical Research Data to Benefit All People,” at the Research Data Access and Preservation Summit (RDAP) in March 2018, four librarians from the University of Minnesota (UMN) set out to create a LibGuide to support research on transgender topics as a response to Boehm’s identification of insufficient traditional mechanisms for describing, securing, and accessing data on transgender people and topics. This commentary describes the process used to craft the LibGuide, \"Library Resources for Transgender Topics,\" including assembling a team of interested library staff, defining the scope of the project, interacting with stakeholders and community partners, establishing a workflow, and designing an ongoing process to incorporate user feedback.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"10 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48527757","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}
Pub Date : 2021-01-01Epub Date: 2021-08-11DOI: 10.7191/jeslib.2021.1208
Kasey C Soska, Melody Xu, Sandy L Gonzalez, Orit Herzberg, Catherine S Tamis-LeMonda, Rick O Gilmore, Karen E Adolph
Video data are uniquely suited for research reuse and for documenting research methods and findings. However, curation of video data is a serious hurdle for researchers in the social and behavioral sciences, where behavioral video data are obtained session by session and data sharing is not the norm. To eliminate the onerous burden of post hoc curation at the time of publication (or later), we describe best practices in active data curation-where data are curated and uploaded immediately after each data collection to allow instantaneous sharing with one button press at any time. Indeed, we recommend that researchers adopt "hyperactive" data curation where they openly share every step of their research process. The necessary infrastructure and tools are provided by Databrary-a secure, web-based data library designed for active curation and sharing of personally identifiable video data and associated metadata. We provide a case study of hyperactive curation of video data from the Play and Learning Across a Year (PLAY) project, where dozens of researchers developed a common protocol to collect, annotate, and actively curate video data of infants and mothers during natural activity in their homes at research sites across North America. PLAY relies on scalable standardized workflows to facilitate collaborative research, assure data quality, and prepare the corpus for sharing and reuse throughout the entire research process.
{"title":"(Hyper)active Data Curation: A Video Case Study from Behavioral Science.","authors":"Kasey C Soska, Melody Xu, Sandy L Gonzalez, Orit Herzberg, Catherine S Tamis-LeMonda, Rick O Gilmore, Karen E Adolph","doi":"10.7191/jeslib.2021.1208","DOIUrl":"10.7191/jeslib.2021.1208","url":null,"abstract":"<p><p>Video data are uniquely suited for research reuse and for documenting research methods and findings. However, curation of video data is a serious hurdle for researchers in the social and behavioral sciences, where behavioral video data are obtained session by session and data sharing is not the norm. To eliminate the onerous burden of <i>post hoc</i> curation at the time of publication (or later), we describe best practices in <i>active</i> data curation-where data are curated and uploaded immediately after each data collection to allow instantaneous sharing with one button press at any time. Indeed, we recommend that researchers adopt \"hyperactive\" data curation where they openly share every step of their research process. The necessary infrastructure and tools are provided by Databrary-a secure, web-based data library designed for active curation and sharing of personally identifiable video data and associated metadata. We provide a case study of hyperactive curation of video data from the Play and Learning Across a Year (PLAY) project, where dozens of researchers developed a common protocol to collect, annotate, and actively curate video data of infants and mothers during natural activity in their homes at research sites across North America. PLAY relies on scalable standardized workflows to facilitate collaborative research, assure data quality, and prepare the corpus for sharing and reuse throughout the entire research process.</p>","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"10 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8443153/pdf/nihms-1732588.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39444475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-18DOI: 10.7191/jeslib.2020.1196
R. Raboin
Key themes in Dickens’ novel, transformation and resurrection, darkness and light, and social justice are firmly connected to the work being done in data. Data librarians can make a difference in times like these: resurrecting data, transforming how students, researchers, or the public think about and use data; unearthing and bringing to light historical data that will give context and meaning to an issue; and that accessible data can help address, and perhaps solve, social justice issues.
{"title":"Charles Dickens’ A Tale of Two Cities and Data Librarians: Connections that Resonate","authors":"R. Raboin","doi":"10.7191/jeslib.2020.1196","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1196","url":null,"abstract":"Key themes in Dickens’ novel, transformation and resurrection, darkness and light, and social justice are firmly connected to the work being done in data. Data librarians can make a difference in times like these: resurrecting data, transforming how students, researchers, or the public think about and use data; unearthing and bringing to light historical data that will give context and meaning to an issue; and that accessible data can help address, and perhaps solve, social justice issues.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46543771","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}
Pub Date : 2020-10-09DOI: 10.7191/jeslib.2020.1185
Kendall Roark
Objective: This eScience in Action article describes the collaborative development process and outputs for a qualitative data curation curriculum initiative led by a library faculty (research data specialist) at an R1 research university. Methods: The collaborative curriculum development activities described in this article took place between 2015-2020 and included 1) a college-wide “call out” meeting with graduate methods instructors and additional one-on-one conversations, 2) a year-long training series for disciplinary faculty teaching graduate-level qualitative research methods courses, 3) guest lectures and co-curricular workshops, and 4) the development of a credit-bearing graduate-level course. Results: This practice-based article includes a reflection on the collaborative curriculum development process and impacts, including the development of networks between the Library and qualitative researchers across campus. The article provides a proof-of-concept example for developing relevant and trustworthy library data services for humanities and qualitative social-science researchers. Conclusions: Curriculum development activities focused predominately upon researcher-centered perspectives and identified needs. However, changes in institutional expectations for library faculty (i.e. requirement to teach credit-bearing courses) played a major role in how the curriculum was implemented, its impact and continued sustainability of outputs going forward.
目的:这篇eScience in Action文章描述了由一所R1研究型大学的图书馆教员(研究数据专家)领导的定性数据管理课程倡议的协作开发过程和产出。方法:本文中描述的合作课程开发活动在2015-2020年期间进行，包括1)与研究生方法导师进行全校范围的“召集”会议和额外的一对一对话，2)为学科教师教授研究生水平的定性研究方法课程进行为期一年的培训系列，3)客座讲座和课外研讨会，以及4)开发一门有学分的研究生课程。结果:这篇基于实践的文章包括对协作课程开发过程和影响的反思，包括图书馆和整个校园的定性研究人员之间网络的发展。本文提供了一个概念验证的例子，为人文科学和定性社会科学研究人员开发相关和可信的图书馆数据服务。结论:课程开发活动主要侧重于以研究人员为中心的观点和确定的需求。但是，机构对图书馆教员期望的变化(即要求教授有学分的课程)在课程如何执行、其影响和今后产出的持续可持续性方面发挥了主要作用。
{"title":"Data Management and Curation for Qualitative Research: Collaborative Curriculum Development and Implementation","authors":"Kendall Roark","doi":"10.7191/jeslib.2020.1185","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1185","url":null,"abstract":"Objective: This eScience in Action article describes the collaborative development process and outputs for a qualitative data curation curriculum initiative led by a library faculty (research data specialist) at an R1 research university. Methods: The collaborative curriculum development activities described in this article took place between 2015-2020 and included 1) a college-wide “call out” meeting with graduate methods instructors and additional one-on-one conversations, 2) a year-long training series for disciplinary faculty teaching graduate-level qualitative research methods courses, 3) guest lectures and co-curricular workshops, and 4) the development of a credit-bearing graduate-level course. Results: This practice-based article includes a reflection on the collaborative curriculum development process and impacts, including the development of networks between the Library and qualitative researchers across campus. The article provides a proof-of-concept example for developing relevant and trustworthy library data services for humanities and qualitative social-science researchers. Conclusions: Curriculum development activities focused predominately upon researcher-centered perspectives and identified needs. However, changes in institutional expectations for library faculty (i.e. requirement to teach credit-bearing courses) played a major role in how the curriculum was implemented, its impact and continued sustainability of outputs going forward.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46685638","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}
Researchers are faced with unprecedented challenges due to the size and complexity of data, and libraries are stepping in to help by providing guidance on research data management primarily to graduate students and faculty. Currently, many universities are encouraging an undergraduate research experience where students engage in research projects in the classroom and in research labs, yet research data management is often not included as part of these opportunities. At UW-Madison, we piloted researchERS (Emerging Research Scholars), a program for undergraduates from all disciplines to learn data management skills. Focusing on core concepts as well as data ethics, reproducibility, and research workflows, the format of the program included seven evening workshops, two networking events, and one field trip. Each workshop invited campus and community speakers relevant to the workshop’s theme as a way to introduce the students to the network of available resources and data expertise and provided food for attendees. The workshops also built in customized activities to show students how to incorporate best practices into their work. Local businesses provided a tour of their facilities as well as a talk on how they leverage data. This paper will describe this program as well as the benefits and drawbacks of tailoring a research data management program toward undergraduates.
{"title":"Dinner and Data Management: Engaging undergraduates in research data management topics outside of the curriculum","authors":"Cameron Cook, Tobin Magle, Heather Shimon, Trisha Adamus","doi":"10.7191/jeslib.2020.1176","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1176","url":null,"abstract":"Researchers are faced with unprecedented challenges due to the size and complexity of data, and libraries are stepping in to help by providing guidance on research data management primarily to graduate students and faculty. Currently, many universities are encouraging an undergraduate research experience where students engage in research projects in the classroom and in research labs, yet research data management is often not included as part of these opportunities. At UW-Madison, we piloted researchERS (Emerging Research Scholars), a program for undergraduates from all disciplines to learn data management skills. Focusing on core concepts as well as data ethics, reproducibility, and research workflows, the format of the program included seven evening workshops, two networking events, and one field trip. Each workshop invited campus and community speakers relevant to the workshop’s theme as a way to introduce the students to the network of available resources and data expertise and provided food for attendees. The workshops also built in customized activities to show students how to incorporate best practices into their work. Local businesses provided a tour of their facilities as well as a talk on how they leverage data. This paper will describe this program as well as the benefits and drawbacks of tailoring a research data management program toward undergraduates.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46368930","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}
Pub Date : 2020-09-09DOI: 10.7191/jeslib.2020.1186
Elizabeth Coburn, L. Johnston
Objective: Data curation is becoming widely accepted as a necessary component of data sharing. Yet, as there are so many different types of data with various curation needs, the Data Curation Network (DCN) project anticipated that a collaborative approach to data curation across a network of repositories would expand what any single institution might offer alone. Now, halfway through a three-year implementation phase, we’re testing our assumptions using one year of data from the DCN. Methods: Ten institutions participated in the implementation phase of a shared staffing model for curating research data. Starting on January 1, 2019, for 12 months we tracked the number, file types, and disciplines represented in data sets submitted to the DCN. Participating curators were matched to data sets based on their self-reported curation expertise. Aspects such as curation time, level of satisfaction with the assignment, and lack of appropriate expertise in the network were tracked and analyzed. Results: Seventy-four data sets were submitted to the DCN in year one. Seventy-one of them were successfully curated by DCN curators. Each curation assignment takes 2.4 hours on average, and data sets take a median of three days to pass through the network. By analyzing the domain and file types of first- year submissions, we find that our coverage is well represented across domains and that our capacity is higher than the demand, but we also observed that the higher volume of data containing software code relied on certain curator expertise more often than others, creating potential unbalance. Conclusions: The data from year one of the DCN pilot have verified key assumptions about our collaborative approach to data curation, and these results have raised additional questions about capacity, equitable use of network resources, and sustained growth that we hope to answer by the end of this implementation phase.
{"title":"Testing Our Assumptions: Preliminary Results from the Data Curation Network","authors":"Elizabeth Coburn, L. Johnston","doi":"10.7191/jeslib.2020.1186","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1186","url":null,"abstract":"Objective: Data curation is becoming widely accepted as a necessary component of data sharing. Yet, as there are so many different types of data with various curation needs, the Data Curation Network (DCN) project anticipated that a collaborative approach to data curation across a network of repositories would expand what any single institution might offer alone. Now, halfway through a three-year implementation phase, we’re testing our assumptions using one year of data from the DCN. Methods: Ten institutions participated in the implementation phase of a shared staffing model for curating research data. Starting on January 1, 2019, for 12 months we tracked the number, file types, and disciplines represented in data sets submitted to the DCN. Participating curators were matched to data sets based on their self-reported curation expertise. Aspects such as curation time, level of satisfaction with the assignment, and lack of appropriate expertise in the network were tracked and analyzed. Results: Seventy-four data sets were submitted to the DCN in year one. Seventy-one of them were successfully curated by DCN curators. Each curation assignment takes 2.4 hours on average, and data sets take a median of three days to pass through the network. By analyzing the domain and file types of first- year submissions, we find that our coverage is well represented across domains and that our capacity is higher than the demand, but we also observed that the higher volume of data containing software code relied on certain curator expertise more often than others, creating potential unbalance. Conclusions: The data from year one of the DCN pilot have verified key assumptions about our collaborative approach to data curation, and these results have raised additional questions about capacity, equitable use of network resources, and sustained growth that we hope to answer by the end of this implementation phase.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41623171","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}
Pub Date : 2020-09-09DOI: 10.7191/jeslib.2020.1184
Sarah C. Williams
Objectives: This small-scale study explores the current state of connections between open data and open access (OA) articles in the life sciences. Methods: This study involved 44 openly available life sciences datasets from the Illinois Data Bank that had 45 related research articles. For each article, I gathered the OA status of the journal and the article on the publisher website and checked whether the article was openly available via Unpaywall and Research Gate. I also examined how and where the open data was included in the HTML and PDF versions of the related articles. Results: Of the 45 articles studied, less than half were published in Gold/Full OA journals, and while the remaining articles were published in Gold/Hybrid journals, none of them were OA. This study found that OA articles pointed to the Illinois Data Bank datasets similarly to all of the related articles, most commonly with a data availability statement containing a DOI. Conclusions: The findings indicate that Gold OA in hybrid journals does not appear to be a popular option, even for articles connected to open data, and this study emphasizes the importance of data repositories providing DOIs, since the related articles frequently used DOIs to point to the Illinois Data Bank datasets. This study also revealed concerns about free (not licensed OA) access to articles on publisher websites, which will be a significant topic for future research.
目的:这项小规模研究探讨了生命科学中开放数据和开放获取(OA)文章之间联系的现状。方法:本研究涉及来自伊利诺伊州数据库的44个公开获取的生命科学数据集，其中包含45篇相关研究文章。对于每一篇文章，我收集了该期刊和该文章在出版商网站上的开放获取状态，并检查该文章是否可以通过Unpaywall和Research Gate公开获取。我还研究了在相关文章的HTML和PDF版本中如何以及在何处包含开放数据。结果:在研究的45篇文章中，不到一半的文章发表在Gold/Full OA期刊上，而其余的文章发表在Gold/Hybrid期刊上，没有一篇是OA。该研究发现，OA文章指向Illinois Data Bank数据集的方式与所有相关文章相似，最常见的是带有包含DOI的数据可用性声明。结论:研究结果表明，混合期刊中的黄金OA似乎不是一个受欢迎的选择，即使是与开放数据相关的文章，本研究强调了提供doi的数据存储库的重要性，因为相关文章经常使用doi指向伊利诺斯数据银行数据集。这项研究还揭示了人们对出版商网站上文章的免费(非授权开放获取)访问的担忧，这将是未来研究的一个重要主题。
{"title":"Open Data and Open Access Articles: Exploring Connections in the Life Sciences","authors":"Sarah C. Williams","doi":"10.7191/jeslib.2020.1184","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1184","url":null,"abstract":"Objectives: This small-scale study explores the current state of connections between open data and open access (OA) articles in the life sciences. Methods: This study involved 44 openly available life sciences datasets from the Illinois Data Bank that had 45 related research articles. For each article, I gathered the OA status of the journal and the article on the publisher website and checked whether the article was openly available via Unpaywall and Research Gate. I also examined how and where the open data was included in the HTML and PDF versions of the related articles. Results: Of the 45 articles studied, less than half were published in Gold/Full OA journals, and while the remaining articles were published in Gold/Hybrid journals, none of them were OA. This study found that OA articles pointed to the Illinois Data Bank datasets similarly to all of the related articles, most commonly with a data availability statement containing a DOI. Conclusions: The findings indicate that Gold OA in hybrid journals does not appear to be a popular option, even for articles connected to open data, and this study emphasizes the importance of data repositories providing DOIs, since the related articles frequently used DOIs to point to the Illinois Data Bank datasets. This study also revealed concerns about free (not licensed OA) access to articles on publisher websites, which will be a significant topic for future research.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44417696","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}
Pub Date : 2020-05-11DOI: 10.7191/jeslib.2020.1183
M. Henderson
There are many courses available to teach research data management to librarians and researchers. While these courses can help with technical skills, like programming or statistics, and practical knowledge of data life cycles or data sharing policies, there are “soft skills” and non-technical skills that are needed to successfully start and run data services. While there are many important characteristics of a good data librarian, reference skills, relationship building, collaboration, listening, and facilitation are some of the most important. Giving consideration to these skills will help any data librarian with their multifaceted job.
{"title":"Why You Need Soft and Non-Technical Skills for Successful Data Librarianship","authors":"M. Henderson","doi":"10.7191/jeslib.2020.1183","DOIUrl":"https://doi.org/10.7191/jeslib.2020.1183","url":null,"abstract":"There are many courses available to teach research data management to librarians and researchers. While these courses can help with technical skills, like programming or statistics, and practical knowledge of data life cycles or data sharing policies, there are “soft skills” and non-technical skills that are needed to successfully start and run data services. While there are many important characteristics of a good data librarian, reference skills, relationship building, collaboration, listening, and facilitation are some of the most important. Giving consideration to these skills will help any data librarian with their multifaceted job.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"9 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45277684","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}
Pub Date : 2020-01-08DOI: 10.7191/jeslib.2019.1182
Tina Griffin, Rebekah Kati, A. Krzton, Lora C. Leligdon
{"title":"Special Issue: 2019 Research Data Access and Preservation Summit","authors":"Tina Griffin, Rebekah Kati, A. Krzton, Lora C. Leligdon","doi":"10.7191/jeslib.2019.1182","DOIUrl":"https://doi.org/10.7191/jeslib.2019.1182","url":null,"abstract":"","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"8 1","pages":"11"},"PeriodicalIF":0.0,"publicationDate":"2020-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45942517","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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