Pub Date : 2019-10-22DOI: 10.7191/JESLIB.2019.1159
Kelly A. Johnson, V. Steeves
Objective : This paper aims to inform on opportunities for librarians to assist faculty with research data management by examining practices and attitudes among life sciences faculty at a tier one research university. Methods : The authors issued a survey to estimate actual and perceived research data management needs of New York University (NYU) life sciences faculty in order to understand how the library could best contribute to the research life cycle. Results : Survey responses indicate that over half of the respondents were aware of publisher and funder mandates, and most are willing to share their data, but many indicated they do not utilize data repositories. Respondents were largely unaware of data services available through the library, but the majority were open to considering such services. Survey results largely mimic those of similar studies, in that storing data (and the subsequent ability to share it) is the most easily recognized barrier to sound data management practices. Conclusions : At NYU, as with other institutions, the library is not immediately recognized as a valuable partner in managing research output. This study suggests that faculty are largely unaware of, but are open to, existent library services, indicating that immediate outreach efforts should be aimed at promoting them.
{"title":"Research Data Management Among Life Sciences Faculty: Implications for Library Service","authors":"Kelly A. Johnson, V. Steeves","doi":"10.7191/JESLIB.2019.1159","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1159","url":null,"abstract":"Objective : This paper aims to inform on opportunities for librarians to assist faculty with research data management by examining practices and attitudes among life sciences faculty at a tier one research university. Methods : The authors issued a survey to estimate actual and perceived research data management needs of New York University (NYU) life sciences faculty in order to understand how the library could best contribute to the research life cycle. Results : Survey responses indicate that over half of the respondents were aware of publisher and funder mandates, and most are willing to share their data, but many indicated they do not utilize data repositories. Respondents were largely unaware of data services available through the library, but the majority were open to considering such services. Survey results largely mimic those of similar studies, in that storing data (and the subsequent ability to share it) is the most easily recognized barrier to sound data management practices. Conclusions : At NYU, as with other institutions, the library is not immediately recognized as a valuable partner in managing research output. This study suggests that faculty are largely unaware of, but are open to, existent library services, indicating that immediate outreach efforts should be aimed at promoting them.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42737918","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 : 2019-10-22DOI: 10.7191/jeslib.2019.1179
R. Raboin
{"title":"Baseball and Research Data Management (RDM) Planning: It’s All About Depth and Data","authors":"R. Raboin","doi":"10.7191/jeslib.2019.1179","DOIUrl":"https://doi.org/10.7191/jeslib.2019.1179","url":null,"abstract":"","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42073078","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 : 2019-07-31DOI: 10.7191/JESLIB.2019.1162
P. Coombs, Christine Malinowski, A. Nurnberger
Objective: To evaluate library workshops on their coverage of data management topics. Methods: We used a modified version of Sapp Nelson’s Competency Matrix for Data Management Skills, a matrix of learning goals organized by data management competency and complexity level, against which we compared our educational materials: slide decks and worksheets. We examined each of the educational materials against the 333 learning objectives in our modified version of the Matrix to determine which of the learning objectives applied. Conclusions: We found it necessary to change certain elements of the Matrix’s structure to increase its clarity and functionality: reinterpreting the “behaviors,” shifting the organization from the three domains of Bloom’s taxonomy to increasing complexity solely within the cognitive domain, as well as creating a comprehensive identifier schema. We appreciated the Matrix for its specificity of learning objectives, its organizational structure, the comprehensive range of competencies included, and its ease of use. On the whole, the Matrix is a useful instrument for the assessment of data management programming. Correspondence: Philip Espinola Coombs: pcoombs@bu.edu
{"title":"Skills, Standards, and Sapp Nelson's Matrix: Evaluating Research Data Management Workshop Offerings","authors":"P. Coombs, Christine Malinowski, A. Nurnberger","doi":"10.7191/JESLIB.2019.1162","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1162","url":null,"abstract":"Objective: To evaluate library workshops on their coverage of data management topics. Methods: We used a modified version of Sapp Nelson’s Competency Matrix for Data Management Skills, a matrix of learning goals organized by data management competency and complexity level, against which we compared our educational materials: slide decks and worksheets. We examined each of the educational materials against the 333 learning objectives in our modified version of the Matrix to determine which of the learning objectives applied. Conclusions: We found it necessary to change certain elements of the Matrix’s structure to increase its clarity and functionality: reinterpreting the “behaviors,” shifting the organization from the three domains of Bloom’s taxonomy to increasing complexity solely within the cognitive domain, as well as creating a comprehensive identifier schema. We appreciated the Matrix for its specificity of learning objectives, its organizational structure, the comprehensive range of competencies included, and its ease of use. On the whole, the Matrix is a useful instrument for the assessment of data management programming. Correspondence: Philip Espinola Coombs: pcoombs@bu.edu","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43571900","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 : 2019-07-29DOI: 10.7191/JESLIB.2019.1161
Thea Atwood, Andrew Creamer, Joshua Dull, J. Goldman, Kristin Lee, Lora C. Leligdon, Sarah K Oelker
In 2017 a group of academic library and information technology staff from institutions across New England piloted a process of joining The Carpentries, an organization developed to train researchers in essential computing skills and practices for automating and improving their handling of data, as a consortium. The New England Software Carpentry Library Consortium (NESCLiC) shared a gold-level tier membership to become a Carpentries member organization. NESCLiC members attended a Software Carpentry workshop together and then participated in instructor training as a cohort, collaborating on learning the material, practicing, and beginning to host and teach workshops as a group. This article describes both the successes and challenges of forming this new consortium, suggests good practices for those who might wish to form similar collaborations, and discusses the future of this program and other efforts to help researchers improve their computing and data handling skills. Correspondence: Sarah K. Oelker: soelker@mtholyoke.edu
{"title":"Joining Together to Build More: The New England Software Carpentry Library Consortium","authors":"Thea Atwood, Andrew Creamer, Joshua Dull, J. Goldman, Kristin Lee, Lora C. Leligdon, Sarah K Oelker","doi":"10.7191/JESLIB.2019.1161","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1161","url":null,"abstract":"In 2017 a group of academic library and information technology staff from institutions across New England piloted a process of joining The Carpentries, an organization developed to train researchers in essential computing skills and practices for automating and improving their handling of data, as a consortium. The New England Software Carpentry Library Consortium (NESCLiC) shared a gold-level tier membership to become a Carpentries member organization. NESCLiC members attended a Software Carpentry workshop together and then participated in instructor training as a cohort, collaborating on learning the material, practicing, and beginning to host and teach workshops as a group. This article describes both the successes and challenges of forming this new consortium, suggests good practices for those who might wish to form similar collaborations, and discusses the future of this program and other efforts to help researchers improve their computing and data handling skills. Correspondence: Sarah K. Oelker: soelker@mtholyoke.edu","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43176365","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 : 2019-03-28DOI: 10.7191/JESLIB.2019.1142
S. Van Tuyl
Objectives: The objective of this study is to evaluate the quality and usability of supplementary data files deposited, between 1971 and 2015, to our university institutional repository. Understanding the extent to which content historically deposited in digital repositories is usable by today’s researchers can help inform digital preservation and documentation practices for researchers today. Methods: I identified all graduate-level theses and dissertations (GTDs) in the institutional repository with multiple files as a first pass at identifying documents that included supplementary data files. These GTDs were then individually examined, removing supplementary files that were artifacts of either the upload or digitization process. The remaining “true” supplementary files were then individually opened and evaluated following elements of the DATA rubric of Van Tuyl and Whitmire (2016). Results: Supplementary files were discovered in the repository dating back to 1971 in 116 GTD submissions totaling more than 25,000 files. Most GTD submissions included fewer than 30 files, though some submissions included thousands of individual data files. The most common file types submitted included imagery, tabular data, and databases, with a very large number of unknown file types. Overall, levels of documentation were poor while actionability of datasets was generally middling. Conclusions: The results presented in this study suggest that legacy data submitted to our institutional repository with GTDs is generally in poor shape with respect to Transparency and somewhat less so for Actionability. It is clear from this study and others that researchers have a long road ahead when it comes to sharing data in a way that makes it potentially useable by other researchers. Correspondence: Steve.Van Tuyl: steve.vantuyl@oregonstate.edu
{"title":"What’s in the Box? Assessing the potential usability of four decades of thesis and dissertation supplementary files","authors":"S. Van Tuyl","doi":"10.7191/JESLIB.2019.1142","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1142","url":null,"abstract":"Objectives: The objective of this study is to evaluate the quality and usability of supplementary data files deposited, between 1971 and 2015, to our university institutional repository. Understanding the extent to which content historically deposited in digital repositories is usable by today’s researchers can help inform digital preservation and documentation practices for researchers today. Methods: I identified all graduate-level theses and dissertations (GTDs) in the institutional repository with multiple files as a first pass at identifying documents that included supplementary data files. These GTDs were then individually examined, removing supplementary files that were artifacts of either the upload or digitization process. The remaining “true” supplementary files were then individually opened and evaluated following elements of the DATA rubric of Van Tuyl and Whitmire (2016). Results: Supplementary files were discovered in the repository dating back to 1971 in 116 GTD submissions totaling more than 25,000 files. Most GTD submissions included fewer than 30 files, though some submissions included thousands of individual data files. The most common file types submitted included imagery, tabular data, and databases, with a very large number of unknown file types. Overall, levels of documentation were poor while actionability of datasets was generally middling. Conclusions: The results presented in this study suggest that legacy data submitted to our institutional repository with GTDs is generally in poor shape with respect to Transparency and somewhat less so for Actionability. It is clear from this study and others that researchers have a long road ahead when it comes to sharing data in a way that makes it potentially useable by other researchers. Correspondence: Steve.Van Tuyl: steve.vantuyl@oregonstate.edu","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48147873","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 : 2019-03-21DOI: 10.7191/JESLIB.2019.1146
Kathryn Vela, Nancy Shin
Objective : Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus. Methods : A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv. This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services. Results : Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup. Conclusions : This needs assessment will direct how RDM services are implemented on the WSU Spokane campus by the Spokane Academic Library (SAL). These services will influence both research data quality and integrity through improved data management practices. The data reveal some interesting inconsistencies in respondent behaviors and attitudes around data sharing. Almost all of the respondents reported having funding from federal sources like the NIH, yet only 38% indicated that they plan to share their data at the conclusion of their research project. This seems to agree with data collected from other RDM needs assessments; Buys and Shaw (2015) found that 34% of the researchers from the school of medicine on their campus share or plan to share their data, and approximately 30% of the medical sciences researchers surveyed by Akers and Doty (2013) planned to share their data. Additionally, when asked how much they agree that it is important to openly share their data with others, 65% of the respondents indicated that they somewhat or strongly agree, which is almost double the percentage of respondents who actually intend to make their data publicly available.
{"title":"Establishing a Research Data Management Service on a Health Sciences Campus","authors":"Kathryn Vela, Nancy Shin","doi":"10.7191/JESLIB.2019.1146","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1146","url":null,"abstract":"Objective : Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus. Methods : A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv. This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services. Results : Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup. Conclusions : This needs assessment will direct how RDM services are implemented on the WSU Spokane campus by the Spokane Academic Library (SAL). These services will influence both research data quality and integrity through improved data management practices. The data reveal some interesting inconsistencies in respondent behaviors and attitudes around data sharing. Almost all of the respondents reported having funding from federal sources like the NIH, yet only 38% indicated that they plan to share their data at the conclusion of their research project. This seems to agree with data collected from other RDM needs assessments; Buys and Shaw (2015) found that 34% of the researchers from the school of medicine on their campus share or plan to share their data, and approximately 30% of the medical sciences researchers surveyed by Akers and Doty (2013) planned to share their data. Additionally, when asked how much they agree that it is important to openly share their data with others, 65% of the respondents indicated that they somewhat or strongly agree, which is almost double the percentage of respondents who actually intend to make their data publicly available.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44607501","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 : 2019-03-18DOI: 10.7191/JESLIB.2019.1132
C. Wiley, Margaret H Burnette
Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of National Institutes of Health (NIH) funded research projects. Specifically, this study seeks to answer the following questions: 1. What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated? 2. To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors? 3. What aspects of data management present the greatest challenges and frustrations? 4. To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing? 5. To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas? Correspondence: Margaret H. Burnett: phburn@illinois.edu
目的:本研究探讨了在美国国立卫生研究院(NIH)资助的研究项目背景下，生物工程和生物医学研究人员的数据管理知识、态度和实践。具体来说，本研究试图回答以下问题:1。伊利诺伊校区生物医学和生物工程研究的本质是什么?产生了哪些类型的数据?2. 生物医学和生物工程研究人员在多大程度上意识到数据管理的最佳实践?实际的数据管理行为是什么?3.数据管理的哪些方面面临着最大的挑战和挫折?4. 生物医学和生物工程研究人员在多大程度上意识到数据共享机会和数据存储库?他们对数据共享的态度是什么?5. 研究人员在多大程度上意识到校园服务和对数据管理规划、数据共享和数据存储的支持，以及对这些领域教学的兴趣程度?通信:Margaret H. Burnett: phburn@illinois.edu
{"title":"Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty","authors":"C. Wiley, Margaret H Burnette","doi":"10.7191/JESLIB.2019.1132","DOIUrl":"https://doi.org/10.7191/JESLIB.2019.1132","url":null,"abstract":"Objectives: This study explores data management knowledge, attitudes, and practices of bioengineering and biomedical researchers in the context of National Institutes of Health (NIH) funded research projects. Specifically, this study seeks to answer the following questions: 1. What is the nature of biomedical and bioengineering research on the Illinois campus and what kinds of data are being generated? 2. To what degree are biomedical and bioengineering researchers aware of best practices for data management and what are the actual data management behaviors? 3. What aspects of data management present the greatest challenges and frustrations? 4. To what degree are biomedical and bioengineering researchers aware of data sharing opportunities and data repositories, and what are their attitudes towards data sharing? 5. To what degree are researchers aware of campus services and support for data management planning, data sharing, and data deposit, and what is the level of interest in instruction in these areas? Correspondence: Margaret H. Burnett: phburn@illinois.edu","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41798917","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 : 2019-01-01Epub Date: 2019-07-29DOI: 10.7191/jeslib.2019.1160
Jessica Van Der Volgen, Shirley Zhao
Background: In August 2017 the National Network of Libraries of Medicine Training Office (NTO) was awarded an administrative supplement from the National Library of Medicine (NLM) to create training for librarians in biomedical and health research data management (RDM). The primary goal of the training was to enable information professionals to initiate or enhance RDM at their institutions.
Case presentation: An eight-week online course was developed to address key concepts in RDM. Each module was organized around measurable learning objectives using existing subject resources, such as readings, tutorials, and videos. Within each module, an expert in the field co-facilitated relevant discussions, created and graded a practical assignment, and answered questions. Thirty-eight participants were selected for this initial cohort. Mentors were assigned to each participant for guidance in completing a required project action plan to further their RDM goals at their institution. The course was evaluated through pre- and post-tests and an online questionnaire.
Results: Thirty participants successfully completed the online course work and project, and gathered at the National Institutes of Health for a Capstone Summit. Students demonstrated improved knowledge of RDM concepts between the pre- and post-tests. Most students also self-reported increased skill and confidence. Practical assignments with individual feedback from experienced data librarians were the most valued aspect of the course. Time to complete each module was underestimated.
Conclusions: The initial offering of this training program improved the RDM skills and knowledge of participants and enabled students to add or enhance services at their institutions. Further investigations are necessary to determine the longer-term impact on the individuals and their libraries. While many of the participants will need additional training to become part of the data-ready workforce of health information professionals, completing this training is an important step in their professional development.
{"title":"Building A National Research Data Management Course for Health Information Professionals.","authors":"Jessica Van Der Volgen, Shirley Zhao","doi":"10.7191/jeslib.2019.1160","DOIUrl":"10.7191/jeslib.2019.1160","url":null,"abstract":"<p><strong>Background: </strong>In August 2017 the National Network of Libraries of Medicine Training Office (NTO) was awarded an administrative supplement from the National Library of Medicine (NLM) to create training for librarians in biomedical and health research data management (RDM). The primary goal of the training was to enable information professionals to initiate or enhance RDM at their institutions.</p><p><strong>Case presentation: </strong>An eight-week online course was developed to address key concepts in RDM. Each module was organized around measurable learning objectives using existing subject resources, such as readings, tutorials, and videos. Within each module, an expert in the field co-facilitated relevant discussions, created and graded a practical assignment, and answered questions. Thirty-eight participants were selected for this initial cohort. Mentors were assigned to each participant for guidance in completing a required project action plan to further their RDM goals at their institution. The course was evaluated through pre- and post-tests and an online questionnaire.</p><p><strong>Results: </strong>Thirty participants successfully completed the online course work and project, and gathered at the National Institutes of Health for a Capstone Summit. Students demonstrated improved knowledge of RDM concepts between the pre- and post-tests. Most students also self-reported increased skill and confidence. Practical assignments with individual feedback from experienced data librarians were the most valued aspect of the course. Time to complete each module was underestimated.</p><p><strong>Conclusions: </strong>The initial offering of this training program improved the RDM skills and knowledge of participants and enabled students to add or enhance services at their institutions. Further investigations are necessary to determine the longer-term impact on the individuals and their libraries. While many of the participants will need additional training to become part of the data-ready workforce of health information professionals, completing this training is an important step in their professional development.</p>","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11349318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44287460","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 : 2018-12-21DOI: 10.7191/JESLIB.2018.1155
Sara Mannheimer
Data Management Plans (DMPs) are often required for grant applications. But do strong DMPs lead to better data management and sharing practices? Several recent research projects in the Library and Information Science field have investigated data management planning and practice through DMP content analysis and data-management-related interviews. However, research hasn’t yet shown how DMPs ultimately affect data management and data sharing practices during grant-funded research. The research described in this article contributes to the existing literature by examining the impact of DMPs on grant awards and on Principal Investigators’ (PIs) data management and sharing practices. The results of this research suggest the following key takeaways: (1) Most PIs practice internal data management in order to prevent data loss, to facilitate sharing within the research team, and to seamlessly continue their research during personnel turnover; (2) PIs still have room to grow in understanding specialized concepts such as metadata and policies for use and reuse; (3) PIs may need guidance on practices that facilitate FAIR data, such as using metadata standards, assigning licenses to their data, and publishing in data repositories. Ultimately, the results of this research can inform academic library services and support stronger, more actionable DMPs. Correspondence: Sara Mannheimer: sara.mannheimer@montana.edu
{"title":"Toward a Better Data Management Plan: The Impact of DMPs on Grant Funded Research Practices","authors":"Sara Mannheimer","doi":"10.7191/JESLIB.2018.1155","DOIUrl":"https://doi.org/10.7191/JESLIB.2018.1155","url":null,"abstract":"Data Management Plans (DMPs) are often required for grant applications. But do strong DMPs lead to better data management and sharing practices? Several recent research projects in the Library and Information Science field have investigated data management planning and practice through DMP content analysis and data-management-related interviews. However, research hasn’t yet shown how DMPs ultimately affect data management and data sharing practices during grant-funded research. The research described in this article contributes to the existing literature by examining the impact of DMPs on grant awards and on Principal Investigators’ (PIs) data management and sharing practices. The results of this research suggest the following key takeaways: (1) Most PIs practice internal data management in order to prevent data loss, to facilitate sharing within the research team, and to seamlessly continue their research during personnel turnover; (2) PIs still have room to grow in understanding specialized concepts such as metadata and policies for use and reuse; (3) PIs may need guidance on practices that facilitate FAIR data, such as using metadata standards, assigning licenses to their data, and publishing in data repositories. Ultimately, the results of this research can inform academic library services and support stronger, more actionable DMPs. Correspondence: Sara Mannheimer: sara.mannheimer@montana.edu","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45776005","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 : 2018-12-20DOI: 10.7191/JESLIB.2018.1152
P. Pascuzzi, Megan Sapp Nelson
Objective : This paper describes a project to revise an existing research data management (RDM) course to include instruction in computer skills with robust data science tools. Setting : A Carnegie R1 university. Brief Description : Graduate student researchers need training in the basic concepts of RDM. However, they generally lack experience with robust data science tools to implement these concepts holistically. Two library instructors fundamentally redesigned an existing research RDM course to include instruction with such tools. The course was divided into lecture and lab sections to facilitate the increased instructional burden. Learning objectives and assessments were designed at a higher order to allow students to demonstrate that they not only understood course concepts but could use their computer skills to implement these concepts. Results : Twelve students completed the first iteration of the course. Feedback from these students was very positive, and they appreciated the combination of theoretical concepts, computer skills and hands-on activities. Based on student feedback, future iterations of the course will include more “flipped” content including video lectures and interactive computer tutorials to maximize active learning time in both lecture and lab.
{"title":"Integrating Data Science Tools into a Graduate Level Data Management Course","authors":"P. Pascuzzi, Megan Sapp Nelson","doi":"10.7191/JESLIB.2018.1152","DOIUrl":"https://doi.org/10.7191/JESLIB.2018.1152","url":null,"abstract":"Objective : This paper describes a project to revise an existing research data management (RDM) course to include instruction in computer skills with robust data science tools. Setting : A Carnegie R1 university. Brief Description : Graduate student researchers need training in the basic concepts of RDM. However, they generally lack experience with robust data science tools to implement these concepts holistically. Two library instructors fundamentally redesigned an existing research RDM course to include instruction with such tools. The course was divided into lecture and lab sections to facilitate the increased instructional burden. Learning objectives and assessments were designed at a higher order to allow students to demonstrate that they not only understood course concepts but could use their computer skills to implement these concepts. Results : Twelve students completed the first iteration of the course. Feedback from these students was very positive, and they appreciated the combination of theoretical concepts, computer skills and hands-on activities. Based on student feedback, future iterations of the course will include more “flipped” content including video lectures and interactive computer tutorials to maximize active learning time in both lecture and lab.","PeriodicalId":90214,"journal":{"name":"Journal of escience librarianship","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41678256","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：