Category: Data Curation, Open Data, and Research Data Management

"Data Management and Sharing in Neuroimaging: Practices and Perceptions of MRI Researchers"

John A. Borghi and Ana E. Van Gulick have published "Data Management and Sharing in Neuroimaging: Practices and Perceptions of MRI Researchers" in PLOS ONE.

Here's an excerpt:

Neuroimaging methods such as magnetic resonance imaging (MRI) involve complex data collection and analysis protocols, which necessitate the establishment of good research data management (RDM). Despite efforts within the field to address issues related to rigor and reproducibility, information about the RDM-related practices and perceptions of neuroimaging researchers remains largely anecdotal. To inform such efforts, we conducted an online survey of active MRI researchers that covered a range of RDM-related topics. Survey questions addressed the type(s) of data collected, tools used for data storage, organization, and analysis, and the degree to which practices are defined and standardized within a research group. Our results demonstrate that neuroimaging data is acquired in multifarious forms, transformed and analyzed using a wide variety of software tools, and that RDM practices and perceptions vary considerably both within and between research groups, with trainees reporting less consistency than faculty. Ratings of the maturity of RDM practices from ad-hoc to refined were relatively high during the data collection and analysis phases of a project and significantly lower during the data sharing phase. Perceptions of emerging practices including open access publishing and preregistration were largely positive, but demonstrated little adoption into current practice.

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"Health Sciences Libraries Advancing Collaborative Clinical Research Data Management in Universities"

Tania P. Bardyn et al. have published "Health Sciences Libraries Advancing Collaborative Clinical Research Data Management in Universities" in the Journal of eScience Librarianship.

Here's an excerpt:

Purpose: Medical libraries need to actively review their service models and explore partnerships with other campus entities to provide better-coordinated clinical research management services to faculty and researchers. TRAIL (Translational Research and Information Lab), a five-partner initiative at the University of Washington (UW), explores how best to leverage existing expertise and space to deliver clinical research data management (CRDM) services and emerging technology support to clinical researchers at UW and collaborating institutions in the Pacific Northwest.

Methods: The initiative offers 14 services and a technology-enhanced innovation lab located in the Health Sciences Library (HSL) to support the University of Washington clinical and research enterprise. Sharing of staff and resources merges library and non-library workflows, better coordinating data and innovation services to clinical researchers. Librarians have adopted new roles in CRDM, such as providing user support and training for UW's Research Electronic Data Capture (REDCap) instance.

Results: TRAIL staff are quickly adapting to changing workflows and shared services, including teaching classes on tools used to manage clinical research data. Researcher interest in TRAIL has sparked new collaborative initiatives and service offerings. Marketing and promotion will be important for raising researchers’ awareness of available services.

Conclusions: Medical librarians are developing new skills by supporting and teaching CRDM. Clinical and data librarians better understand the information needs of clinical and translational researchers by being involved in the earlier stages of the research cycle and identifying technologies that can improve healthcare outcomes. At health sciences libraries, leveraging existing resources and bringing services together is central to how university medical librarians will operate in the future.

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"Supporting the Proliferation of Data-Sharing Scholars in the Research Ecosystem"

Ali Krzton has published "Supporting the Proliferation of Data-Sharing Scholars in the Research Ecosystem" in the Journal of eScience Librarianship.

Here's an excerpt:

Librarians champion the value of openness in scholarship and have been powerful advocates for the sharing of research data. College and university administrators have recently joined in the push for data sharing due to funding mandates. However, the researchers who create and control the data usually determine whether and how data is shared, so it is worthwhile to look at what they are incentivized to do. The current scholarly publishing landscape plus the promotion and tenure process create a "prisoner’s dilemma" for researchers as they decide whether or not to share data, consistent with the observation that researchers in general are eager for others to share data but reluctant to do so themselves. If librarians encourage researchers to share data and promote openness without simultaneously addressing the academic incentive structure, those who are intrinsically motivated to share data will be selected against via the promotion and tenure process. This will cause those who are hostile to sharing to be disproportionately recruited into the senior ranks of academia. To mitigate the risk of this unintended consequence, librarians must advocate for a change in incentives alongside the call for greater openness. Highly-cited datasets must be given similar weight to highly-cited articles in promotion and tenure decisions in order for researchers to reap the rewards of their sharing. Librarians can help by facilitating data citation to track the impact of datasets and working to persuade higher administration of the value of rewarding data sharing in tenure and promotion.

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Want to Support Open Access? Volunteer for the Open Access Tracking Project

The Open Access Tracking Project (OATP) provides a constant stream of up-to-date information about open access issues in a primary feed and in a number of secondary feeds that focus on specialized OA subtopics. It offers the primary feed in a variety of distribution options, including email, Google+, HTML, RSS, Twitter, and others. It is an invaluable source of information for open access advocates, research data specialists, and scholarly communication specialists, and it provides important support for the open access movement as a whole.

Based at the Harvard Open Access Project, the OATP was launched by Peter Suber. Suber's SPARC Open Access Newsletter and his Free Online Scholarship Newsletter played an important part in getting the open access movement off the ground. The OATP continues the mission of those groundbreaking publications using the open source TagTeam software, which was developed for the OATP.

Launched with the help of grant funding, the OATP will enter a new an all-volunteer phase at the end of August 2018. To continue this crowd-sourced project, new volunteers are needed. You can help move the OA agenda forward by being one of them. This wiki page explains how you can join the team and start tagging.

By volunteering just a bit of time to the OATP, you can make a significant difference.

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"A Funder-Imposed Data Publication Requirement Seldom Inspired Data Sharing"

Jessica L. Couture et al. have published "A Funder-Imposed Data Publication Requirement Seldom Inspired Data Sharing" in PLOS ONE.

Here's an excerpt:

Growth of the open science movement has drawn significant attention to data sharing and availability across the scientific community. In this study, we tested the ability to recover data collected under a particular funder-imposed requirement of public availability. We assessed overall data recovery success, tested whether characteristics of the data or data creator were indicators of recovery success, and identified hurdles to data recovery. Overall the majority of data were not recovered (26% recovery of 315 data projects), a similar result to journal-driven efforts to recover data. Field of research was the most important indicator of recovery success, but neither home agency sector nor age of data were determinants of recovery. While we did not find a relationship between recovery of data and age of data, age did predict whether we could find contact information for the grantee. The main hurdles to data recovery included those associated with communication with the researcher; loss of contact with the data creator accounted for half (50%) of unrecoverable datasets, and unavailability of contact information accounted for 35% of unrecoverable datasets. Overall, our results suggest that funding agencies and journals face similar challenges to enforcement of data requirements. We advocate that funding agencies could improve the availability of the data they fund by dedicating more resources to enforcing compliance with data requirements, providing data-sharing tools and technical support to awardees, and administering stricter consequences for those who ignore data sharing preconditions./p>

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"Research Data Management Tools and Workflows: Experimental Work at the University of Porto"

Cristina Ribeiro et al. have published "Research Data Management Tools and Workflows: Experimental Work at the University of Porto" in IASSIST Quarterly.

Here's an excerpt:

We focus on data preparation, namely on dataset organization and metadata creation. For groups in the long tail, we propose Dendro, an open-source research data management platform, and explore automatic metadata creation with LabTablet, an electronic laboratory notebook. For groups demanding a domain-specific approach, our analysis has resulted in the development of models and applications to organize the data and support some of their use cases. Overall, we have adopted ontologies for metadata modeling, keeping in sight metadata dissemination as Linked Open Data.

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"Defining Data Librarianship: A Survey of Competencies, Skills, and Training"

Lisa Federer has published "Defining Data Librarianship: A Survey of Competencies, Skills, and Training" in the Journal of the Medical Library Association.

Here's an excerpt:

Respondents considered a broad range of skills and knowledge important to their work, especially “soft skills” and personal characteristics, like communication skills and the ability to develop relationships with researchers. Traditional library skills like cataloging and collection development were considered less important. A cluster analysis of the responses revealed two types of data librarians: data generalists, who tend to provide data services across a variety of fields, and subject specialists, who tend to provide more specialized services to a distinct discipline.

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"Managing Digital Research Objects in an Expanding Science Ecosystem: 2017 Conference Summary"

Joshua Borycz and Bonnie Carroll have published "Managing Digital Research Objects in an Expanding Science Ecosystem: 2017 Conference Summary" in Data Science Journal.

Here's an excerpt:

Digital research objects are packets of information that scientists can use to organize and store their data. There are currently many different methods in use for optimizing digital objects for research purposes. These methods have been applied to many scientific disciplines but differ in architecture and approach. The goals of this joint digital research object (DRO) conference were to discuss the challenge of characterizing DROs at scale in volume and over time and possible organizing principles that might connect current DRO architectures. One of the primary challenges concerns convincing scientists that these tools and practices will actually make the research process easier and more fruitful. This conference included work from CENDI, the National Federal STI Managers Group, the National Federation of Advanced Information Services (NFAIS), the Research Data Alliance (RDA), and the National Academy of Science (NAS).

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"A Conceptual Enterprise Framework for Managing Scientific Data Stewardship"

Ge Peng et al. have published "A Conceptual Enterprise Framework for Managing Scientific Data Stewardship" in the Data Science Journal.

Here's an excerpt:

Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. federal government directives and scientific organization guidelines have levied specific requirements, increasing the need for a more formal approach to ensuring that stewardship activities support compliance verification and reporting. However, many science data centers lack an integrated, systematic, and holistic framework to support such efforts. The current business- and process-oriented stewardship frameworks are too costly and lengthy for most data centers to implement. They often do not explicitly address the federal stewardship requirements and/or the uniqueness of geospatial data. This work proposes a data-centric conceptual enterprise framework for managing stewardship activities, based on the philosophy behind the Plan-Do-Check-Act (PDCA) cycle, a proven industrial concept. This framework, which includes the application of maturity assessment models, allows for quantitative evaluation of how organizations manage their stewardship activities and supports informed decision-making for continual improvement towards full compliance with federal, agency, and user requirements.

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University of California: "Re: Declaration of Rights and Principles to Transform Scholarly Communication"

The University of California's University Committee on Library and Scholarly Communication has released "Re: Declaration of Rights and Principles to Transform Scholarly Communication."

Here's an excerpt:

1. No copyright transfers. Our authors shall be allowed to retain copyright in their work and grant a Creative Commons Attribution license of their choosing.

2. No restrictions on preprints. Our authors shall have the right to submit for publication work they have previously made available as preprints.

3. No waivers of OA Policy. Publishers shall not require our authors to provide waivers of our Institutional OA Policy as a condition for publishing our work.

4. No delays to sharing. Publishers shall make work by our authors immediately available for harvest or via automatic deposit into our Institutional OA repository or another public archive.

5. No limitations on author reuse. Our authors shall have the right to reuse figures, tables, data, and text from their published work without permission or payment.

6. No impediments to rights reversion. Publishers shall provide a simple process for our authors to regain copyright in their previously published work.

7. No curtailment of copyright exceptions. Licenses shall not restrict, and should instead expressly protect, the rights of authors, institutions, and the public to reuse excerpts of published work consistent with legal exceptions and limitations on copyright such as fair use.

8. No barriers to data availability. Our authors shall have the right to make all of their data, figures, and other supporting materials from their published work publicly available.

9. No constraints on content mining. Publishers shall make licensed materials open, accessible, and machine-readable for text and data mining by our researchers, at no additional cost and under terms that allow retention and reuse of results.

10. No closed metadata. Publishers shall make bibliographic records, usage metrics, and citation data for our authors freely available, easy to parse, and machine-readable.

11. No free labor. Publishers shall provide our Institution with data on peer review and editorial contributions by our authors in support of journals, and such contributions shall be taken into account when determining the cost of our subscriptions or OA fees for our authors.

12. No long-term subscriptions. Publishers shall provide our Institution with plans and timelines for transitioning their subscription journals to OA.

13. No permanent paywalls. Our Institution shall receive perpetual access for previously licensed content and back files shall be made freely available once a journal transitions to OA.

14. No double payments. Publishers shall provide our Institution with data on hybrid OA payments from our authors and such payments shall reduce the cost of our subscriptions.

15. No hidden profits. Publishers shall use transparent pricing for the services they provide our authors when levying article processing charges and other fees associated with publishing.

16. No deals without OA offsets. Our Institution shall only enter into publishing agreements that include offsets for OA publishing by our authors.

17. No new paywalls for our work. Work by our authors shall be made OA on the publisher’s website as part of subscription terms for new journals.

18. No non-disclosure agreements. Publisher agreements with our Institution shall be transparent and shall not contain terms that prevent the sharing of their contents.

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"Managing Research Data: Graduate Student and Postdoctoral Researcher Perspectives"

Christie A. Wiley and Erin E. Kerby have published "Managing Research Data: Graduate Student and Postdoctoral Researcher Perspectives" in Issues in Science and Technology Librarianship.

Here's an excerpt:

The authors conducted six focus group semi-structured interviews consisting of graduate students and postdoctoral researchers within the College of Engineering at the University of Illinois Urbana-Champaign (UIUC) in order to understand their roles within research groups and their ability to manage research data. More specifically, participants were asked how they manage, organize, and describe data, as well as the challenges they face in these activities. This study revealed graduate students primarily discuss managing research data in terms of the software they use and that their focus is task specific. Additionally, the language and concepts librarians use in conversations about data management creates a barrier to understanding for graduate students. This study confirms that there is a significant disconnect between the faculty members who design and direct research projects and the graduate students and postdoctoral researchers that do the front-line work. This study helped identify that more data management engagement, interaction, and instruction within research groups is needed. Acknowledging this will allow librarians to develop more meaningful data management instruction and enhance the research data support services provided to faculty.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Open Science Support as a Portfolio of Services and Projects: From Awareness to Engagement"

Birgit Schmidt et al. have published "Open Science Support as a Portfolio of Services and Projects: From Awareness to Engagement" in Publications.

Here's an excerpt:

Together with many other universities worldwide, the University of Göttingen has aimed to unlock the full potential of networked digital scientific communication by strengthening open access as early as the late 1990s. Open science policies at the institutional level consequently followed and have been with us for over a decade. However, for several reasons, their adoption often is still far from complete when it comes to the practices of researchers or research groups. To improve this situation at our university, there is dedicated support at the infrastructural level: the university library collaborates with several campus units in developing and running services, activities and projects in support of open access and open science. This article outlines our main activity areas and aligns them with the overall rationale to reach higher uptake and acceptance of open science practice at the university. The mentioned examples of our activities highlight how we seek to advance open science along the needs and perspectives of diverse audiences and by running it as a multi-stakeholder endeavor. Therefore, our activities involve library colleagues with diverse backgrounds, faculty and early career researchers, research managers, as well as project and infrastructure staff. We conclude with a summary of achievements and challenges to be faced.

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Turning FAIR Data Into Reality: Interim Report from the European Commission Expert Group on FAIR Data

The European Commission Expert Group on FAIR Data has released Turning FAIR Data Into Reality: Interim Report from the European Commission Expert Group on FAIR Data.

Here's an excerpt:

The central chapters of the report focus on existing practice in certain fields to ascertain what can be learned from those research areas that have already standardised practices and developed international agreements and infrastructure to enable FAIR data sharing. These examples have helped to define models for FAIR data and the essential components of a FAIR data ecosystem. Naturally the main building blocks in the ecosystem are technology-based services, however the social aspects that drive the system and enable culture change are also addressed in sections of the report covering skills, metrics, rewards, investment and sustainability.

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"’Yeah, I Guess That’s Data’: Data Practices and Conceptions among Humanities Faculty"

portal: Libraries and the Academy has released an e-print of "'Yeah, I Guess That's Data': Data Practices and Conceptions among Humanities Faculty" by Jennifer L. Thoegersen.

Here's an excerpt:

Libraries are attempting to identify their role in providing data management services. However, humanities faculty’s conceptions of data and their data management practices are not well-known. This qualitative study explores the data management practices of humanities faculty at a four-year university and examines their perceptions of the term data.

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"Conceptualizing Data Curation Activities within Two Academic Libraries"

Sophia Lafferty-Hess et al. have self-archived "Conceptualizing Data Curation Activities within Two Academic Libraries."

Here's an excerpt:

At the 2017 Triangle Research Libraries Network Institute, staff from the University of North Carolina at Chapel Hill and Duke University used the 47 data curation activities identified by the Data Curation Network project to create conceptual groupings of data curation activities. The results of this "thought-exercise" are discussed in this white paper. The purpose of this exercise was to provide more specificity around data curation within our individual contexts as a method to consistently discuss our current service models, identify gaps we would like to fill, and determine what is currently out of scope. We hope to foster an open and productive discussion throughout the larger academic library community about how we prioritize data curation activities as we face growing demand and limited resources.

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"Data-Level Metrics Now Available through Make Data Count"

DataONE has released "Data-Level Metrics Now Available through Make Data Count."

Here's an excerpt:

One year into our Sloan funded Make Data Count project, the Make Data Count Team comprising DataONE, California Digital Library and Data Cite are proud to release Version 1 of standardized data usage and citation metrics! . . .

Since the development of our COUNTER Code of Practice for Research Data we have implemented comparable, standardized data usage and citation metrics at Dash (CDL) and DataONE, two project team repositories. . . .

The Make Data Count project team works in an agile "minimum viable product" methodology. This first release has focused on developing a standard recommendation, processing our logs against that Code of Practice [COUNTER Code of Practice for Research Data] to develop comparable data usage metrics, and display of both usage and citation metrics at the repository level.

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"The Changing Influence of Journal Data Sharing Policies on Local RDM Practices "

Dylanne Dearborn et al. have published "The Changing Influence of Journal Data Sharing Policies on Local RDM Practices" in the International Journal of Digital Curation.

Here's an excerpt:

The purpose of this study was to examine changes in research data deposit policies of highly ranked journals in the physical and applied sciences between 2014 and 2016, as well as to develop an approach to examining the institutional impact of deposit requirements. Policies from the top ten journals (ranked by impact factor from the Journal Citation Reports) were examined in 2014 and again in 2016 in order to determine if data deposits were required or recommended, and which methods of deposit were listed as options. For all 2016 journals with a required data deposit policy, publication information (2009-2015) for the University of Toronto was pulled from Scopus and departmental affiliation was determined for each article. The results showed that the number of high-impact journals in the physical and applied sciences requiring data deposit is growing. In 2014, 71.2% of journals had no policy, 14.7% had a recommended policy, and 13.9% had a required policy (n=836). In contrast, in 2016, there were 58.5% with no policy, 19.4% with a recommended policy, and 22.0% with a required policy (n=880). It was also evident that U of T chemistry researchers are by far the most heavily affected by these journal data deposit requirements, having published 543 publications, representing 32.7% of all publications in the titles requiring data deposit in 2016. The Python scripts used to retrieve institutional publications based on a list of ISSNs have been released on GitHub so that other institutions can conduct similar research.

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"A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository"

Amy M Pienta et al. have published "A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository" in the International Journal of Digital Curation.

Here's an excerpt:

Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.

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"Modelling the Research Data Lifecycle"

Stacy T. Kowalczyk has published "Modelling the Research Data Lifecycle" in the International Journal of Digital Curation.

Here's an excerpt:

This paper develops and tests a lifecycle model for the preservation of research data by investigating the research practices of scientists. This research is based on a mixed-method approach. An initial study was conducted using case study analytical techniques; insights from these case studies were combined with grounded theory in order to develop a novel model of the Digital Research Data Lifecycle. A broad-based quantitative survey was then constructed to test and extend the components of the model. The major contribution of these research initiatives are the creation of the Digital Research Data Lifecycle, a data lifecycle that provides a generalized model of the research process to better describe and explain both the antecedents and barriers to preservation. The antecedents and barriers to preservation are data management, contextual metadata, file formats, and preservation technologies. The availability of data management support and preservation technologies, the ability to create and manage contextual metadata, and the choices of file formats all significantly effect the preservability of research data.

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Research Data Preservation in Canada: A White Paper

The Portage Network has released Research Data Preservation in Canada: A White Paper.

Here’s an excerpt from the announcement:

The Preservation Expert Group (PEG) was created to advise Portage on developing research data management (RDM) infrastructure and best practices for preserving research data and metadata in Canada. The members of PEG have written this White Paper as a foundation document to describe the current digital preservation landscape, highlighting some of the digital preservation work already being undertaken in Canada, and to identify challenges that need to be addressed by Portage and other stakeholders to develop and improve RDM capacity and infrastructure across the country.

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