Category Archives: oa.rdm

Scholarly Communications, Data, and Affordable Learning Librarian

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“Reporting to the Head of Reference, Outreach, & Instruction in Healey Library, and working closely with other units across the Library (including Collections, Archives & Special Collections, Library Systems & Discovery Services, Technical Services) and across the University as needed (e.g. IT, the Open Educational Resources [OERs] Working Group, instructional and learning designers, etc.), the Scholarly Communications, Data, & Affordable Learning Librarian will have a strong commitment to user-centered service delivery and to student and faculty success.  The successful candidate will promote awareness, adoption, creation, and support for Open Education and Affordable Learning Initiatives, and for Open Access publishing inquiries.  The successful candidate will also oversee the ScholarWorks Institutional Repository, and will assist faculty and other users with Research Data Management Plans, management of research datasets, and related activities.  These will constitute the bulk of the position’s duties, but this position will also have some assigned areas of focus, including outreach, instruction, reference/research support, and related services within our Liaison Librarian program.  The Scholarly Communications, Data, & Affordable Learning Librarian is a newly created role within Healey Library, and it is expected that the incumbent will be able to play a strong role in shaping the nature of the position as related campus and library programs in these areas grow (e.g. Open Access publishing, OERs, research data management, etc.). …”

Evolution of research data management in academic libraries: A review of the literature – Arslan Sheikh, Amara Malik, Rubina Adnan, 2023

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Abstract:  This study provides insights into the evolution and conceptual framework of research data management (RDM). It also investigates the role of libraries and librarians in offering data management services and the challenges they face in this regard. The study is qualitative in nature and based on an extensive literature review survey. The analysis of the reviewed literature reveals that the idea of RDM has emerged as a new addition to library research support services. The more recent literature clearly established the pivotal role of libraries and librarians in developing and managing RDM services. However, data sharing practices and the development of RDM services in libraries are more prevalent in developed countries. While these trends are still lacking among researchers and libraries in developing countries. Creating awareness among researchers about the benefits of data sharing is a challenging task for libraries. Furthermore, institutional commitment, collaboration, academic engagement, technological infrastructure development, lack of policies, funding, and storage, skills, and competencies required for librarians to offer RDM-based services are some of the other significant challenges highlighted in the literature. Certainly, RDM services are difficult and complicated; therefore, librarians need to master the skills of research data to offer library-based RDM services.

 

Research data management needs assessment for social sciences graduate students: A mixed methods study | PLOS ONE

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Abstract:  The complexity and privacy issues inherent in social science research data makes research data management (RDM) an essential skill for future researchers. Data management training has not fully addressed the needs of graduate students in the social sciences. To address this gap, this study used a mixed methods design to investigate the RDM awareness, preparation, confidence, and challenges of social science graduate students. A survey measuring RDM preparedness and training needs was completed by 98 graduate students in a school of education at a research university in the southern United States. Then, interviews exploring data awareness, knowledge of RDM, and challenges related to RDM were conducted with 10 randomly selected graduate students. All participants had low confidence in using RDM, but United States citizens had higher confidence than international graduate students. Most participants were not aware of on-campus RDM services, and were not familiar with data repositories or data sharing. Training needs identified for social science graduate students included support with data documentation and organization when collaborating, using naming procedures to track versions, data analysis using open access software, and data preservation and security. These findings are significant in highlighting the topics to cover in RDM training for social science graduate students. Additionally, RDM confidence and preparation differ between populations so being aware of the backgrounds of students taking the training will be essential for designing student-centered instruction.

Public Access Data Management and Sharing Activities for Academic Administration and Researchers – Association of Research Libraries

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“The Realities of Academic Data Sharing (RADS) Initiative’s public-access data management and sharing (DMS) activities are the result of categorizing services and support across the institution that are likely needed to make public access to research data available. The RADS project team categorized these activities by life-cycle phases for public access to research data, and used the activities in RADS surveys of publicly funded campus researchers and institutional administrators whose departments likely provide support in these areas. The result of categorizing and defining these activities not only delineated questions for RADS’s retrospective studies, but, consequently, may also help researchers, administrators, and librarians prepare for upcoming federal and institutional policies requiring access to publicly funded research data.

This report presents version 1 of the RADS public access DMS activities. Additional versions are expected to be released as more institutions engage in implementing new federal policies in the coming months. Community engagement and feedback on the RADS DMS activities is critical to (1) validate the activities and (2) parse out the activities, as sharing and refining them will benefit stakeholders interested in meeting new federal open-access and sharing policies….”

Fischer et. al. (2022) Producing Open Data | Research Ideas and Outcoms

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Fischer C, Hirsbrunner SD, Teckentrup V (2022) Producing Open Data. Research Ideas and Outcomes 8: e86384. https://doi.org/10.3897/rio.8.e86384

Abstract:

Open data offer the opportunity to economically combine data into large-scale datasets, fostering collaboration and re-use in the interest of treating researchers’ resources as well as study participants with care. Whereas advantages of utilising open data might be self-evident, the production of open datasets also challenges individual researchers. This is especially true for open data that include personal data, for which higher requirements have been legislated. Mainly building on our own experience as scholars from different research traditions (life sciences, social sciences and humanities), we describe best-practice approaches for opening up research data. We reflect on common barriers and strategies to overcome them, condensed into a step-by-step guide focused on actionable advice in order to mitigate the costs and promote the benefit of open data on three levels at once: society, the disciplines and individual researchers. Our contribution may prevent researchers and research units from re-inventing the wheel when opening data and enable them to learn from our experience.

The Intangible Rewards of Engaging with Research Data – NLM Musings from the Mezzanine

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“As I reread the OSTP Public Access Memos from 2013 and 2022, I am struck again by the premise behind openly sharing research data:

When federally funded research is available to the public, it can improve lives, provide policymakers with important evidence with which to make critical decisions, accelerate the rates of discovery and translation, and drive more equitable outcomes across every sector of society.

That’s ambitious enough but sharing research data goes a few steps further: It also uses our taxpayer funds more efficiently, increases public trust in the scientific endeavor, and facilitates research collaboration. However, if you haven’t had the opportunity to be a part of it yet, these can remain abstract motivations and may seem daunting. How and why would any librarian engage with sharing research data? …”

Open Access is necessary but not sufficient to ensure research integrity

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This interactive session will explore the central role of open access to publications, data, instruments, protocols, code and/or scripts in fostering a culture of research integrity and public trust in research. Through discussion of contemporary investigations into misconduct, we will consider the interconnectedness of good data practices and open access with principles of research integrity. In particular, we will discuss concrete practices related to project management, data management, and training that enable validation, foster a culture of research integrity, and support greater openness in the conduct of research and dissemination of research outputs.

NIH Data Management and Sharing Policy | University Libraries | Virginia Tech

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“After January 25, 2023, all NIH grant applications or renewals that generate scientific data must include a robust and detailed plan for how researchers will manage and share data during the entire funded period. This includes information on data storage during a project, access policies/procedures, data preservation after a project is completed, metadata standards, and sharing approaches. Researchers must provide this information to NIH in a data management and sharing plan (DMSP) at the time of proposal submission. The DMSP is similar to what other funders call a data management plan (DMP).

The DMSP is assessed by NIH program staff as part of your grant application. Reviewers also have access to this document. The NIH Institute, Center or Office (ICO)-approved plan is important because it becomes a term and condition of award if you are awarded your grant.

This policy will supersede the NIH Data Sharing Policy of 2003, but will not supersede other NIH research sharing policies. Plans for sharing genomic data as expected by the Genomic Data Sharing (GDS) Policy are to be described in the DMSP submitted at the time of proposal submission, and not in a separate GDS Plan or at Just-in-Time….”

The Pitch: Hire Research Data Management Librarians ASAP | Arthur J. Boston

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“If you have any budgetary power at your university, you need to contact whoever is in charge of overseeing the compliance of federally-funded research. If you are that person in the office of sponsored programs, you need to contact your libraries to identify who is involved in research data management (RDM). And finally, if you are a head librarian who supervises anyone involved in RDM, ask them to write up a full memo detailing the staffing and support necessary to run a full shop and not be shy about it. University leadership, offices of sponsored programs, and libraries need to hire research data management librarians and specialists, and soon. Move a mountain and make it happen. 

By order of the recent White House Office of Science and Technology Policy (OSTP) memo, by the end of 2025, faculty conducting federally-funded research will need to deposit their underlying research data, immediately and without embargo. Even the data that doesn’t lead to publication. While data deposit was part of the previous OSTP guidance from 2013, it only applied to federal agencies with more than $100M in R&D expenditures. The more recent 2022 Nelson Memo extends to all agencies, agencies who are now working with “OSTP to update their public access and data sharing plans by mid-2023.” 

It’s unclear how intensely federal agencies have scrutinized their researcher’s compliance with regard to data deposit since 2013, but given that the 2022 Memo mentions the word data 50 times compared to the 31 mentions in 2013, there seems to be a renewed emphasis on its importance….”

EOSC Symposium 2022, Nov 14-17, 2022 @ Prague (CZ) & online | EOSC Association

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The EOSC Symposium is the main EOSC annual event and this year takes place in Prague, Czech Republic, from 14th-17th November 2022.

Over 500 stakeholders from ministries, policy makers, research performing organisations, service providers, research infrastructures and research communities across Europe and beyond are expected to attend the Symposium to reflect on the EOSC key achievements and strategic challenges and to identify priorities and concrete actions at European, national, and institutional level to speed up the EOSC implementation.

 

During the Symposium, there will be an opportunity to inspire the EOSC community by sharing your work or ideas. Apply to the call for talks or sessions now! Deadline: Friday 23 September 2022, 17:00 CEST.

Call for talks: Submit a talk (the talk should not exceed 7 minutes) on the following topics:

FAIR enabling practices 
Use cases demonstrating the added value of EOSC
EOSC Core developments
EOSC Exchange & Data Federation developments
Federation of national Research Infrastructures & e-infrastructure in EOSC
Training & Skills for EOSC
Contributions of for profit partners to EOSC
Engaging stakeholders in EOSC

More information here.

Call for sessions: Submit ideas for a side session (max 90 minutes) or an evening session (up to 3 hours). Please note that there is a limited number of slots for sessions and the sessions might be running in parallel with the main programme of the Symposium.Please double check the draft structure of the event here. 

More information here.

The applications will be evaluated by the Programme Committee and the applicants will be notified on the week of the 3rd of October 2022.

 

Towards a European network of FAIR-enabling Trustworthy Digital Repositories (TDRs) – A Working Paper | Zenodo

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Philipp Conzett, Ingrid Dillo, Francoise Genova, Natalie Harrower, Vasso Kalaitzi, Mari Kleemola, Amela Kurta, Pedro Principe, Olivier Rouchon, Hannes Thiemann, & Maaike Verburg. (2022). Towards a European network of FAIR-enabling Trustworthy Digital Repositories (TDRs) – A Working Paper (v2.0). Zenodo. https://doi.org/10.5281/zenodo.7034315

Abstract: This working paper is a bottom-up initiative of  a group of stakeholders from the European repository community. Its purpose is to outline an aspirational vision of a European Network of FAIR-enabling Trustworthy Digital Repositories (TDRs). This initiative originates from the workshop entitled “Towards exploring the idea of establishing the Network”. The paper was created in close connection with the wider community, as its core was built on community feedback and the first draft of the paper was shared for community-wide consultation. This paper will serve as input for the EOSC Task Force on Long Term Digital Preservation. One of the core activities mentioned in the charter of this Task Force is to produce recommendations on the creation of such a network.

The working paper puts together a vision of how a European network of FAIR-enabling TDRs could be based on the community’s needs and its most important functions: Networking and knowledge exchange, stakeholder advocacy and engagement, and coordination and development. The specific activities hosted under these umbrella functions could address the wide range of topics that are important to TDRs. Beyond these functions and the challenges they address, the paper presents a framework to highlight aspects of the Network to further explore in the next steps of its development.

 

Analysis of Harvard Medical School Countway Library’s MOOC Course, Best Practices for Biomedical Research Data Management: Learner Demographics and Motivations

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Abstract:  The Harvard Medical School Countway Library’s Massive Open Online Course (MOOC) Best Practices for Biomedical Research Data Management launched on Canvas in January 2018. This report analyzes learner reported data and course generated analytics from March 2020 through June 2021 for the course. This analysis focuses on three subsets of participant data during the pandemic to understand global learner demographics and interest in biomedical research data management.