IASSIST Quarterly (Journal)
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Support for Computer-Assisted Qualitative Data Analysis Software in ARL libraries
Full text linkAcademic libraries are filled with niche support services that are unique to their primary clientele. While rarely taught to librarians in a formal academic setting, the support of Computer-Aided Qualitative Data Analysis Software is one such niche that appears in academic libraries across North America. But how common is it, and at what level is support offered amongst members of the Association of Research Libraries? This paper attempts to answer this question
Introducing the Journal Editors Discussion Interface
Full text linkJournal editors play an important role in advancing open science in their respective fields. However, their role is temporary and (usually) part time, and therefore many do not have enough time to dedicate towards changing policies, practices, and procedures at their journals. The Journal Editors Discussion Interface (JEDI, https://dpjedi.org) is an online community for journal editors in the social sciences that was launched in 2021, consisting of a listserv and resource page. JEDI aims to increase uptake of open science at social science journals by providing journal editors with a space to learn and discuss. In this paper, we explore JEDI’s progress in its first two years, presenting data on membership, posts, and from a members survey. We see a reasonable mix of people participating in listserv conversations and there are no detectable differences among groups in the number of replies received by thread-starters. The community survey suggests JEDI members find conversations and resources on JEDI generally informative and useful, and see JEDI primarily as a community to get honest opinions from others on editorial practices. However, JEDI membership is not as heterogeneous as would be ideal for the purpose of the group, especially when considering geographic diversity
Data competencies for liaison librarians: A scoping review
Full text linkThis retrospective scoping review explores the data-related competencies required by liaison and subject librarians to effectively support academic researchers. Despite the growing demand for research data assistance, many librarians lack formal training (Tenopir et al., 2014) or confidence (Cox et al., 2012) in this area, often relying on self-taught skills. The objective of this review was to map data-related competencies over a ten-year period (2012-2022) with particular attention given to the skill sets that liaisons or non-data librarians may need to develop or hone. Overall, the findings indicate a surprisingly stable list of skills over this period. This review finds that to support research data services on campus, librarians must rely on traditional skills including reference/consulting, teaching/training and collaboration/engagement as well as data-specific competencies, including metadata creation, data preparation for repositories, data preservation, data management plan (DMP) creation, and programming/data analysis. These competencies are essential for librarians to assist researchers with data queries. The study highlights the need for structured training and suggests which competencies to prioritize. The findings aim to guide the development of self-training resources and cross-training initiatives to better equip librarians in supporting data-rich research
The ONS Longitudinal Study – opportunities for longitudinal research on the England and Wales population
Full text linkComprising longitudinal data on around 1.1 million individuals, the Office for National Statistics Longitudinal Study (ONS-LS) is the largest nationally representative longitudinal dataset in the United Kingdom. It follows a 1% sample of the England & Wales population drawn from the decennial census data (1971 – 2011), linked to some administrative data. Currently comprising up to 46 years of data (1971 – 2017) on sample members, the forthcoming linkage of the 2021 England and Wales Census data to the ONS-LS will extend this follow-up to 50 years. The Centre for Longitudinal Study Information and User Support (CeLSIUS) provides assistance for researchers wishing to use the ONS-LS in their research. Based at University College London (UCL) and the Office for National Statistics (ONS), it has been supporting academic and voluntary sector users of the ONS-LS since 2001. Its work includes helping researchers with their applications to use the ONS-LS, supporting research projects and advising on research outputs
Developing Institutional Research Data Management Strategies in Canada: Setting the Foundation for Stronger Partnerships and Collaborations
Full text linkThe Government of Canada’s Tri-Agency formally launched the Research Data Management (RDM) Policy in March 2021 with the objective of supporting “Canadian research excellence by promoting sound data management and data stewardship practices”. A central component of this policy requires postsecondary institutions eligible to administer Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), or the Social Sciences and Humanities Research Council of Canada (SSHRC ) funds to create an institutional RDM strategy by March 2023.
A national survey was developed to gauge institutions’ readiness for developing an institutional RDM strategy required by the Tri-Agency. The survey emphasized increasing participation from diverse institutions to ensure that future support and resources are developed to address the distinct needs of institutions.
Recommendations from the survey report included increasing Tri-Agency involvement as institutions developed their institutional RDM strategies, encouraging institutions to collaborate, and the development of forums to provide support for disciplinary societies to have RDM conversations.
As a result, three panel discussions covering the active stages (Initial, Planning, and Execution) of developing an institutional RDM strategy were successfully delivered through the Digital Research Alliance RDM (Alliance RDM) to a diverse range of institutions. Recognizing the needs of smaller institutions including CEGEPS, colleges, and polytechnics, an additional panel discussion was developed and delivered to this audience
Assessing needs and developing solutions
Full text linkWelcome to the second issue of IASSIST Quarterly for 2024, IQ 48(2).
It was wonderful to meet so many old and new colleagues at the Best IASSIST Ever in Halifax. It was really inspiring to learn about all the great work that is being done by members of this community. For those of you who presented, please consider turning your conference presentation or poster into a paper and submitting it to IQ. This will allow you to share your expertise with a wider audience.
If you were not able to attend the conference, you may have missed the announcement about the winner of the IASSIST Conference Paper Competition. This year’s winner is the paper “How are we FAIR-ing? Creating a FAIR Self-Assessment Checklist for Data Repositories” by Lauren Phegley and Lynda Kellam. In the paper the authors describe a project in which a data repository’s staff wanted to gauge how well they were enabling FAIR principles. A small team from Penn Libraries found that much of the literature about FAIR was from the perspective of data creators, so they developed a FAIR Principles Self-Assessment Tool for repository teams. We look forward to publishing this paper in a future issue.
We would like to take this opportunity to encourage you to look ahead to submitting your papers for next year’s paper competition. In addition to bragging rights, the award incudes free registration for the first author to the following year’s IASSIST conference.
The four papers included in this issue of IQ introduce tools developed in several institutions, representing a wide geographic diversity, to assess and resolve operational challenges.
In the article titled ”Research analysis: A World Data System and Canadian CoreTrustSeal Cohort needs assessment,” Lee, Gonzalez, Payne and Goins describe how they designed a method to identify the needs and challenges faced by members of the World Data System (WDS) and Canadian CoreTrustSeal Pilot. They also describe the assessment tool they developed and the overarching challenges and goals identified through the usage of this tool. Based on their findings, they provide recommendations on how best to assist the WDS members and the cohort of Canadian data repositories.
Constanzo and Cooper, in their article ”Developing institutional research data management strategies in Canada: Setting the foundation for stronger partnerships and collaborations,” describe national surveys developed by Research Intelligence Expert Group (RIEG) to gauge institutions’ readiness for developing an institutional RDM strategy required by the Government of Canada’s Tri-Agency. The first survey was conducted in 2019 and a follow-up survey in 2022 in order to assess the progress of institutions in creating their institutional strategies and identifying additional challenges. The authors and report the findings and recommendations from their study and share their survey instruments.
In ”Enhancing FAIR compliance: A controlled vocabulary for mapping social sciences survey variables,” authors Bach and Klas introduce the GESIS Controlled Vocabulary (CV) for Variables in Social Sciences Research Data. This CV is designed to enhance semantic interoperability across various organizations and systems, and facilitates harmonization across different study waves. This endeavor aligns with the FAIR data principles, and aims to foster a more integrated and accessible research landscape.
Obasola and Usman in their article ”Digitising old Yoruba newspapers at Kenneth Dike Library,” describe in detail the digitisation of a collection of old Yoruba newspapers stored at Kenneth Dike Library in Ibadan, Nigeria. The project was undertaken in order to preserve this historical and delicate material, which includes rich details of local history. In addition to providing a detailed workflow, the authors share lessons learned.
We hope you enjoy reading and wish you a productive summer.
Ofira Schwartz and Michele Hayslett, June 202
Future models and architecture of data repositories in African universities
Full text linkResearch data repositories as part of research infrastructures are being developed and are important tools and components that help to store, preserve, and allow for the re-use of data. As the technologies, networks, and systems that the data repositories are built upon are advancing, this study explores the future models and architectures that African universities can follow to have reliable and sustainable systems for the preservation of research data. A scoping review was done to focus on the future shape of data repositories based on past experiences of the last 10 years of research institutions in establishing data repositories. This study was done to gauge the communities’ responses to the architecture of existing platforms to prepare other institutions planning to establish digital research data repositories. Articles were retrieved from Scopus, Web of Science, and Dimensions databases using relevant keywords. The content analysis approach was used to establish the requirements for establishing digital research data repositories to develop a framework that can be utilised by other research institutions to develop their repositories. The framework would be handy in providing a roadmap for research institutions that want to establish research data services in Africa enhancing the future of research infrastructure in African universities
Developing systems to encourage FAIR and secure research data
Full text linkWelcome to first issue of IASSIST Quarterly for 2024; this is Volume 48 of the journal (IQ 48(1) 2024).
The three papers in this issue represent different aspects of researchers’ use of data archives. Experts from three major data archives (ICPSR, IPUMS, and GESIS) share their experiences developing systems to make research resources in their archives more findable, accessible, and usable.
Lafia, Million, and Hemphill in their article “Exploratory and directed search strategies at a social science data archive” investigate search strategies of users of a large social science data archive. In an effort to understand how users search for curated research data, the authors analyze data queries issued through the Inter-University Consortium for Political and Social Research (ICPSR) website’s search box. The study is meant to inform archives and repositories of their users’ experience and help develop systems that encourage dataset findability, accessibility and reuse. The authors identify two types of data searches, exploratory and directed searches. They find that while users that issued exploratory queries were able to navigate the ICPSR website successfully and refine their searches, they may benefit from more explicit support for query reformation. The authors suggest ways development of tools and training could improve users’ experience.
In the article “Stewarding our resources: Building a sustainable IPUMS archival document access system” Daina Magnuson describes IPUMS experience building a web interface to support exploration and dissemination of archival materials associated with IPUMS International (IPUMS-I). Ancillary materials, including thousands of unique pieces of census and survey documentation were obtained by IPUMS-I during data acquisition efforts. This rich source material was curated and preserved by archival staff. Magnuson describes in details the development of a system that would make these resources findable, searchable and downloadable to internal users as well as IPUMS researchers. Strategies describe may inform other data archives considering developing similar tools.
Deborah Wiltshire in her article “Developing canonical ‘Safe Researcher’ training materials for Trusted Research Environment” describes the development of training materials for researchers applying to access restricted data through Trusted Research Environment (TRE). The increased use of a virtual desktop environment, as opposed to physical safe rooms, offers researchers easier and more flexible access to restricted data; however, it offers fewer physical safeguards. Attending a mandatory ‘Safe Researcher’ training is one of the principles of the Five Safe Framework[i] developed by the UK’s Office for National Statistics to bridge this gap and assure the safe use of sensitive data. The process described in the article could be easily adapted by other TREs according to their needs and settings (e.g., in-person vs. online training).
In the spirit of making information findable, accessible and reusable, we’re happy to share that the Open Journal System platform from the University of Alberta has enabled author linking to ORCID. This means that IQ authors are now able to connect their ORCID iDs to their IQ publications, so that their ORCID profiles will automatically update with those citations as their articles are published. For existing IQ account holders, log into your account at the upper right of the IQ page, and go to Profile > Public. Then click “Create or Connect your ORCID iD” (just below the Homepage URL field). For details, see this video walkthrough of profile authentication. New IQ users will automatically be prompted to link (or create) their ORCID iDs during IQ account creation. Authors are also encouraged to note their ORCID iD link with their affiliation and contact information in an endnote when submitting a manuscript for publication.
We hope to see many of you at the 49th Annual IASSIST Conference in Halifax, Nova Scotia, Canada, May 28-31, 2024!
Ofira Schwartz and Michele Hayslett, March 2024
State of the DDI Cloud
Full text linkAs the DDI community continues to grow, an increasing number of repositories are providing their metadata in various DDI formats. However, the current landscape of DDI metadata standards usage is not well understood. Understanding this landscape is crucial as it helps identifying usage patterns, improve interoperability, and guide future developments. To address this research gap, we investigated the availability and comprehensive element usage of DDI standards across 29 repositories registered on the platform re3data.org, using the OAI-PMH API. By analyzing approximately, a quarter of a million metadata records in DDI-Codebook format, we summarized statistics on the usage of popular DDI elements and their distribution across repositories. Our findings may have implications for the deployment of DDI metadata and the further development of these standards. They also inform researchers and data stewards about how DDI-Codebook is utilized by the community. Overall, this investigation underscores the value of openly available metadata in supporting research and achieving the goals of the FAIR data movement.
Enhancing FAIR compliance: A controlled vocabulary for mapping Social Sciences survey variables
Full text linkThe dynamic relationship among survey instruments and study entities like questionnaires, variables, questions, and response formats evolve in Social Sciences surveys. Researchers may need to modify variable attributes such as labels or names, question-wording, or response scales when reusing variables in survey design. Therefore, explaining these relations across different waves and studies is necessary to track how variables relate to each other. Although standards like Data Documentation Initiative – Lifecycle (DDI-LC) and DataCite model these relationships, these frameworks fall short of capturing the complexity of variable relationships. The DDI Alliance Controlled Vocabulary for Commonality Type employs codes—such as \u27identical,\u27 \u27some,\u27 and \u27none\u27—to outline shifts in entities like variables; however, this approach is insufficient for disambiguating these relationships since they do not differentiate the variable attributes subject to change. We introduce the GESIS Controlled Vocabulary (CV) for Variables in Social Sciences Research Data to bridge this gap. This CV is designed to enhance semantic interoperability across various organizations and systems. Establishing explicit relationships facilitates harmonization across different study waves and enriches data reuse. This enhancement supports advanced search and browse functionalities. The CV, published via the CESSDA vocabulary manager, seeks to forge a semantically rich, interconnected knowledge graph specifically tailored for Social Science Research. This endeavour aligns with the FAIR data principles, aiming to foster a more integrated and accessible research landscape