https://iassistquarterly.com/index.php/iassist/issue/feed IASSIST Quarterly 2020-01-09T07:54:14-07:00 Karsten Boye Rasmussen editor.iassistquarterly@gmail.com Open Journal Systems <p class="p1">The <strong>IASSIST Quarterly</strong> represents an international cooperative effort on the part of individuals managing, operating, or using machine-readable data archives, data libraries, and data services. The&nbsp;<strong>IASSIST Quarterly </strong>reports on activities related to the production, acquisition, preservation, processing, distribution, and use of machine-readable data carried out by its members and others in the international social science community.&nbsp;</p> https://iassistquarterly.com/index.php/iassist/article/view/972 Sharing qualitative research data, improving data literacy and establishing national data services 2020-01-09T07:54:14-07:00 Karsten Boye Rasmussen editor.iassistquarterly@gmail.com <p>Welcome to the fourth issue of volume 43 of the IASSIST Quarterly (IQ 43:4, 2019).</p> <p>The first article is authored by Jessica Mozersky, Heidi Walsh, Meredith Parsons, Tristan McIntosh, Kari Baldwin, and James M. DuBois – all located at the Bioethics Research Center, Washington University School of Medicine, St. Louis, Missouri in USA. They ask the question “Are we ready to share qualitative research data?”, with the subtitle “Knowledge and preparedness among qualitative researchers, IRB Members, and data repository curators.” The subtitle indicates that their research includes a survey of key personnel related to scientific data sharing. The report is obtained through semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members in the USA. IRB stands for Institutional Review Board, which in other countries might be called research ethics committee or similar. There is generally an increasing trend towards data sharing and open science, but qualitative data are rarely shared. The dilemma behind this reluctance to share is exemplified by health data where qualitative methods explore sensitive topics. The sensitivity leads to protection of confidentiality, which hinders keeping sufficient contextual detail for secondary analyses. You could add that protection of confidentiality is a much bigger task in qualitative data, where sensitive information can be hidden in every corner of the data, that consequently must be fine-combed, while with quantitative data most decisions concerning confidentiality can be made at the level of variables. The reporting in the article gives insights into the differences between the three stakeholder groups. An often-found answer among researchers is that data sharing is associated with quantitative data, while IRB members have little practice with qualitative. Among curators, about half had curated qualitative data, but many only worked with quantitative data. In general, qualitative data sharing lacks guidance and standards.</p> <p>&nbsp;</p> <p>The second article also raises a question: “How many ways can we teach data literacy?” We are now in Asia with a connection to the USA. The author Yun Dai is working at the Library of New York University Shanghai, where they have explored many ways to teach data literacy to undergraduate students. These initiatives, described in the article, included workshops and in-class instruction - which tempted students by offering up-to-date technology, through online casebooks of topics in the data lifecycle, to event series with appealing names like “Lying with Data.” The event series had a marketing mascot - a “Lying with Data” Pinocchio - and sessions on being fooled by advertisements and getting the truth out of opinion surveys. Data literacy has a resemblance to information literacy and in that perspective, data literacy is defined as “critical thinking applied to evaluating data sources and formats, and interpreting and communicating findings,” while statistical literacy is “the ability to evaluate statistical information as evidence.” The article presents the approaches and does not conclude on the question, “How many?” No readers will be surprised by the missing answer, and I am certain readers will enjoy the ideas of the article and the marketing focus.</p> <p>&nbsp;</p> <p>With the last article “Examining barriers for establishing a national data service,” the author Janez Štebe takes us to Europe. Janez Štebe is head of the social science data archives (Arhiv Družboslovnih Podatkov) at the University of Ljubljana, Slovenia. The Consortium of European Social Science Data Archives (CESSDA) is a distributed European social science data infrastructure for access to research data. CESSDA has many - but not all - European countries as members. The focus is on the situation in 20 non-CESSDA member European countries, with emerging and immature data archive services being developed through such projects as the CESSDA Strengthening and Widening (SaW 2016 and 2017) and CESSDA Widening Activities (WA 2018). By identifying and comparing gaps and differences, a group of countries at a similar level may consider following similar best practice examples to achieve a more mature and supportive open scientific data ecosystem. Like the earlier articles, this article provides good references to earlier literature and description of previous studies in the area. In this project 22 countries were selected, all CESSDA non-members, and interviewees among social science researchers and data librarians were contacted with an e-mail template between October 2018 and January 2019. The article brings results and discussion of the national data sharing culture and data infrastructure. Yes, there is a lack of money! However, it is the process of gradually establishing a robust data infrastructure that is believed to impact the growth of a data sharing culture and improve the excellence and the efficiency of research in general.</p> <p>&nbsp;</p> <p>Submissions of papers for the <em>IASSIST Quarterly</em> are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the <em>IQ</em>. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author login to <a href="https://www.iassistquarterly.com">https://www.iassistquarterly.com</a> (our Open Journal System application). We permit authors to “deep link” into the <em>IQ</em> as well as to deposit the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue <em>IQ</em> is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the <em>IASSIST Quarterly</em> website at <a href="https://www.iassistquarterly.com">https://www.iassistquarterly.com</a>.&nbsp; Authors are very welcome to take a look at the instructions and layout:</p> <p><a href="https://www.iassistquarterly.com/index.php/iassist/about/submissions">https://www.iassistquarterly.com/index.php/iassist/about/submissions</a></p> <p>Authors can also contact me directly via e-mail: <a href="mailto:kbr@sam.sdu.dk">kbr@sam.sdu.dk</a>. Should you be interested in compiling a special issue for the <em>IQ</em> as guest editor(s) I will also be delighted to hear from you.</p> <p>Karsten Boye Rasmussen - December 2019</p> 2020-01-02T08:18:14-07:00 Copyright (c) 2020 Karsten Boye Rasmussen https://iassistquarterly.com/index.php/iassist/article/view/952 Are we ready to share qualitative research data? Knowledge and preparedness among qualitative researchers, IRB members, and data repository curators 2020-01-09T07:52:57-07:00 Jessica Mozersky jmozersky@wustl.edu Heidi Walsh heidiwalsh@wustl.edu Meredith Parsons m.parsons@wustl.edu Tristan McIntosh t.mcintosh@wustl.edu Kari Baldwin karibaldwin@wustl.edu James M DuBois duboisjm@wustl.edu <p>Data sharing maximizes the value of data, which is time and resource intensive to collect. Major funding bodies in the United States (US), like the National Institutes of Health (NIH), require data sharing and researchers frequently share de-identified quantitative data. In contrast, qualitative data are rarely shared in the US but the increasing trend towards data sharing and open science suggest this may be required in future. Qualitative methods are often used to explore sensitive health topics raising unique ethical challenges regarding protecting confidentiality while maintaining enough contextual detail for secondary analyses. Here, we report findings from semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members to explore their experience and knowledge of QDS. Our findings indicate that all stakeholder groups lack preparedness for QDS. Researchers are the least knowledgeable and are often unfamiliar with the concept of sharing qualitative data in a repository. Curators are highly supportive of QDS, but not all have experienced curating qualitative data sets and indicated they would like guidance and standards specific to QDS. IRB members lack familiarity with QDS although they support it as long as proper legal and regulatory procedures are followed. IRB members and data curators are not prepared to advise researchers on legal and regulatory matters, potentially leaving researchers who have the least knowledge with no guidance. Ethical and productive QDS will require overcoming barriers, creating standards, and changing long held practices among all stakeholder groups.</p> 2020-01-08T13:22:43-07:00 Copyright (c) 2020 Jessica Mozersky, Heidi Walsh, Meredith Parsons, Tristan McIntosh, Kari Baldwin, James M DuBois https://iassistquarterly.com/index.php/iassist/article/view/963 How many ways can we teach data literacy? 2020-01-09T07:53:49-07:00 Yun Dai yun.dai@nyu.edu <p><span style="font-weight: 400;">Academic Libraries are ideally positioned to teach data literacy. What is ‘data literacy’ in the first place? Is it the new information literacy? Will the ways we teach information literacy limit imaginative ways to teach data literacy?</span></p> <p><span style="font-weight: 400;">With those questions in mind, the Library of New York University Shanghai has explored multiple ways to teach data literacy to undergraduate students through university events, ‘for-class’ instruction and workshops, and online casebooks. (1) We initiated the yearlong series of events titled ‘Lying with Data’, inviting faculty across disciplines to each address one core data literacy question that </span><span style="font-weight: 400;">students of data science may elude.</span><span style="font-weight: 400;"> (2) We offered workshops and in-class instruction that are up-to-date with the latest technology and that fit with the curriculum. (3) We created online casebooks on various topics in the data lifecycle, tackling user needs at different levels. Essential to our teaching activities are two core values: ‘let the quality speak for itself’, and ‘outreach by teaching’.&nbsp;</span></p> 2020-01-02T11:57:01-07:00 Copyright (c) 2020 Yun Dai https://iassistquarterly.com/index.php/iassist/article/view/960 Examining barriers for establishing a national data service 2020-01-09T07:53:22-07:00 Janez Štebe janez.stebe@fdv.uni-lj.si <p><span lang="EN-GB" style="margin: 0px; line-height: 115%; font-family: 'Calibri',sans-serif; font-size: 11pt;">A system for monitoring the current situation of Data Archive Services (DAS) maturity in European countries was developed during the CESSDA Strengthening and Widening in (SaW 2016 and 2017) and further adapted in CESSDA Widening Activities 2018 (WA 2018) projects for continuous monitoring. An assessment of the existing national data sharing culture, the development of the social science sector and its production of high-quality research data, the funders’ research data policy requirements, and the capacity and skills of national grassroots initiatives, provide a framework for understanding the current situation in different countries. Methods used in the projects, included desk research of <span style="margin: 0px;">&nbsp;</span>existing documents and a survey, combined with extensive interviews focused on the area of expertise of the informants (individuals from data services, research and decision makers’ representatives from each country). The focus of the paper is the situation in 20 non-member CESSDA European countries with emerging and immature DAS initiatives. Results show that countries are slowly but persistently removing the key obstacles in establishing a DAS initiative in their respective countries. The remaining obstacles reside mainly outside the control of the data professional community – namely research funders slowly adopt data sharing policies and incentives for data sharing, including the provision of a sustainable DAS infrastructure, capable of supporting researchers with publishing and accessing research data. The results show that the lack of expertise and skills of DAS initiatives, their understanding of tools and services or organizational settings are not such an issue, as more mature DAS are organising training and mentorship activities. Detailed guidance in the DAS advocacy and planning was prepared in the framework of the above-mentioned pan-European and some past regional projects. The tools and framework of those activities will be referred to in the discussions as a resource that can be used in other countries and continents. </span></p> 2020-01-02T12:21:15-07:00 Copyright (c) 2020 Janez Štebe