IASSIST Quarterly (Journal)
Not a member yet
764 research outputs found
Sort by
Restricting data’s use: A spectrum of concerns in need of flexible approaches
Full text linkAs researchers consider making their data available to others, they are concerned with the responsible use of data. As a result, they often seek to place restrictions on secondary use. The Research Connections archive at ICPSR makes available the datasets of dozens of studies related to childcare and early education. Of the 103 studies archived to date, 20 have some restrictions on access. While ICPSR’s data access systems were designed primarily to accommodate public use data (i.e. data without disclosure concerns) and potentially disclosive data, our interactions with depositors reveal a more nuanced notion range of needs for restricting use. Some data present a relatively low risk of threatening participants’ confidentiality, yet the data producers still want to monitor who is accessing the data and how they plan to use them. Other studies contain data with such a high risk of disclosure that their use must be restricted to a virtual data enclave. Still other studies rest on agreements with participants that require continuing oversight of secondary use by data producers, funders, and participants. This paper describes data producers’ range of needs to restrict data access and discusses how systems can better accommodate these needs
Frustrations and roadblocks in data reference librarianship
Full text linkAs data skills are incorporated into academic curriculum and data becomes more widely available and used in everyday life, many librarians find themselves serving as \u27accidental\u27 data librarians in their subject areas. Due to this evolving landscape and growing data need, it is increasingly important for librarians to be familiar with data resources and able to answer secondary data reference questions. To learn more about this area of librarianship, this study uses survey responses from librarians who answer data questions to explore the challenges and frustrations that arise from data reference questions and interactions. Our key findings reveal that frustrations are ever present in data reference regardless of how much experience a librarian has, and many frustrations arise due to factors such as patron expectations, subject-specific and data-related jargon, and data formats and accessibility
Research-driven approaches to improving archival discovery
Full text linkThe National Anthropological Archives (NAA), part of the Department of Anthropology at the Smithsonian’s National Museum of Natural History, holds some 18,000 cubic feet of materials of relevance to qualitative researchers. These archival collections—manuscripts, fieldnotes, audio recordings, drawings, maps, and still and moving images—are used by not only anthropologists, but increasingly scholars from a range of qualitative research fields. In 2016, the NAA received a grant to support a 3-year post-doctoral fellow to conduct research that would lead to the improved discovery and use of archival resources. This article discusses some of the practical ways the fellowship was designed to ask interdisciplinary research questions, and describes how that premise, as well as findings from a pilot study run in the first year, are helping to improve the research experience for our increasingly interdisciplinary users. Both the project’s preliminary findings and its overall design may provide valuable insights to qualitative researchers and their institutions
How NOT to create a digital media scholarship platform: the history of the Sophie 2.0 project
Full text linkSince the mid-2000s digital platforms have emerged to take advantage of the capabilities of new technology to incorporate media content, tell nonlinear stories, and reinvent the book for the 21st century. Sophie 1.0, from the University of Southern California, the Institute for the Future of the Book (IFB), and computer scientists based in Europe, was an attempt to create a multimedia editing, reading, and publishing platform. Sophie 2.0 was an international collaboration between the University of Southern California and Astea Solutions in Bulgaria to rewrite Sophie 1.0 in the Java programming language. This research will explore how the Sophie 2.0 project was unable to become a viable and wellmaintained open source product despite receiving over a million dollars in funding from the Mellon Foundation. Problems included the technological difficulty of creating an easy-to-use but completely customizable open source multimedia e-publishing platform, which was also compounded by competing visions over what this project was to be. Stakeholders did not demand a deliverable that actually worked. Funders seemed willing to overlook weaknesses in early releases for a more encompassing, if impractical, project. The computer scientists wanted to add the most features possible while, the IFB and USC Institute for Multimedia Literacy focused on creating a product based on the values of a future they hoped to create. Understanding what went wrong with Sophie 2.0 can help us understand how to create better digital media scholarship tools and to start much needed discussions about failure in the digital humanities.  
Data archiving for dissemination within a Gulf nation
Full text linkSince 2008, Qatar University’s Social and Economic Survey Research Institute (SESRI), has been collecting nationally representative survey data on social and economic issues. In 2017, SESRI leadership established an Archiving Unit tasked with data preservation and dissemination both for internal purposes and with the intent of disseminating select data to the public for secondary analysis.
This paper reviews the lessons learned from creating a data archive in an emerging economy where both cultural and political sensitivities exist amid varied groups of stakeholders. Challenges have included recruiting trained personnel, developing policies for data selection and workflow objectives, processing restricted and non-restricted datasets and metadata, data security issues, and promoting usage. Additionally, there is hope that the presence of the Archiving Unit adds value for other SESRI research staff involved in the design, collection, documentation, and processing of studies. After successfully addressing these challenges over the past year, the Archive met its objective to launch a data center at the Institute’s website (http://sesri.qu.edu.qa) and to make multiple datasets available for public download from it. Also, to be discussed are the tools, processes and leveraging of resources that are being implemented as the archiving process continues to evolve
Managing data in cross-institutional projects
Full text linkThis paper provides guidelines for data management professionals and researchers on how FAIR data usage can help improve the planning, execution and overall success of a cross-institutional project. Cases from Danish cross-institutional projects are detailed to illustrate this point – as well as the lessons learnt with implementing FAIR data principles in such projects. Key learnings from this paper are:
Using FAIR data principles in cross-institutional projects can help manage the data used in the project in terms of knowledge sharing, access rights, use of templates, metadata and further sharing the data after the project has ended.
To benefit the most from using FAIR data in a cross-institutional project it should be considered and planned for early in the project process.
If FAIR is not considered early in the project process problems can arise such as a lot of time spent on converting formats, obtaining permissions and assigning metadata.
It is necessary for researchers and research projects to have infrastructure and other services in place which support FAIR data usage
Cycling infrastructure in the Ottawa-Gatineau area: a complex assemblage of data
Full text linkThe Ottawa-Gatineau National Capital Region (Canada) has a well developed and well used cycling network of over 1,000 km which spans both sides of the Ontario and Quebec provincial boundary. The purpose of this study is to map out the complex data landscape behind the cycling infrastructure in the National Capital Region (NCR), which is largely based on inter-jurisdictional cooperation and partnerships with cycling advocacy groups. The questions we try to answer are: What data are collected for cycling infrastructure and activities? Who are the data producers and stakeholders? What are the relationships amongst the various data producers and stakeholders? The study reveals that the complexity of the cycling data landscape in the NCR is due to the complexity of the relationships between the various data producers and stakeholders
Guest editors\u27 notes: Special issue on qualitative research support
No full textWelcome to the second issue of Volume 43 of the IASSIST Quarterly (IQ 43:2, 2019). Four papers are presented in this issue on qualitative research support. This special issue arises from conversations in the Qualitative Social Science and Humanities Data Interest Group (QSSHDIG) at IASSIST about how best to support qualitative researchers. This group was founded in 2016 to explore the challenges and opportunities facing data professionals in the social sciences and humanities, and has focused on using, reusing, sharing, and archiving of qualitative, textual, and other non-numeric data.
In ‘Annotation for transparent inquiry (ATI),’ Sebastian Karcher and Nic Weber present their work on a new approach to transparency in qualitative research by the same name, which they have been exploring at the Qualitative Data Repository at the University of Syracuse, New York. As one solution to the problem of ‘showing one’s work’ in qualitative research, ATI allows researchers to link final reports back to the underlying qualitative and textual data used to support a claim. Using the example of Hypothes.is, they discuss the positives and negatives of ATI, particularly the amount of time required to annotate a qualitative article effectively and technical limitations in widespread web display.
The next article highlights how archived materials can be re-used by qualitative researchers and used to build their arguments. In ‘Research driven approaches to archival discovery,’ Diana Marsh examines what qualitative researchers need from the collections at the National Anthropological Archives in the United States, in order to improve archival discovery for those not as accustomed to working in the archives.
In ‘Bringing method to the madness,’ Mandy Swygart-Hobaugh, Leader of the Research Data Services Team at the Georgia State University Library, outlines a project created to bridge the gap between training researchers to use qualitative data software and training them in qualitative methods. Her answer has been a collaborative workshop with a sociology professor who provides a methodological framework while she applies those principles to a project in NVivo. These successful workshops have helped to encourage researchers to consider qualitative methods while at the same time promoting the use of CAQDAS software.
Jonathan Cain, Liz Cooper, Sarah DeMott, and Alesia Montgomery in their article ‘Where QDA is hiding?’ draw on a study originally conducted for QSSHDIG to create a list of qualitative data services in libraries. When they realized that finding these services was quite difficult, they expanded the study to examine the discoverability of library sites supporting QDA. This study of 95 academic library websites provides insight into the issues of finding and accessing library websites that support the full range of qualitative research needs. They also outline the key characteristics of websites that provide more accessible access to qualitative data services.
We thank our authors for participating in this special issue and providing their insights on qualitative data and research. If you are interested in issues related to qualitative research, then please join the Qualitative Social Sciences and Humanities Data Interest Group. Starting with IASSIST 2019 in Australia, our interest group has a new leadership team with two of our authors, Sebastian Karcher and Alesia Montgomery, taking over as co-conveners. We are certain that they would love to hear your ideas for the group, and we look forward to working with the qualitative data community more in the future.
Lynda Kellam, Cornell Institute for Social & Economic Research
Celia Emmelhainz, University of California, Berkele
The interest group on qualitative data sums up and continues
Full text linkWelcome to the second issue of volume 43 of the IASSIST Quarterly (IQ 43:2, 2019).
With joy and pride the many people behind each issue of the IQ are here presenting a special issue. IASSIST has several interest groups of members committed to selected important areas under the umbrella of IASSIST. Be aware that you could become a member of an interest group (see: https://iassistdata.org/about/committees.html#interest). If an interest area that you find important is not presently on this list, you are invited to start campaigning for the formation of a new interest group. The interest groups discuss and document their area and often arrange sessions at the IASSIST conferences. More formalization and continued documentation of the group’s work are presented in conference papers and papers published here in the IQ.
This issue of the IQ is dedicated to papers on qualitative data presented by members of the group named ‘Qualitative Social Science & Humanities Data Interest Group’ (QSSHDIG) and related practitioners. Lynda Kellam from the Cornell Institute for Social & Economic Research and Mandy Swygart-Hobaugh of George State University end their leadership of the group with this special issue. Lynda Kellam and Celia Emmelhainz (qualitative research librarian at the University of California Berkeley) are guest editors of this issue and their introduction to the issue is following this page. I want to express my great thanks from the IQ to Lynda and Celia for taking the job of compiling a special issue. Support for qualitative data is important and a growing area. I trust you as readers will find valuable information and excellent advice in the papers of the many authors that are committed to improving the use and value of qualitative data.
Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. 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 https://www.iassistquarterly.com (our Open Journal System application). We permit authors \u27deep links\u27 into the IQ as well as deposition of the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue IQ 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 IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout:
https://www.iassistquarterly.com/index.php/iassist/about/submissions
Authors can also contact me directly via e-mail: [email protected]. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you.
Karsten Boye Rasmussen - June 201
Annotation for transparent inquiry: Transparent data and analysis for qualitative research
Full text linkHow can authors using many individual pieces of qualitative data throughout a publication make their research transparent? In this paper we introduce Annotation for Transparent Inquiry (ATI), an approach to enhance transparency in qualitative research. ATI allows authors to connect specific passages in their publication with an annotation. These annotations provide additional information relevant to the passage and, when possible, include a link to one or more data sources underlying a claim; data sources are housed in a repository. After describing ATI’s conceptual and technological implementation, we report on its evaluation through a series of workshops conducted by the Qualitative Data Repository (QDR) and present initial results of the evaluation. The article ends with an outlook on next steps for the project