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Conference Presentations 2017

  • IASSIST 2017-IASSIST 2017 – Data in the Middle: The common language of research, Lawrence
    Host Institution: University of Kansas

E2: Encouraging Data Publishing in the Social Sciences and Humanities (Thu, 2017-05-25)
Chair:Karen Hogenboom

  • Scooping the social sciences: how new metrics can help us make sense of data
    Lily Troia (Altmetric)

    [abstract]

    How much impact does your institution have? And how do you know? Are your researchers getting the funding they deserve, or is there room for improvement? 

    In this session we'll look at the role that engagement metrics play in the challenges and opportunities that make up the current research landscape. 

    We'll present case studies of how institutions around the world are using these data to track and showcase the value of their arts, social science and humanities outputs, and discuss how these new approaches have been integrated into existing workflows. 
    As researchers become more connected to each other and to a broader audience, it's crucial that institutions play a more active role in monitoring and supporting the conversation relating to their expertise. This session will provide attendees with practical ideas for how they might go about getting started.

  • Why do authors of social science journal articles share their data? Explanations by the Theory of Planned Behavior.
    Esra Akdeniz (GESIS – Leibniz-Institute for the Social Sciences)
    Wolfgang Zenk-Möltgen (GESIS – Leibniz-Institute for the Social Sciences)

    [abstract]

    Previous work on data sharing of sociology and political science research datasets focused on journal policies in the fields of social and political science and their impact on authors´ data sharing behaviors. In order to analyze individual motivations of data sharing, we extended this approach with a survey to authors of articles in academic journals, revealing their views on data sharing. After presenting initial descriptive results at IASSIST2016, we now provide some more in-depth analysis.

    The Theory of Planned Behavior (TPB) has proved to be a powerful approach to better understand human behavior. Therefore, the survey was conducted with the aim to identify possible factors that can affect researchers´ behavior towards data sharing in terms of three aspects: attitude towards data sharing, perceived social norm and perceived behavioral control. The data was analyzed using structural equation modelling (SEM) to outline the role of TPB and to explain data sharing in the social sciences.

E3: Tools for Reproducible Workflows Across the Research Lifecycle (Thu, 2017-05-25)
Chair:Amber Sherman

  • Building up a Tool Chain to support the Research Data Life Cycle
    David Schiller (TBA21 Germany)
    Ingo Barkow (HTW Chur - University of Applied Sciences)

    [abstract]

    The Research Data Life Cycle includes several processes from data collection plans (questionnaires or alternative data collection techniques) to the actual data collection, the processing of raw data, first data analysis, data archiving as well as curating data and data dissemination. Each of those processes needs to be supported by a specialized software. Thereby the quality of data and efficiency of research is heavily depending on the software used and the interoperability of different software products.

    A variety of products often leads to complications during the Research Data Life Cycle. Different formats and standards, proprietary code, and sometimes the lack of appropriate and user friendly software at all make it hard and sometimes impossible to create and maintain efficient Research Data Life Cycle processes. The recommendation of a Tool Chain to support the complete process aims on solving those challenges. Build on Open Source and wit

    h interoperability in mind different software modules focus on different process within the life cycle. The paper first describes the different processes within the Research Data Life Cycle, afterwards names appropriate tools or shows blank spaces in the overall workflow and closes with a summary of important best practice procedures needed to fulfil the requirements of a real Tool Chain.

  • Reproducing and preserving research with ReproZip
    Remi Rampin (New York University )
    Vicky Steeves (New York University)
    Fernando Chirigati (New York University)

    [abstract]

    The problem of reproducibility is multifaceted - there are social and cultural obstacles as well as technical inconsistencies that make replicating and reproducing extremely difficult. In this paper, we introduce ReproZip (https://reprozip.org), an open source tool to help overcome the technical difficulties involved in preserving and replicating research, applications, databases, software, and more.

  • Projects, Packrat, & Tidyverse - New ways to do reproducible research in R
    Alicia Hofelich Mohr (University of Minnesota)

    [abstract]

    While the "replication crisis" has called into question the reliability of many scientific findings from psychology to medicine, it has also highlighted the criticality of good data management in the research workflow. As researchers strive to make their work more transparent, open, and reproducible, more tools are being developed to support these efforts. The analysis workflow in particular is one part of the research lifecycle that stands to benefit most from these developments. This presentation will describe how researchers can integrate better data management and reproducibility into their analyses using new extensions in R, a popular tool for statistical computing. These extensions include new support for a variety of tasks, such as file directory management (R Projects), version control and sharing (Git/Github interfaces), reproducible reports (knitr), project portability and longevity (Packrat), as well as visualization and data wrangling (Tidyverse).

E4: Strategies for Delivering Data Services (Thu, 2017-05-25)
Chair:Angela Zoss

  • Visualization Services in the Harvard College Library: Laying the groundwork
    Hugh Truslow (Harvard College Library)

    [abstract]

    Like many university library systems, the Harvard Library is trying to find ways to more deeply and meaningfully support the many new forms of digital and data-centric scholarship across the disciplines, and data visualization is one important aspect of this. Two newly created positions in the Maps, Media, Data, and Government Information unit in the Faculty of Arts & Sciences, are in the early stages of exploring service models, internal partnerships, outreach, and other issues as they try to build a program of services in the complex and decentralized Harvard system that in many ways has adapted to the landscape of digital scholarship by local responses, often within departments. What is the role that data visualization plays in the various aspects of the research lifecycle, not just in the presentation of research results? What are scalable models of support? What is the balance of training opportunities on specific visualization tools versus more general approaches? This presentation will delve into these and other questions.

  • Data Librarian in the middle, creating instructional content for the digital humanities
    Matthew Gertler (University of Toronto Scarborough)

    [abstract]

    A data librarian at a small to medium sized campus will receive data related requests from many disciplines representing a variety of approaches methodologies and tools. There may not be enough questions to merit multiple data specialists, but the breadth of questions can be difficult for one individual to handle. Join Matthew Gertler a data librarian who recently began his career starting from a Social Sciences Data Services perspective. He will discuss the challenges, opportunities and joys of delivering reference and instruction for data discovery, literacy, management, manipulation and visualization for a diverse academic audience.

    The discussion will be framed upon a project creating instructional content for five lectures of a digital humanities course with the collaboration and input of other librarians.  There will be an exploration of how principles related to research data are transferable across disciplines. This commonality aids in the creation of instructional content for discipline specific approaches. In contrast the content was targeted by discipline and skill set. This was true even for examples such as web mapping and data management, which are widely used.

  • Students helping students: Economic Library Student Assistants at Dartmouth College
    John Cocklin (Dartmouth College )

    [abstract]

    The number of undergraduate students taking Economics courses is rising dramatically at Dartmouth College. To better help them with their culminating senior projects, and assist their faculty, the Library is building a team of undergraduate student assistants. They help their fellow students find data, wrangle it into a form compatible with Stata, and then use it with Stata. When developing the team, the Library looked to examples from other college and university libraries.

    Since Dartmouth does not offer a Ph.D. in Economics or in Business, who are frequently used as consultants elsewhere, we look to undergraduates for providing consultation.  Indirectly, this program has proven to be a very effective form of outreach to both students and faculty. Directly, even at this early stage the program is successful on multiple levels. Students feel comfortable working with other students, and they can meet on evenings or week-ends when Librarians are unavailable. With the Library handling many of the data and basic Stata questions, faculty are given more time with students to focus on in-depth questions about econometric methodology. Perks for student assistants include advanced training in databases such as Bloomberg, an attractive skill to employers.

F1: Health Data: An International Comparative Deep Dive (Thu, 2017-05-25)
Chair:Ron Nakao

  • Health data: An international comparative deep dive
    Bobray Bordelon (Princeton University)
    Jane Fry (Carleton University)
    Ron Nakao (Stanford University)

    [abstract]

    A deep dive into data sources for health from Canada, the USA, and international developing countries will be presented.  What are the best sources for individual nations?  How does one choose which dataset(s) to use? Can comparisons be made between nations?  Sources from the United States' National Center for Health Statistics; Statistics Canada; the Demographic and Health Surveys; and other agencies will be explored.

F2: Building Bridges for Qualitative Social Science and Humanities Researchers (Thu, 2017-05-25)
Chair:Mandy Swygart-Hobaugh

  • Stuck in the middle with you: Building bridges for qualitative Social Science and Humanities researchers
    Lynda Kellam (UNCG)
    Mandy Swygart-Hobaugh (Georgia State University)
    Louise Corti (UK Data Service)
    Sebastian Karcher (Syracuse University)
    Dessi Kirilova ( Syracuse University)

    [abstract]

    The Qualitative Social Science and Humanities Data Interest Group was founded in 2016 to explore the challenges and opportunities facing data professionals in these areas.

    In this panel, Mandy Swygart-Hobaugh introduces how qualitative social science and humanities researchers may feel “stuck in the middle” between more quantitative disciplines, and how the language of data can help build bridges across disciplines and methodological approaches.

    Lynda Kellam discusses efforts to work with historians to apply principles of research "data" management to archival work. She discusses her efforts to develop and promote best practices with the history graduate students at UNCG, who use non-numerical data, such as PDFs, images etc.

    Louise Corti addresses disciplinary bridging, showing how older qualitative data, from the 1960s, is being used by social historians, firmly established as a humanities resource. She introduces her collaborative project with humanities scholars looking at automating the publishing of recorded oral histories.

    Sebastian Karcher and Dessislava Kirilova discuss the recent transparency agenda in the social science and humanities and what this means for different types of qualitative data. They draw on examples from political science and QDR to consider potential solutions for open science, such as the use of Annotation for Transparent Inquiry.

  • IASSIST Quarterly

    Publications Special issue: A pioneer data librarian
    Welcome to the special volume of the IASSIST Quarterly (IQ (37):1-4, 2013). This special issue started as exchange of ideas between Libbie Stephenson and Margaret Adams to collect

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  • Resources

    Resources

    A space for IASSIST members to share professional resources useful to them in their daily work. Also the IASSIST Jobs Repository for an archive of data-related position descriptions. more...

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