Already a member?

Sign In

Conference Presentations 2016

  • IASSIST 2016-Embracing the 'Data Revolution': Opportunities and challenges for research, Bergen
    Host Institution: NSD - Norwegian Centre for Research Data

3D: Data curation: Active phase data management (Thu, 2016-06-02)
Chair:Limor Peer

  • Sharing code and research data with iPython notebooks
    Sandra Schwab (University of Alberta)


    Code is hard to share. It is often relegated to a citation or mentioned in an analysis, but it is rarely ever published with the results of the research it has informed. While making code and data available to scrutiny is a growing requirement for research funding, sharing code and raw data acknowledges the necessity for openness in research data management and scholarly communication. Librarians are on the forefront of the open data movement, and are uniquely positioned to help researchers find tools and resources that make the work of research easier to do and to disseminate. This presentation introduces iPython Notebook as a tool for sharing code-based research. iPython Notebook is an interactive web-based application that combines live code, data visualizations, and rich text and media. Using my own thesis work as an example, I will show how iPython notebooks can be used for text mining and data visualization on a 58-million-word, multi-file corpus. Using the coding language Python, I've conducted a text analysis on the transcripts of the Canadian Parliamentary debates (known as Hansard) to determine how the discourse of privacy has developed over a 10 year period. I've discovered changes over time in the patterns and frequencies of words being used in the discourse around privacy. I have shared my code and my corpus data on GitHub, for download and use by others. iPython Notebooks not only provide a platform for code to be openly published, they allow other researchers to conduct their own investigations on the data. The structure of the notebooks makes them accessible to non-coders, and their multi-media format provides a linear space for explanation and analysis. For research data to be truly open we must openly share and explain our code. iPython Notebook is an important tool that exemplifies the open data movement.

  • Electronic lab notebooks: A solution for active-phase data management
    Katherine McNeill (MIT)


    Many universities are looking to enable researchers to store data effectively during the active phase of research. Solutions need to provide not only storage, but also features for organization and metadata, collaborative work, and version control. One option is Electronic Lab Notebook (ELN) software, a platform used to collect and house experimental procedures, protocols, and data produced in scientific experiments. This presentation will discuss a recent project at one university to initiate a campus-wide rollout and support of a general-purpose ELN, LabArchives. This project is a collaboration between the several university departments: the Libraries, central IT, and the Office of the Vice President for Research. The presentation will discuss and address questions such as: How effective are ELNs for active-phase data management? How might ELNs be used within a suite of tools for active-phase data management? How can staff support adoption and use of ELNs? How can campus departments best collaborate to support use of ELNs? How can this work meet the diverse interests of stakeholders? What can rolling out an ELN teach us about how researchers manage their data day-to-day?

  • The UK Data Service's Unified User Interface - a framework to provide a consistent user experience for data and metadata management
    Ashley Fox (UK Data Archive)


    As technology platforms continually evolve to support developing trends such as big data, the need for responsive user facing applications is increasing. This presentation aims to demonstrate how new frameworks like AngularJS can be utilised to build powerful single page web applications. We will look at how The UK Data Service is developing a unified interface to manage the deposit, ingest and access workflow, along with study metadata for collections and series records, which powers our UK Data Service Discover search engine. Increasing use of technologies such as Chart.js and D3.js allow us to provide data visualisation tools which have enriched how users can find and interact with our data. In the future, this technology will expand to power the new UK Data Service user account area, where users can manage their deposits and order new data easily. We will explore the possibilities of open sourcing our unified interface framework, allowing other organisations to provide an integrated experience for their users. For instance, it could be used to provide the CESSDA Research Infrastructure with a common look and feel for the various components delivered by the Service Providers.

  • Annotation for Transparent Inference (ATI): Selecting a platform for qualitative research based on individual sources
    Colin Elman (Syracuse University)
    Nicholas Weber (University of Washington)
    Diana Kapiszewski (Georgetown University)
    Sebastian Karcher (Syracuse University)
    Dessislava Kirilova (Syracuse University)
    Carole Palmer (University of Washington)


    Social scientists working in rule-bound and evidence-based traditions need to show how they know what they know. The less visible the process that produced a conclusion, the less one can see of the conclusion. A sufficiently diminished view of that process undermines the claim. What an author needs to do to fulfill this transparency obligation differs depending on the nature of the work, the data that were used, and the analyses that were undertaken. For a scholar arriving at a conclusion using a statistical software package to analyze a quantitative dataset, making the claim transparent would include providing the dataset and software commands. Research transparency is a much newer proposition for qualitative social science, especially where granular data are generated from individual sources, and the data are analyzed individually or in small groups. Because the data are not used holistically as a dataset, however, new ways have to be developed to associate the claims with the granular data and their analysis. The Qualitative Data Repository has been working on annotation for transparent inference (ATI) for some time, and has made considerable progress, particularly in specifying what information needs to be surfaced for readers to be able to understand and evaluate published claims. With these requirements in mind, this paper will develop a list of functional specifications and a set of criteria for choosing an annotation standard to use as the basis for ATI.


1B: Data collection challenges (Thu, 2016-06-02)
Chair:Justin Joque

  • Collecting Community Experiences of Conflict
    Celia Russell (JISC)


    How do UN peacekeeping missions gather information about local experiences of conflict? What are the effects of personal networks, tensions with national security services and trust in the credibility of the mission? How do these factors influence the reliability and the accuracy of the data produced?

    Peacekeeping missions gather narratives of security incidents and human rights abuses from local populations in order to monitor the security environment and inform strategic decision-making. The documented incidents create a historical record of the security situation and often constitute one of the few continuous information resources on the conflict. However, relatively little is known about the practices by which this information is amassed, verified and processed.

    In this key informant study, we talked to five former field officers from the UN mission in Darfur to better understand the methods of incident data collection, evaluation and verification. In particular, we looked at the extent to which the ideals as outlined in formal training and guidelines diverge from the experience of data collection on the ground in Darfur.

  • Social Science Archive Meets Historians
    Martin Vavra (Czech Academy of Sciences)


    Presentation reflects experience of Czech Social Science Data Archive (CSDA) based on collaboration with historians from The Institute for the Study of Totalitarian Regimes' institution documenting period of communist rule in Czechia. Continuing work consists in preparation, archiving and publishing of data sets based on data from "classic" archives.

  • The Happiness Analyzer: A Proposed Solution to the Challenges of Measuring Well-Being in Developing Countries
    Paula Lackie (Carleton College)
    Kai Ludwigs (Happiness Research Organisation)
    Faress Bhuivan (Carleton College)


    Measuring well-being in developing countries is still a work in progress. There are numerous issues at all stages of the process but we are developing new mechanisms to cope with them. This presentation will describe the progression of a census of the relative well-being among villagers in Bangladesh in 2013 from a low-budget, high-labor approach into the next iteration of this research; a smartphone app based on the survey tool Happiness Analyzer. Our new tool is designed to help control the interviewer’s location, their accuracy in inputting the information and informs them who they should interview, when and where. The tool works offline on pc, tablet and smartphone with high data security and ethical standards. It allows for the collection of high quality well-being data in developing countries in a comparatively efficient way. This presentation will also describe how basic components of the data life cycle for this project (a GIS, the database process, its metadata scheme, and security protocols) grew or differ from the first iteration (which used low-power smartpens and paper for the data capture) to the second (which will use the new app).

1S1: Embracing databrarianship: Professional opportunities and challenges (Thu, 2016-06-02)
Chair:Lynda Kellam and Kristi Thompson

  • Embracing Databrarianship: Professional Opportunities and Challenges
    Lynda Kellam (University of North Carolina, Greensboro)
    Kristi Thompson (University of Windsor)
    Hailey Mooney (University of Michigan)
    Amber Leahey (Scholars Portal)
    Joel Herndon (Duke University)
    Rob O'Reilly (Emory University)


    This session will explore a variety of issues and responsibilities within data librarianship, drawing on an international community of experts behind a forthcoming book on the theory and practice of the profession. As the number of data librarian positions expands, we bring to light the fundamental opportunities and challenges shaping the field. The session will begin with critical reflection and framing of the current state of data librarianship, followed by a series of snapshots showcasing a mix of case studies and theoretical explorations.
    First, Mooney will share the essential history and background of data's place in the scholarly communication environment in order to ground data librarians within the larger context shaping their work. Herndon and O'Reilly will complement this more theoretical approach with their comparative study of journal replication policies across various social science disciplines. Next, Leahey and Fry will discuss suggestions for metadata best practices. The final presentation will focus on future opportunities for data librarianship with Giesbrecht considering directions in teaching the next generation of data librarians.
    In closing, the editors of the forthcoming book will highlight common themes and concerns across the various chapters with the goal of a broader community discussion about the future contours of the field of databrarianship.

2H: Research replication promotion and service development (Thu, 2016-06-02)
Chair:Katherine McNeill

  • Reuse of Research Data - Re-Writing the Economic History of Denmark Using Research Data
    Steen Andersen (Danish Data Archive)
  • Reproducible Research: A Replication Server for the Social Sciences
    Natascha Schumann (GESIS, Leibniz Institute for the Social Sciences)


    Openness is an important aspect of good scientific practice. In this context, data sharing can be seen as a trust-building mechanism: Making underlying data findable and accessible supports reproducibility and confirmability of research results published in journal articles.
    The presentation gives an overview about the "Replication Server" project, which is an initiative by two leading German sociology journals and GESIS to foster reproducibility in the social sciences. As part of this project, both of the involved journals, "Zeitschrift fur Soziologie" and "Soziale Welt", developed respective data policies. Authors who submit articles based on research data have to agree to make their data available to the community in the case that the article is published. In December 2015 a corresponding service was introduced to support journals in implementing their data policies practically.
    datorium is an existing GESIS service which provides a user-friendly tool for the documentation, upload and publication of social science research data. Researchers describe their data in a standardized manner. Incoming data will be checked with regard to data privacy, coherence and completeness. All datasets receive a persistent identifier (DOI).
    For the purposes of the cooperation with the journals, datorium has been extended by additional features. These make it possible to link all data sets to the corresponding articles and vice versa. Users can easily recognise data sets as belonging to an article from the respective journal. Data are accessible via the datorium webpage and access conditions are definedin accordance with the policies of the respective journals.
    The initiative started with the two mentioned journals but is also open for further partners.

  • 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


  • 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...

  • community

    • LinkedIn
    • Facebook
    • Twitter

    Find out what IASSISTers are doing in the field and explore other avenues of presentation, communication and discussion via social networking and related online social spaces. more...