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but how do i *do* qualitative research? bridging the gap between qualitative researchers and methods resources--part 4

Last week Mandy shared ideas about how librarians and other data-support professionals can act as connectors, crusaders and collaborators on campus in order to better provide and develop qualitative research teaching resources. This week we want to build on Mandy’s suggestions by looking a bit more broadly at how librarians and other data-support professionals can help build community around qualitative research at their institutions.

As qualitative research methods are often not the dominant methodologies used in departments and institutions, qualitative researchers may not have a strong support network and may lack colleagues to consult with or learn from. I have regularly heard from graduate students embarking on a qualitative project that they are struggling to learn about qualitative methods on their own because their advisor doesn’t know much about qualitative research or because their department does not offer a course in qualitative research methods. I have also heard from the lone qualitative research faculty member in a department about how isolating that can be. So building a community where qualitative researchers can support, connect with and learn from each other can be very important. Libraries, often seen as neutral ground on campus, have an opportunity to play a unique role as facilitators building this community by connecting people and leveraging resources from across campus.

Some activities that librarians and data support professionals may want to consider to help build a qualitative research community on their campus include:

  • Conduct an environmental scan.  Each campus has a different research support environment, so it may help to first do an environmental scan of your campus to learn who is already doing what to support qualitative research. Document what you learn! Think about how the library can bring together existing resources and build on them.
  • Then, act as a clearinghouse around qualitative methods and support. As you investigate what is going on across your campus related to qualitative research, compile and publicize what you find.  For example, you may create:
  1. lists of campus resources, including labs and software/support tools available,
  2. lists of qualitative methods courses offered in departments across campus,
  3. a directory of faculty members with strengths in qualitative research who agree to act as a resource for others.

As Jill mentioned in our second blogpost, Libguides/research guides are often a great way to capture and share this type of information with the university community and with  library colleagues. Additionally, sharing this information through other campus organizations, such as a graduate resource center, might be a good way to reach an audience with related needs. 

  • Establish/host/contribute to a campus listserv for those with questions or who need help working with qualitative methods and tools.
  • Partner with faculty/graduate students/other campus departments to establish/host a qualitative research support group on your campus. These could be informal brown bags, reading groups, or a place for attendees to meet others and ask questions of those  interested in similar issues.
  • Consider helping to establish a mentor program partnering those new to qualitative research with more experienced researchers.
  • Host/organize/co-sponsor a qualitative research event/symposium - this not only fosters building a vibrant qualitative research community but can help demonstrate the library’s commitment to serving this community.
  • Offer library spaces and resources to support qualitative groups, events, etc.

I hope these suggestions get you started thinking about ways to build a community on your campus. We’d love to hear what you are already doing and we welcome comments here, emails to the IASSIST listserv, the QSSHDIG google group, or directly to the authors, and/or comments in this “Blog Conversations” doc embedded in the QSSHDIG website.

This is the last of our 4-part blog series, “How Do I *Do* Qualitative Research? Bridging the Gap between Qualitative Researchers and Methods Training Resources.” QSSHDIG would love to get more conversations going on the IASSIST blog - there's a section at the bottom of our “Blog Conversations” doc for suggesting future QSSDHIG posts - please do!

But How Do I *Do* Qualitative Research? Bridging the Gap between Qualitative Researchers and Methods Resources--PART 3

Connectors, Crusaders, and Collaborators

Jill’s post from last week detailed ways we data-support professionals can connect researchers to library collections and other information sources for bridging the qualitative methods gap. I’d like to offer more ideas for how we can act not only as connectors but also as crusaders and collaborators on our campuses specifically in the realm of providing and developing qualitative-research teaching resources. 

Because we work with researchers across campus and in various capacities, data-support professionals are often more aware of methods gaps than are the academic departments we support. As such, we are well-positioned to act as intermediaries to address these gaps by connecting researchers to existing resources and crusading for additional resources. For example:

  • We can use our cross-disciplinary knowledge to connect researchers to resources (including other people) about which they may be unaware:
    • “Did you know that the College of Education offers a qualitative methods class that’s open to any discipline?”
    • “Do you know about ResearchTalk's Qualitative Research Summer Intensive?”
    • “Professor X does narrative analysis - maybe you should contact them to see if they’d be on your dissertation committee?”
    • “Professor Y does mixed-methods research - perhaps they’d be willing to consult on the qualitative aspects of your research, and maybe even be a co-investigator?”
  • When we encounter campus researchers experiencing this qualitative methods gap, we can document these occasions and then share them with those who can affect positive change:
    • Tell chairs of academic departments and/or methods professors that graduate students attending qualitative analysis software workshops want this training integrated into their qualitative methods class.
    • Contact the Graduate School and recommend they coordinate student support groups focused on qualitative research [Liz’s post next week will have even more community-building suggestions].
    • Share information gleaned from research consultations and/or instruction sessions with your library administrators to advocate for funds for qualitative-research collections/e-resources and for your own professional development in qualitative methods training.

In addition to connecting and crusading, we data-support professionals can collaborate with other campus researchers to buttress qualitative methods training on campuses. For example:

  • Librarians can draw on their own expertise and also partner with qualitative researchers on campus to offer presentations, workshops, brown bags, etc., aimed at addressing the qualitative methods gap:
    • In my presentation with sociology professor Dr. Ralph LaRossa, “The Logics and Logistics of Qualitative Research”, Dr. LaRossa discusses the methodological steps involved in building theoretically-rich qualitative analyses, then I outline the specific features of NVivo qualitative research software that complement and facilitate these analyses.
    • When teaching qualitative research softwares such as NVivo, Atlas.ti, Quirkos, MAXQDA, or Dedoose, pointedly integrate methodological concepts along with teaching the mechanics (e.g., “Grounded Theory in the Atlas.ti Environment,” “Using NVivo Memos to Document your Methodological Process,” “Developing Variables and Rich Coding Schemas using NVivo Hierarchical Nodes,” “De-Identifying Interview Transcripts in Quirkos,” etc.)

These are just a few ideas for how we can use the three Cs (connecting, crusading, and collaborating) to address this qualitative methods gap. What ideas do you have? What are your successes in this area? Or your slip-ups that we can all learn from?

We welcome comments here, emails to the IASSIST listserv, the QSSHDIG google group, or directly to the authors, and/or comments in this “Blog Conversations” doc embedded in the QSSHDIG website. Also, there's a section at the bottom of the "Blog Conversations" doc for suggesting future QSSDHIG posts - please do!

Stayed tuned for Part 4 of our blog series next week, when Liz Cooper will address how librarians and other data-support professionals can help build community at their institutions around qualitative research.

But How Do I *Do* Qualitative Research? Bridging the Gap between Qualitative Researchers and Methods Resources--PART 2

Mandy kicked off our 4-part blog series last week with an inaugural post that provided background and context for this project, which centers around a specific challenge faced by many qualitative researchers: lack of qualitative methods training.  This post offers some concrete ideas to data-support professionals on how to leverage library collections and other information sources that direct researchers to secondary and tertiary sources on qualitative methods to address this issue.

Possibly the most basic yet high-impact way to bridge the gap between researchers and qualitative methods is to create a LibGuide—or any other online research guide or pathfinder—dedicated to qualitative research resources.  It can be embedded within an existing resource, such as a library’s Data Services page or a course-specific guide, or it can exist as an independent guide unto itself.

Now, I know what you’re thinking: when faced with an instructional or research need, a librarian’s knee-jerk reaction is often, “Let’s make a LibGuide!”  While research guides aren’t necessarily appropriate for every topic or service we provide as information and data specialists (i.e., LibGuides aren’t a panacea, per se), they can be a useful didactic medium for culling and delivering information and resources specific to qualitative research methods.   

Online research guides, like LibGuides, allow researchers to benefit from the guidance and expertise of a data-support professional in an autonomous, self-paced manner.  This type of learning object is well-suited for researchers who fit the profile Mandy described in her introductory post for this series: those who aren’t getting formal qualitative methods training and need to get up to speed quickly on their own, and/or researchers with varying degrees of qualitative methods knowledge and experience who would like a set of materials, sources, and resources to which they can refer back periodically.  The portability of a LibGuide also makes it convenient for use by data-support professionals in mediated settings, such as consultations or instruction sessions.  And at institutions where demand for research methods and tools training outstrips an individual or staff’s capacity to provide one-on-one or even course-embedded support, a LibGuide can solve the scalability problem for a large and diverse set of needs (although, obviously, not all of them).  Lastly, LibGuides aren’t just for researchers; they also serve to assist colleagues and fellow information and data specialists in providing reference and research services at an institution (and beyond) and are an effective tool for cross-training.  This last point is relevant especially for fairly specialized, niche areas of expertise, like qualitative research methods.

 A number of qualitative research guides already exist and are worth checking out (e.g., Duke University Libraries’ guide on Qualitative Research by Linda Daniel, UCSF Library’s Qualitative Research Guide by Evans Whitaker).  Below are some suggestions for content to include—with a focus on resources related to learning about qualitative methods—if one were to consider creating anew or building on an existing qualitative research guide.

Select bibliography of relevant literature

A centralized bibliography, or simply citations/links dispersed throughout a guide, can be useful in directing users to relevant secondary and tertiary sources to learn more about qualitative research methods.  Citations to the following literature types may be appropriate to include:  

As a companion, it may be useful to link to relevant catalogs and social-sciences databases to search for additional literature and research.  However, not all catalogs and bibliographic databases index research methods, and even those that do often don’t index qualitative methods with appropriate granularity.  Thus, it may be necessary to provide tips on how best to search for studies that employ qualitative methods (e.g., NYU Libraries’ guide on Locating Qualitative Research by Susan Jacobs).  This way, a guide delivers select sources but also teaches users how to find additional methods-related sources themselves.

Links to subscription-based resources

There are a number of specialized library databases designed for quick reference and/or in-depth, self-guided learning, and these serve as rich fonts of information about qualitative methods.  Three possible resources that fit this bill are:   

  • Credo Reference
    While not specific to research methods, Credo is a multidisciplinary, searchable collection of digitized reference works (e.g., dictionaries, encyclopedias, and handbooks) that provide helpful background information on a topic but also act as springboards to connect users to further readings and cross-references.  Credo can serve as a good starting point for researchers looking to learn more about qualitative methods in general or about a particular methodology.   
  • Sage Research Methods Online (SRM)
    SRM is an online multimedia collection devoted to research methods (qualitative and quantitative), with a special emphasis on research skills training.  It includes e-versions of SAGE’s Little Blue Books, an instructional series on qualitative research methods, as well as many other searchable, full-text interdisciplinary SAGE reference and journal sources that allow users to deep-dive into a particular method at each stage of the research lifecycle.  SRM also provides resources for teaching qualitative methods, including case studies, sample datasets, and instructional videos.

  • Oxford Bibliographies Online (OBO)
    OBO offers access to online, peer-reviewed, annotated bibliographies that are organized by discipline and are written by experts in their fields.  One can find entire bibliographies or portions of a bibliography dedicated to qualitative methods in a given field of social science (e.g., sociology, political science) or to a particular qualitative methodology (e.g., anthropology, education).  This makes OBO a good source of information for discipline-specific qualitative research methods.  

In addition to researchers, these resources can be indispensible to data-support professionals who are asked to consult on research projects using qualitative methods outside their own specializations, or who are asked to consult with researchers who sit in (or between) disciplines with which they are less familiar or comfortable.

List of professional development and ongoing learning opportunities

Researchers who are new to a qualitative research method may want to learn more about it in an interactive manner beyond (or in lieu of) the classroom.  Opportunities to do so are plentiful and varied, and may take the following forms:

I hope you have enjoyed my suggestions in this post!  They are by no means exhaustive.  I would love to here what you think, what you would add, or what you’re already using on your guides to address the qualitative methods gap discussed in this series of blog posts.  

We welcome comments here, emails to the IASSIST listserv, the QSSHDIG google group, or directly to the authors, and/or comments in this “Blog Conversations” doc embedded in the QSSHDIG website. Also, there's a section at the bottom of the "Blog Conversations" doc for suggesting future QSSDHIG posts - please do!

Stayed tuned for Part 3 of our blog series next week when Mandy Swygart-Hobaugh will share ideas for developing and providing training resources in collaboration with faculty and academic departments that are mindful of the qualitative methods gap.

But How Do I *Do* Qualitative Research? Bridging the Gap between Qualitative Researchers and Methods Resources--PART 1

The IASSIST Qualitative Social Science & Humanities Data Interest Group (QSSHDIG) was created in October 2016, its central purpose: to foster conversations regarding the needs of researchers who generate qualitative data, and what types of services librarians and other information professionals can develop to support these researchers in managing their data/source materials throughout the research lifecycle.

This four-post blog series engages in one particular conversation: challenges researchers face in terms of a lack of qualitative methods training, and strategies for how data-support professionals can address these challenges. The following QSSHDIG members are the series authors:

  • Jill Conte, Social Sciences Librarian at New York University
  • Liz Cooper, Social Sciences Librarian at the University of New Mexico
  • Mandy Swygart-Hobaugh, Social Sciences Librarian at Georgia State University

To foster conversation, we welcome comments here, emails to the IASSIST listserv, the QSSHDIG google group, or directly to the authors, and/or comments in this “Blog Conversations” doc embedded in the QSSHDIG website. Also, there's a section at the bottom of the "Blog Conversations" doc for suggesting future QSSDHIG posts - please do!

Why have this conversation?

Many social science researchers (students and faculty alike) are increasingly conducting qualitative research while lacking formal training in qualitative methods. This may be due to various factors, including but not limited to the following:

  • their particular discipline does not widely embrace qualitative research,
  • their discipline just recently began emphasizing mixed methods (using qualitative and quantitative methods) when previously it was predominantly quantitative-based,
  • they are in an interdisciplinary academic program without a strong research methods training component.

Those of us who offer training sessions on qualitative data analysis software (such as NVivo, Atlas.ti, Quirkos, or Dedoose) often experience researchers coming to these sessions without the methodological background to *do* qualitative research or understand what the software can/cannot do for them - sometimes hoping that the software will have the “magic button” to solve their lack of training. Similarly, as social science liaison librarians we often witness this qualitative methods gap during our research consultations. Although this dilemma of lack of methods training is not unique to qualitative research (i.e., researchers lacking quantitative research training are known to attend statistical software training sessions), when compared to their quantitative counterparts, qualitative researchers often have less resources for support and for building necessary skills.

The three posts in the remainder of this blog series will offer concrete strategies for how data-support professionals can act as bridges between social science researchers and the resources they need to strengthen their qualitative research and methodologies skills:

  • Jill Conte’s post will offer suggestions for connecting researchers with secondary and tertiary sources for qualitative research training. [to be posted Monday, July 24] 
  • Mandy Swygart-Hobaugh’s post will share ideas for developing and providing training resources in collaboration with faculty and academic departments that are mindful of this methods gap. [to be posted Monday, July 31] 
  • Liz Cooper’s post will address how librarians and other data-support professionals can help build community at their institutions around qualitative research. [to be posted Monday, August 7] 

IASSIST 2016 Program At-A-Glance, Part 2: Data infrastructure, data processing and research data management

 

Here's another list of highlights from IASSIST2016 which is focusing on the data revolution. For previous highlights, see here.

Infrastructure

  • For those of you with an interest in technical infrastructure, the University of Applied Sciences HTW Chur will showcase an early protype MMRepo (1 June, 3F), whose function is to store qualitative and quantitative data into one big data repository.
  • The UK Data Service will present the following panel "The CESSDA Technical Framework - what is it and why is it needed?", which elaborates how the CESSDA Research Infrastructure should have modern data curation techniques rooted in sophisticated IT capabilities at its core, in order to better serve its community.

  • If you have been wondering about the various operational components and the associated technology counterparts involved with running a data science repository, then the presentation by ICPSR is for you. Participants in that panel will leave with an understanding of how the Archonnex Architecture at ICPSR is strengthening the data services offered to new researchers and much more.

Data processing

Be sure to check out the aforementioned infrastructure offerings if you’re interested in data processing, but also check out a half-day workshop on 31 May, “Text Processing with Regular Expressions,” presented by Harrison Dekker, UC Berkeley, that will help you learn regular expression syntax and how to use it in R, Python, and on the command line. The workshop will be example-driven.

Data visualisation

If you are comfortable working with quantitative data and are familiar with the R tool for statistical computing and want to learn how to create a variety of visualisations, then the workshop by the University of Minnesota on 31 May is for you. It will introduce the logic behind ggplot2 and give participants hands-on experience creating data visualizations with this package. This session will also introduce participants to related tools for creating interactive graphics from this syntax.

Programming

  • If you’re interesting in programming there’s a full-day Intro to Python for Data Wrangling workshop on 31 May, led by Tim Dennis, UC San Diego,  that will provide tools to use scientific notebooks in the cloud, write basic Python programs, integrate disparate csv files and more.

  • Also, the aforementioned Regular Expressions workshop also on 31 May will offer  in-workshop opportunities  to working with real data and perform representative data cleaning and validation operations in multiple languages.

Research data management

  • Get a behind-the-scenes look at data management and see how an organization such as the Odum Institute manages its archiving workflows, head to “Automating Archive Policy Enforcement using Dataverse and iRODS” on 31 May with presenters from the UNC Odom Institute, UNC Chapel Hill. ’Participants will see machine actionable rules in practice and be introduced to an environment where written policies can be expressed in ways an archive can automate their enforcement.

  • Another good half-day workshop, targeted to for people tasked with teaching good research data management practices to researchers is  “Teaching Research Data Management Skills Using Resources and Scenarios Based on Real Data,” 31 May, with presenters from ICPSR, the UK Data Archive and FORS. The organisers of this workshop will showcase recent examples of how they have developed teaching resources for hands-on-training, and will talk about successes and failures in this regard.

Tools

If you’re just looking to add more resources to your data revolution toolbox, whether it’s metadata, teaching, data management, open and restricted access, or documentation, here’s a quick list of highlights:

  • At Creating GeoBlacklight Metadata: Leveraging Open Source Tools to Facilitate Metadata Genesis (31 May), presenters from New York University will provide hands-on experience in creating GeoBlacklight geospatial metadata, including demos on how to capture, export, and store GeoBlacklight metadata.

  • DDI Tools Demo (1 June). The Data Documentation Initiative (DDI) is an international standard for describing statistical and social science data.

  • DDI tools: No Tools, No Standard (3 June), where participants will be introduced to the work of the DDI Developers Community and get an overview of tools available from the community.

Open-access

As mandates for better accessibility of data affects more researchers, dive into the Conversation with these IASSIST offerings:

Metadata

Don’s miss IASSIST 2016’s offerings on metadata, which is the data about the data that makes finding and working with data easier to do. There are many offerings, with a quick list of highlights below:

  • Creating GeoBlacklight Metadata: Leveraging Open Source Tools to Facilitate Metadata Genesis (Half-day workshop, 31 May), with presenters from New York University

  • At Posters and Snacks on 2 June, Building A Metadata Portfolio For Cessda, with presenters from the Finnish Social Science Data Archive; GESIS – Leibniz-Institute for the Social Sciences; and UK Data Service

Spread the word on Twitter using #IASSIST16. 


A story by Dory Knight-Ingram (
ICPSR)

Interested in the “data revolution” and what it means for research? Here’s why you should attend IASSIST2016

 

Part 1: Data sharing, new data sources and data protection

IASSIST is an international organisation of information technology and data services professionals which aims to provide support to research and teaching in the social sciences. It has over 300 members ranging from data archive staff and librarians to statistical agencies, government departments and non-profit organisations.

The theme of this year’s conference is Embracing the ‘data revolution’: opportunities and challenges for research” and it is the 42nd of its kind, taking place every year. IASSIST2016 will take place in Bergen, Norway, from 31 May to 3 June, hosted by NSD - Norwegian Centre for Research Data.

Here is a first snapshot of what is there and why it is important.

Data sharing

If you have ever wondered whether data sharing is to the advantage of researchers, there will be a session led by Utrecht University Library exploring the matter. The first results of a survey which explores personal beliefs, intention and behaviour regarding the sharing of data will also be presented by GESIS. The relationship between data sharing and data citation, relatively overlooked until now, will then be addressed by the Australian Data Archive.

If you are interested in how a data journal could incentivise replications in economics, you should think about attending a session by ZBW Leibniz Information Centre for Economics which will present some studies describing the outcome of replication attempts and discuss the meaning of failed replications in economics.

GESIS will then look into improving research data sharing by addressing different scholarly target groups such as individual researchers, academic institutions, or scientific journals, all of which place diverse demands on a data sharing tool. They will focus on the tools offered by GESIS as well as a joint tool, “SowiDataNet”, offered together with the Social Science Centre Berlin, the German Institute for Economic Research, and the German National Library of Economic.

The UKDA and UKDS will present a paper which seeks to explore the role that case studies of research can play in regard to effective data sharing, reuse and impact.

The Data Archive in Finland (FSD) will also be presented as a case study of an archive that is broadening its services to the health sciences and humanities, disciplines in which data sharing practices have not yet been established.

If you’d like to know more about data accessibility, which is being required by journals and mandated by government funders, join a diverse group of open data experts as IASSIST dives into open data dialogue that includes presentations on Open Data and Citizen Empowerment and 101 Cool Things to do with Open Data as part of the “Opening up on open data workshop.” Presenters will be from archives from across the globe.

New data sources

A talk entitled “Data science: The future of social science?” by UKDA will introduce its conceptual and technical work in developing a big data platform for social science and outline preliminary findings from work using energy data.

If you have been wondering about the role of social media data in the academic environment, the session by the University of California will include an overview of the social media data landscape and the Crimson Hexagon product.

The three Vs of big data, volume, variety and velocity, are being explored in the “Hybrid Data Lake” being built by UKDA using the Universal Decimal Classification platform and expanding “topics” search while using big data management. Find out more about it as well as possible future applications.

Data protection

If you follow data protection issues, the panel on “Data protection: legal and ethical reviews” is for you, starting off with a presentation of the Administrative Data Research Network's (ADRN) Citizen's Panel, which look at public concerns about research using administrative data, the content of which is both personal and confidential. The ADRN was set up as part of the UK Government’s Big Data initiative as a UK-wide partnership between universities, government bodies, national statistics authorities and the wider research community.

The next ADRN presentation within this session will outline their application process and the role of the Approvals Panel in relation to ethical review. The aim is “to expand the discussion towards a broader reflection on the ethical dilemmas that administrative data pose”, as well as present some steps taken to address these difficulties.

NSD will then present the new EU General Data Protection Regulation (GDPR), recently adopted at EU level, and explain how it will affect data collection, data use, data preservation and data sharing. If you have been wondering how the regulation will influence the possibilities for processing personal data for research purposes, or how personal data are defined, what conditions apply to an informed consent, or in which cases it is legal and ethical to conduct research without the consent of the data subjects, this presentation is for you.

The big picture

Wednesday 1 June will kick-off with a plenary entitled “Data for decision-makers: Old practice - new challenges” by Gudmund Hernes, the current president of the International Social Science Council and Norway’s former Minister of Education and Research 1990-95, and Minister of Health 1995-97.

The third day of the conference (2 June) will begin with a plenary - “Embracing the ‘Data Revolution’: Opportunities and Challenges for Research’ or ‘What you need to know about the data landscape to keep up to date”, by Matthew Woollard, Director of the UK Data Archive at the University of Essex and Director of the UK Data Service.

If you want to know more about the three European projects under the framework of the Horizon 2020 programme of the European Commission that CESSDA is involved in, one on big data (Big Data Europe - Empowering Communities with Data Technologies), another on - strengthening and widening the European infrastructure for social science data archives (CESSDA SaW) and a third on synergies for Europe's Research Infrastructures in the Social Sciences (SERISS), this panel is for you.  

"Don't Hate the Player, Hate the Game": Strategies for Discussing and Communicating Data Services” considers how libraries might strategically reconsider communications about data services.

Keep an eye on this blog for more news in the run-up to IASSIST2016.

Find out more on the IASSIST2016 website.

Spread the word on Twitter using #IASSIST16.

We are looking forward to seeing you in Bergen! 


A story by Eleanor Smith (CESSDA)

Latest Issue of IQ Available! Data Documentation Initiative - Results, Tools, and Further Initiatives

Welcome to the third issue of Volume 39 of the IASSIST Quarterly (IQ 39:3, 2015). This special issue is guest edited by Joachim Wackerow of GESIS – Leibniz Institute for the Social Sciences in Germany and Mary Vardigan of ICPSR at the University of Michigan, USA. That sentence is a direct plagiarism from the editor’s notes of the recent double issue (IQ 38:4 & 39:1). We are very grateful for all the work Mary and Achim have carried out and are developing further in the continuing story of the Data Documentation Initiative (DDI), and for their efforts in presenting the work here in the ASSIST Quarterly.

As in the recent double issue on DDI this special issue also presents results, tools, and further initiatives. The DDI started 20 years ago and much has been accomplished. However, creative people are still refining and improving it, as well as developing new areas for the use of DDI.

Mary Vardigan and Joachim Wackerow give on the next page an overview of the content of DDI papers in this issue.

Let me then applaud the two guest editors and also the many authors who made this possible:

  • Alerk Amin, RAND Cooperation, www.rand.org, USA
  • Ingo Barkow, Associate Professor for Data Management at the University for Applied Sciences Eastern Switzerland (HTW Chur), Switzerland
  • Stefan Kramer, American University, Washington, DC, USA
  • David Schiller, Research Data Centre (FDZ) of the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB)
  • Jeremy Williams, Cornell Institute for Social and Economic Research, USA
  • Larry Hoyle, senior scientist at the Institute for Policy & Social Research at the University of Kansas, USA
  • Joachim Wackerow, metadata expert at GESIS - Leibniz Institute for the Social Sciences, Germany
  • William Poynter, UCL Institute of Education, London, UK
  • Jennifer Spiegel, UCL Institute of Education, London, UK
  • Jay Greenfield, health informatics architect working with data standards, USA
  • Sam Hume, vice president of SHARE Technology and Services at CDISC, USA
  • Sanda Ionescu, user support for data and documentation, ICPSR, USA
  • Jeremy Iverson, co-founder and partner at Colectica, USA
  • John Kunze, systems architect at the California Digital Library, USA
  • Barry Radler, researcher at the University of Wisconsin Institute on Aging, USA
  • Wendy Thomas, director of the Data Access Core in the Minnesota Population Center (MPC) at the University of Minnesota, USA
  • Mary Vardigan, archivist at the Inter-university Consortium for Political and Social Research (ICPSR), USA
  • Stuart Weibel, worked in OCLC Research, USA
  • Michael Witt, associate professor of Library Science at Purdue University, USA.

I hope you will enjoy their work in this issue, and I am certain that the contact authors will enjoy hearing from you
about new potential results, tools, and initiatives.

Articles for the IASSIST Quarterly are always very welcome. They can be papers from IASSIST conferences or other
conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing
a presentation, give a thought to turning your one-time presentation into a lasting contribution to continuing development. As an author you are permitted ‘deep links’ where you link directly to your paper published in the IQ. 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 session participants, and will be readily available on the IASSIST website at http://www.iassistdata.org.

Authors are very welcome to take a look at the instructions and layout: http://iassistdata.org/iq/instructions-authors. Authors can also contact me via e-mail: kbr@sam.sdu.dk.

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
September 2015
Editor

New Perspectives on DDI

This issue features four papers that look at leveraging the structured metadata provided by DDI in
different ways. The first, “Design Considerations for DDI-Based Data Systems,“ aims to help decisionmakers
by highlighting the approach of using relational databases for data storage in contrast to
representing DDI in its native XML format. The second paper, “DDI as a Common Format for Export
and Import for Statistical Packages,” describes an experiment using the program Stat/Transfer to
move datasets among five popular packages with DDI Lifecycle as an intermediary format. The paper
“Protocol Development for Large-Scale Metadata Archiving Using DDI Lifecycle” discusses the use
of a DDI profile to document CLOSER (Cohorts and Longitudinal Studies Enhancement Resources,
www.closer.ac.uk), which brings together nine of the UK’s longitudinal cohort studies by producing a
metadata discovery platform (MDP). And finally, “DDI and Enhanced Data Citation“ reports on efforts in
extend data citation information in DDI to include a larger set of elements and a taxonomy for the role
of research contributors.

Mary Vardigan - vardigan@umich.edu
Joachim Wackerow - Joachim.Wackerow@gesis.org

Looking Back/Moving Forward - Reflections on the First Ten Years of Open Repositories

Open Repositories conference celebrated its first decade by having four full days of exciting workshops, keynotes, sessions, 24/7 talks, and development track and repository interest group sessions in Indianapolis, USA. All the fun took place in the second week of June. The OR2015 conference was themed "Looking Back/Moving Forward: Open Repositories at the Crossroads" and it brought over 400 repository developers and managers, librarians and library IT professionals, service providers and other experts to hot and humid Indy.

Like with IDCC earlier this year, IASSIST was officially a supporter of OR2015. In my opinion, it was a worthy investment given the topics covered, depth and quality of presentations, and attendee profile. Plus I got to do what I love - talk about IASSIST and invite people to attend or present in our own conference.

While there may not be extremely striking overlap with IASSIST and OR conferences, I think there are sound reasons to keep building linkages between these two. Iassisters could certainly provide beneficial insight on various RDM questions and also for instance on researchers' needs, scholarly communication, reusing repository content, research data resources and access, or data archiving and preservation challenges. We could take advantage of the passion and dedication the repository community shows in making repositories and their building blocks perfect. It's quite clear that there is a lot more to be achieved when repository developers and users meet and address problems and opportunities with creativity and commitment.

 

While IASSIST2015 had a plenary speaker from Facebook, OR had keynote speakers from Mozilla Science Lab and Google Scholar. Mozilla's Kaitlin Thaney skyped a very interesting opening keynote (that is what you resort to when thunderstorms prevent your keynote speaker from arriving!) on how to leverage the power of the web for research. Distributed and collaborative approach to research, public sharing and transparency, new models of discovery and freedom to innovate and prototype, and peer-to-peer professional development were among the powers of web-enabled open science.
 
Anurag Acharya from Google gave a stimulating talk on pitfalls and best practices on indexing repositories. His points were primarily aimed at repository managers fine-tuning their repository platforms to be as easily harvestable as possible. However, many of his remarks are worth taking into account when building data portals or data rich web services. On the other, hand it can be asked if it is our job (as repository or data managers) to make things easy for Google Scholar, or do we have other obligations that put our needs and our users first. Often these two are not conflicting though. What is more notable from my point of view was Acharya's statement that Google Scholar does not index other research outputs (data, appendixes, abstracts, code…) than articles from the repositories. But should it not? His answer was that it would be lovely, but it cannot be done efficiently because these resources are not comprehensive enough, and it would not possible for example to properly and accurately link users to actual datasets from the index. I'd like to think this is something for IASSIST community to contemplate.

Open Researcher and Contributor ID (ORCID) had a very strong presence in OR2015. ORCID provides an open persistent identifier that distinguishes a researcher from every other researcher, and through their API interfaces that ID can be connected to organisational and inter-organisational research information systems, helping to associate researchers and their research activities. In addition to a workshop on ORCID APIs there were many presentations about ORCID integrations. It seems that ORCID is getting close to reaching a critical mass of users and members, allowing it to take big leaps in developing its services. However, it still remains to be seen how widely it will be adopted. For research data archiving purposes having a persistent identifier provides obvious advantages as researchers are known to move from one organisation to another, work cross-nationally, and collaborate across disciplines.

Many presentations at least partly addressed familiar but ever challenging research data service questions on deposits, providing data services for the researcher community and overcoming ethical, legal or institutional barriers, or providing and managing a trustworthy digital service with somewhat limited resources. Check for example Andrew Gordon's terrific presentation on Databrary, a research-centered repository for video data. Metadata harmonisation, ontologies, putting emphasis on high quality metadata and ensuring repurposing of metadata were among the common topics as well, alongside a focus on complying with standards - both metadata and technical.

I see there would be a good opportunity and considerable common ground for shared learning here, for example DDI and other metadata experts to work with repository developers and IASSIST's data librarians and archivists to provide training and take part in projects which concentrate on repository development in libraries or archives.

Keynotes and a number of other sessions were live streamed and recorded for later viewing. Videos of keynotes and some other talks and most presentation slides are available already, rest of the videos will be available in the coming weeks.

Data Visualization Support Roles

Hello IASSISTers,

Since our last entry, the Data Visualization Working Group (DVIG) has been connecting through email to gather information and share knowledge about data visualization tools, best practices, teaching, and events of interest. A major theme of conversation has been open source programming frameworks like R statistical packages to conduct visualization.  Many other non-programming tools have also been discussed and shared. The question of tools is not an easy one, and there are a lot out there!

For a list of tools (not comprehensive) see: DVIG Tool list (opens in Pearl Trees)

What are we doing with visualization?

Some members are considering licensing software for their institutions, including licensed software such as Tableau (http://www.tableausoftware.com/). Others are considering adding visualization features to existing data repositories or portals, while others are considering these for upcoming data collections and repository development. A discussion about the creation of a blog series related to experiences with different repository software has been mentioned, as well as, a list of criteria for discerning between licensed software and repository systems. Many are concerned about the scalability of tools and are interested in the application of visualization techniques across disciplines and groups.

Now, there are a lot of ways to visualize data. The following diagram describes the process of creating and making sense of visualizations, and might be helpful for our discussions and understanding.

Process – Information Workflow

 

Taken from: Aisch, Gregory. Using Data Visualization to Find Insights in Data. Data Journalism Handbook, Open Knowledge Foundation. http://datajournalismhandbook.org/1.0/en/understanding_data_7.html . 2014-07-11.

Regardless of where we are at, we are all in agreement that data visualization is COOL! And it needs support. Unfortunately the skills needed to perform data visualization and “data wrangling” projects are not taught widely in higher education, however, some institutions have made strides to develop these core skills and training and others are now developing curriculum. 

Here is a short list of current courses and teaching materials:

University of Washington, Data Visualization (winter 2014)

New York University, Certificate in Data Visualization

Columbia University, Data Visualization

University of Kansas, Managing Research Data in the Social Sciences (incl data wrangling) (summer 2014)

University of British Columbia, Information Visualization

University of Toronto, Big Data Analytics (fall 2014)

A major theme at this past IASSIST Conference was data support roles. Data visualization topics such as R programming package, developing library support services, teaching tools and undergraduate pedagogy, current research, were very well attended. The IASSIST community is engaged in Data Visualization at almost all stages of the process workflow (see above).

Libraries can play an important role in supporting researchers…

Libraries serve as an ideal place on campus to support visualization for a number of reasons. Data visualization is a truly interdisciplinary activity seeing a growing importance in a wide variety of fields. Even the techniques involved draw on diverse fields from statistics to computer science to design. As such an interdisciplinary field and on that benefits so many diverse fields, visualization has a natural home in the library. Rather than individual disciplines developing support, knowledge and tools for visualization these advances can be shared across campus by making the library a central point of visualization activities.

Furthermore, providing support for data visualization in the library can amplify other data related activities. As libraries increasingly move to collecting, managing and preserving complex datasets offering services that can assist in making sense of that data will make it all the more valuable. Moreover, visualization services provide additional opportunities to inform researchers of support for research and data within libraries.

Data Viz at University of Michigan Libraries

At the University of Michigan we are in the process of developing our services to support visualization. Historically our support for data visualization has developed in two different parts of the library. Both our 3D Lab (part of our Digital Media Commons group) and our Spatial and Numeric Data Services (SAND – Part of the Clark Library for Maps, Government Information and Data Services) have supported and continue to support various types of data visualization, mapping and working with complex types of data. In SAND, where I am located, we focus primarily on helping researchers, students and faculty through consultations where we teach people techniques and how to use appropriate software rather than producing finished products. While we all have our favorite pieces of software we attempt to balance our patron’s familiarity and the most effective software for their goals. We also offer open workshops and course instruction on various data visualization and mapping topics.

While we would ideally like to be able to support the entire spectrum of data visualization activities, one of the most challenging aspects of supporting visualization is providing a scalable service or at least supporting a variety of scales to best benefit one’s campus. Providing consultations around producing graphs and charts for presentations and publications seems easily within the scope and scale of traditional library consultations, but providing production services and assisting with large scale projects such as the creation of interactive web environments or visualizing terabytes of data often requires more time and effort that we usually have to devote to individual projects. Still, libraries, in providing a space for whatever assistance is possible and helping researchers and students understand the resources required for a given project, can offer an invaluable service to our campus communities.

Supported projects at the University of Michigan:

19th Century Acts - http://19thcenturyacts.com/

Mapping Moby Dick - http://record.umich.edu/articles/technology-meets-literature-students-map-classic-novel

 

Many thanks for all the collaboration on the DVIG list, 

Amber Leahey (University of Toronto) & Justin Joque (University of Michigan)

Announcing the Release of the CRDCN Dataset Builder

The Canadian Research Data Centre Network (CRDCN) is pleased to announce the release of the CRDCN Dataset Builder.

In collaboration with Statistics Canada and Metadata Technology North America, the Dataset Builder allows researchers working (or intending to work) in a Canadian RDC the ability to browse, search for and select variables in the Statistics Canada surveys currently housed in the RDCs. 

Utilizing DDI Lifecycle metadata, the Dataset Builder allows researchers to find and select variables, as well as produce SAS, SPSS or Stata syntax to help read in and format the variables, and produce customized documentation (Layout and Codebooks) for the dataset they create using the app. 

 A one-page installation, setup and use guide can be found at this link, with a link to more descriptive documentation if necessary: https://docs.google.com/document/d/135Eq2fwVRtlMdENpQjmZe5Zjm1OFGImCxtyWeV_7sdI [docs.google.com]

The application is open-source software, so please contact Metadata Technology NA if you're interested in contracting them to customize this application for your own organization.

Please contact Dave Haans (dave.haans@utoronto.ca) for more information.

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