Another New Home and Service for Qualitative Data

Previously, we’ve posted a pointer to the news about the launch of a new home for social science qualitative data called QDR. Today, UK Data Services introduced QualiBank.

This is the UK Data Service’s search and browse interface for qualitative data objects allowing searching of the content of text files, such as interviews, essays, open ended questions and reports. It also allows searching of metadata attached to these objects, such as a description of an image or of an audio recording, and it enables hyperlinking to related objects. A citation can be made for a whole object or interview extracts.

At present it is still in a beta version, but it contains only 5 collections that are completely open and these cover in depth interviews, some with politicians, children’s essays about ‘what do you want to be when you grow up’ and WWII morale amongst the British troops and the population. Another ten or so collections which will sit behind authentication are to follow.


Open Data Can Empower Archaeologists

Over the last few years, the DART project collected large amounts of archaeological data, and as part of the project, a group of archaeologists created a purpose-built data repository to catalogue data and make them available, using CKAN, the Open Knowledge Foundation’s (OKF) open-source data catalogue and repository. In their recent blog post of OKF, Anthony Beck and Dave Harrison talk about the project and its progress, and revisit the meaning of open data and open science for archaeologists.

figshare Now Takes Code, Software and Scripts

Last week, figshare announced a forthcoming functionality to sync GitHub repos through the figshare upload page. Today, figshare released this new functionality — now you can upload code, software and scripts, and receive academic credit for them.

Related post by Data Forwards (March 12, 2014): Blog: For Improved Access to Software and Code

Sharing Qualitative Data: The Launch of the Qualitative Data Repository

While data sharing, research transparency, and replication have customarily been prominent concerns for quantitative researchers, they are increasingly being seen as relevant for the qualitative tradition. The Qualitative Data Repository (QDR), which recently came online at Syracuse University, aims to select, ingest, curate, archive, manage, durably preserve, and provide access to digital data used in qualitative and multi-method research in the social sciences.  The repository develops and publicizes common standards and methodologically informed practices for these activities, as well as for the reusing and citing of qualitative data. It is hosted by the Center for Qualitative and Multi-Method Inquiry (a unit of Syracuse University’s Maxwell School of Citizenship and Public Affairs), and funded by the National Science Foundation.

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Blog: Institutional Repositories and Disciplinary Data Repositories

Those who are interested in knowing more about repositories for data sharing and preservation, here are a couple blogs at Data Pub hosted by the California Digital Library (CDL). The three recent blogs by Carly Strasser (CDL), John Kratz (CDL), and Natsuko Nicholls (University of Michigan) feature the subject of institutional and disciplinary data repositories.

How to Find an Appropriate Research Data Repository, an Open Science tool, heps you find a data repository

In our earlier Data Forwards posts (Sept. 19 & Nov 22), we introduced whose goal is to create a global research data repositories. 

Recently, Heinz Pampel, one of the people behind, wrote a blog post on this new emerging Open Science tool that helps researchers to easily identify a suitable repository for their data and thus comply to requirements set out in data policies. covers the following aspects of a research data repository:

  • general information (e.g. short description of the repository, content types, keywords),
  • responsibilities (e.g. institutions responsible for funding, content or technical issues),
  • policies (e.g. guidelines and policies of the repository),
  • legal aspects (e.g. licenses of the database and datasets),
  • technical standards (e.g. APIs, versioning of datasets, software of the repository),
  • quality standards (e.g. certificates, audit processes).

You can learn more about at: