Study title

SQUAD - Smart Qualitative Data: Methods and Community Tools for Data Mark-Up is a demonstrator project that will explore methodological and technical solutions for exposing digital qualitative data to make them fully shareable, exploitable and archivable for the longer term. Such tools are required to exploit fully the potential of qualitative data for adventurous collaborative research using web-based and e-science systems. An example of the latter might be linking multiple data and information sources, such as text, statistics and maps. Initially, the project deals with specifying and testing flexible means of storing and marking-up, or annotating, qualitative data using universal standards and technologies, through eXtensible Mark-up Language (XML).A community standard, or schema, will be proposed that will be applicable to most kinds of qualitative data. The second strand investigates optimal requirements for describing or 'contextualising' research data (e.g. interview setting or interviewer characteristics), aiming to develop standards for data documentation. The third strand aims to use natural language processing technologies to develop and implement user-friendly tools for semi-automating processes to prepare marked-up qualitative data. Finally, the project will investigate tools for publishing the enriched data and contextual information to web-based systems and for exporting to preservation formats.