The idea that data management does not apply to arts, humanities and social sciences is a little old-fashioned. Researchers in these disciplines frequently collect and analyse both quantitative and qualitative data that must be safely captured, catalogued, stored, shared and protected.

Your research data

In these fields, the concepts of “data” and “evidence” are very nuanced. However, virtually all information you record during your research counts as such. Here are some common (yet not exhaustive) examples of data captured in the arts, humanities [1] and social sciences [2]:

• Focus group notes
• Fieldwork notes
• Finding aids [3]
• Interviews (audio/video) and transcriptions
• Interview coding
• Meeting minutes
• Text corpus/corpora [4]
• Text with markup [5]
• Thematic research collections [6]
• Digitised [7] books, paintings and other works of art (e.g. the Europeana [8] collections).

As a researcher in these disciplines, you will often collect evidence empirically and you may be more likely than other disciplines to collect personally identifiable information with direct identifiers. Make sure you consider both the ethical and the legal requirements that apply to your data when planning for its collection, sharing and long-term preservation. You can consult the guidance provided by CESSDA [9], DANS [10] , or the ICPSR [11].

Digital humanities and social sciences

Digital humanities and digital social sciences [12] have risen as interdisciplinary research fields that use information sciences as a research tool in the traditional humanities and social sciences domains. Digital humanities and social sciences use technology to address some research questions more effectively and on a larger scale. This includes two approaches [13]:

• ‘Big data’ digital humanities and social sciences analyse large and interconnected datasets using cutting-edge data processing and interpretation tools and methods.
• ‘Small data’ digital humanities and social sciences use digital tools to perform the analysis and interpretation of smaller and simpler datasets.

If you are planning to embrace digital humanities and social sciences, this article [14] will help you understand how these methods can contribute to your research and to find examples of existing research projects.