Researchers in the Humanities need an accessible and easy to use digital platform to manage, store, work with and share their research data. Interesting IT-tools already exist. However, for small projects, e.g., PhD projects, pilot projects, and proof of concepts, these technologies can be difficult to use due to researchers’ limited IT-skills, small amounts of funding, limited project time, or need for specific assistance. Most small humanities projects rely on “homemade solutions” using desktop data management tools, such as FileMaker, MSAccess, etc., but the data modelling often does not follow standards. The data itself may be inconsistent. Often researchers only have access to poor tools for export, analyse, and re-use of the data.
Powerful data tools already exist for humanities research. The Data and Service Center for the Humanities (DaSCH) is a national research infrastructure at the University of Basel that includes all disciplines of the humanities. This infrastructure is clearly focused on qualitative data such as interlinked databases, complex data involving different media with annotations (text, facsimile, photographic images, video, and film), rich linkages, and connections. The DaSCH team has developed a unique and powerful software platform, Knora, to provide services, like data maintenance, long-term access, and research and analysis tools for qualitative data. However, with no simple user interface, this platform is not easily used by researchers with small projects or limited resources. Over 30 Swiss projects are currently queuing to get access to Knora, waiting for developer staff support.
This project proposes to develop a Simple User Interface for DaSCH (SUID). The design is an intuitive, easy to use web-based application placed on top of Knora to directly use its powerful data management functionalities. With SUID, the researchers will be able to add data models, search, browse, and work with their qualitative data as easily as they could with a desktop data management tool. In addition, data models and data will automatically follow accepted standards, be interoperable, findable, and re-usable. Researchers and scholars with small data sets will have access to long-term accessibility at minimal cost and time to keep their research data alive, guaranteeing longevity of the data.