The effective and long-term application of digital research approaches necessitates new skills like efficient, long-term data management and algorithmic analysis methods for large data sets along with an understanding of the legal issues surrounding copyright and data protection.

Very different kinds of data sets are often used in the economic sciences in particular. These may range from publicly accessible to commercially (protected) content on the web, from historical databases to real-time data on financial market transactions, and from structured to unstructured data, and include numerical data, texts, images, and video materials – from financial statements and interview transcriptions to questionnaires and press releases.

Very disparate types of data necessitate different forms of expert know-how and different types of technical infrastructures.

The technical infrastructure required for digital research includes comprehensive computing resources, large, fast data storage options, research data management, and long-term archiving, plus special software packages and IT solutions. Increasingly complex technical infrastructures call for additional complementary services such as consulting, targeted skills development, and individual support for researchers.

New services and IT solutions frequently emerge from proofs of concept and pilot projects in departments and research institutes, often with the potential to benefit WU as a whole. Such solutions are to be more clearly defined in future to allow the entire WU community wider access to the new know-how.