Documenting social science data: the Data Documentation Initiative (DDI)

Persistent identifiers are familiar for articles, datasets, and people, but the physical objects of research, the rock cores, water samples, and the instruments that measure them, have long lacked stable references. The IGSN for samples and the PIDINST work for instruments extend persistent identification to the physical world, making physical research objects findable, citable, and connectable to the data they produce.

Sharing data about people without exposing the people themselves is one of the hardest problems in research data management. This article distinguishes anonymisation from pseudonymisation, explains the privacy models researchers actually use, k-anonymity, l-diversity and differential privacy, and introduces the practical guidance from the UK Anonymisation Network (UKAN) and the ICO’s anonymisation code. It also confronts the uncomfortable reality that re-identification is often easier than it looks.

Big data describes datasets so large, fast or varied that traditional tools cannot handle them. This guide explains the defining Vs, from volume and velocity to veracity and value, how distributed processing copes, and what big data means for research and FAIR data.