Data Science Journal

Scope

The Data Science Journal (DSJ) was founded in 2002 to help build knowledge and understanding of how data practices can advance research and human knowledge. Recent decades have seen an unprecedented explosion in the human capacity to acquire, store, and manipulate data and information. We are experiencing an historic revolution in knowledge creation, communication, and utilisation. DSJ explores what that means for the conduct of research and data management. We regard data science as the ‘science of data’ — the evidence-based study of the socio-technical developments and transformations that affect science policy; the conduct and methods of research; and the data systems, standards, and infrastructure that are integral to research. A central goal of DSJ is to ensure that data are used in the most effective, efficient, and ethical way in promoting knowledge and learning. It is a peer-reviewed, open-access, electronic journal that is relevant to all sciences as well as the empirical humanities. The scope of the journal includes descriptions of data systems; their implementations, applications, infrastructures, software, legal, reproducibility, and transparency issues; the availability and usability of complex datasets; and with a particular focus on the principles, policies, and practices for data preservation and reuse.