Skip to main content

Data Management for the Humanities


For digital humanities data, a standard has been defined as “codified rules and guidelines for the creation, description and management of digital resources” (Gill and Miller, 2002). Standards can be classified as a de jure standard, which may be mandated by law (or may be used to designate a formal standard), or de facto standards, such as the Text Encoding Initiative, which enjoys widespread use and acceptance.

There are a number of introductions to standards that provide a background on standards and how to participate. Guides are frequently available from national and international standards organizations. In terms of data curation, the basic underlying theme is that standards encourage interoperability, although most guides are written from the viewpoint of business, and not humanities projects.

Those standards of interest to digital curation projects are largely in information and communication technology (ICT). Today, ICT standards are developed by formal Standards Developing Organizations (SDOs), such as the International Organization for Standardization (ISO), as well as national and regional standards organizations.

Finding the relevant standards for humanities data curation may be difficult, because the number of ICT standards is growing and can be fragmented across industry, consortia, academic groups, and standards organizations. Most standards organizations have search portals (such as those provided by ISO, ANSI, and NISO), but a more effective retrieval method might be to locate the list of standards maintained by a relevant community, such as the list for librarians and archivists as maintained by Library of Congress (or the portal developed for archivists, maintained by Society of American Archivists).

There many reasons for abiding by such standards for data curation. Standards make data interchange possible across different programs, application software, or computer systems, especially if the standard has been widely adopted by industry and the academy. Standards also help preserve data for the long-term because the data does not follow not an ad hoc system, which may not be recoverable in the future. As a standard matures through time and eventually become outdated, migration to the newer standard is easier when a project initially followed a standard.

This page adapted from:

Deborah Anderson, University of California, Berkeley