Context grabbing: Assigning metadata in large document collections

Abstract

Classification schemes are an important issue in the collective use of large document collections. We have investigated the classification of technical documentations in two engineering domains: a steel mill and a sewerage plant company. In both cases we found a coexistence of different classification schemes and problems resulting from distributed local archives. In supporting human actors to maintain different classifications schemes while working on a common archive, we developed the concept of context grabbing. It allows assigning context information efficiently in the form of metadata. Based on a document management system, a tool kit for context grabbing was developed. Its evaluation in a sewerage service company allows us to comment on important aspects of understanding the role of classifications in collaborative work.