Enabling a Common Understanding in a Community

In order for a community (e.g. a workgroup, taskforce, project/product team, department, etc.) to realize its objectives, it is beneficial that its members have a common set of the ideas, concepts and other semantic units that are relevant for realizing these objectives. The ability to realize such a common understanding, and to demonstrate that this is actually the case, is a critical capability for success.

The Terminology Engine (v2) is a set of specifications and tools that (technically) facilitate such capabilities, by recognizing that each community wants (and needs):

its own terminology that can develop over time (producing different versions);
to autonomously define specific terms, create its particular documentation for its concepts or other semantic units;
to 'import' (borrow, include, use) specific terms that are defined by other communities;
to make its own terminologies available for other communities to 'import';
to generate tangible artifacts such as glossaries, dictionaries and other documentation (specifications, white papers, etc.) that actually use the terminology as committed to by (each member of) the community.

This technical support must, however, be complemented with methods that a community will actually use to produce and maintain its terminology. We need to decide whether or not to provide guidance for that as well.

Editor's note

(Agredo-Delgado, et. al., 2021)¹ have tested a process for constructing a shared understanding in computer-supported collaborative work, where the construction part consists of 4 steps:

each group member acquires an individual understanding of the subject;
each group member exposes his/her ideas and the others actively listen to them;
the group refines, builds or modifies the original ideas;
the differences of interpretation between the group members are dealt with in a constructive fashion, through arguments and clarifications.

Agredo-Delgado, V., Ruiz, P.H., Mon, A. et al. Applying a process for the shared understanding construction in computer-supported collaborative work: an experiment. Comput Math Organ Theory 28, 247-270 (2022). https://doi.org/10.1007/s10588-021-09326-z ↩