The Q-codes: Metadata, Research data, and desiderata, oh my! Improving access to grey literature in family medicine

Melissa P. Resnick, Ashwin Ittoo, Marc Jamoulle, Marc Vanmeerbeek, Frank S. Shamenek, Chiehwen Ed Hsu, Robert Vander Stichele, Julien Grosjean, Stefan Darmoni, Elena Cardillo, Miguel Pizzanelli

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Problem/Goal: In GL19's "Indexing grey literature in General Practice: Family Medicine in the Era of Semantic Web," Jamoulle and colleagues (Jamoulle et al., 2018) propose the use of a relatively new terminology (3CGP) to allow for the indexing and retrieval of (GP/FM) knowledge which otherwise would be lost, or difficult to locate. Though designed to meet Cimino's (Cimino, 1998) twelve desiderata for the design of a controlled healthcare vocabulary, Jamoulle and colleagues (Jamoulle et al., 2018) acknowledge that a detailed requirement by requirement evaluation of 3CGP was not performed. The goal of this paper is to evaluate the Q-Codes component of the 3CGP terminology, in detail, with each of Cimino's twelve desiderata. Research Method/Procedure: In our work, we will focus on qualitative analysis, whereby our taxonomy, the Q-Codes, and in particular, its vocabulary satisfies a standard set of desiderata. Qualitative analysis provides a simple and yet effective way to assess the Q-Codes taxonomy's quality. We will briefly describe each of the desiderata and discuss how our taxonomy satisfies each one of them (or not). Anticipated Results of the Research: The qualitative evaluation is intended as an initial stage, which focuses on the Q-Codes taxonomy's contents, namely, its vocabulary (e.g. terms and definitions). Our aim with the qualitative evaluation is to investigate whether our proposed taxonomy, and in particular its vocabulary, satisfies a set of desiderata. This will enable us to determine whether the knowledge acquisition and (part of) the conceptualization steps of our ontology development process have been performed correctly. We consider that validating our vocabulary against a set of well-defined desiderata is paramount before evaluating other aspects of the taxonomy (such as the relations). As a set of desiderata, we chose that proposed by Cimino in his seminal study entitled "Desiderata for controlled medical vocabularies in the twenty-first century" (Cimino, 1998). These desiderata ensure that our taxonomy can be successfully deployed and exploited in actual GM/FM applications / activities, such as indexing grey literature. The desiderata define a set of (desired) characteristics that (ideally all) standard medical vocabularies should satisfy. Thus, these desiderata help in alleviating inter-operability issues, with the use of common standards ensuring the efficient integration of our taxonomy with other medical vocabularies and resources (taxonomies, ontologies). From the results of this study, improvements can be made to the Q-Codes component of, and thus, the 3CGP terminology. This, in turn, improves the ability to index the grey literature with the 3CGP terminology, providing greater access to needed information. Indication of costs related to the project: This project has not been funded. 3CGP is placed under Attribution-Non-Commercial-Share-Alike 4.0 International (CC BY-NC-SA 4.0) license.

Original languageEnglish
Title of host publication20th International Conference on Grey Literature
Subtitle of host publicationResearch Data Fuels and Sustains Grey Literature, GL 2018 - Conference Proceedings
Number of pages10
ISBN (Electronic)9789077484333
Publication statusPublished - 2019
Event20th International Conference on Grey Literature: Research Data Fuels and Sustains Grey Literature, GL 2018 - New Orleans, United States
Duration: 2018 Dec 32018 Dec 4

Publication series

NameGL-Conference Series: Conference Proceedings
ISSN (Print)1386-2316


Conference20th International Conference on Grey Literature: Research Data Fuels and Sustains Grey Literature, GL 2018
Country/TerritoryUnited States
CityNew Orleans

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Library and Information Sciences


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