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October 17, 2018
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A framework and computer system for knowledge-level acquisition, representation, and reasoning with process knowledge

Publicated to: INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES. 68 (10): 641-668 - 2010-10-01 68(10), DOI: 10.1016/j.ijhcs.2010.05.004

Authors:

Gómez-Pérez, JM; Erdmann, M; Greaves, M; Corcho, O; Benjamins, R
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Affiliations

- Author
Intelligent Software Components (ISOCO) S.A. - Author
Ontoprise GmbH - Author
Telefnica ID - Author
Universidad Politécnica de Madrid - Author
Vulcan Inc. - Author
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Abstract

The development of knowledge-based systems is usually approached through the combined skills of software and knowledge engineers (SEs and KEs, respectively) and of subject matter experts (SMEs). One of the most critical steps in this task aims at transferring knowledge from SMEs' expertise to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this process is costly and error prone. Alleviating such knowledge acquisition bottleneck requires enabling SMEs with the means to produce the target knowledge representations, minimizing the intervention of KEs. This is especially difficult in the case of complex knowledge types like processes. The analysis of scientific domains like Biology, Chemistry, and Physics uncovers: (i) that process knowledge is the single most frequent type of knowledge occurring in such domains and (ii) specific solutions need to be devised in order to allow SMEs to represent it in a computational form. We present a framework and computer system for the acquisition and representation of process knowledge in scientific domains by SMEs. We propose methods and techniques to enable SMEs to acquire process knowledge from the domains, to formally represent it, and to reason about it. We have developed an abstract process metamodel and a library of problem solving methods (PSMs), which support these tasks, respectively providing the terminology for SME-tailored process diagrams and an abstract formalization of the strategies needed for reasoning about processes. We have implemented this approach as part of the DarkMatter system and formally evaluated it in the context of the intermediate evaluation of Project Halo, an initiative aiming at the creation of question answering systems by SMEs. © 2010 Elsevier Ltd. All rights reserved.
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Keywords

EvaluationKnowledge acquisitionKnowledge representationProblem solving methodsProblem-solving methodsProcess knowledgeReasoningSubject matter expertsUsability

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2010, it was in position 8/19, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Cybernetics.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • WoS: 9
  • Scopus: 18
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 64.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 64 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 12.
  • The number of mentions on the social network X (formerly Twitter): 6 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/5633/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 544
  • Downloads: 759
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Germany; United States of America.

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