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International Workshop on Business Process Modeling, Development and Support

International Conference on Evaluation and Modeling Methods of Systems Analysis and Development

BPMDS 2017, EMMSAD 2017: Enterprise, Business-Process and Information Systems Modeling pp 272–286Cite as

Know-How Mapping – A Goal-Oriented Approach and Evaluation

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 287))

Abstract

Information system developers have to cope with a continually changing technological landscape. Knowing what each kind of technique or technology can do and how well they perform under various conditions constitute an important kind of know-how that systems professionals seek. In this paper, we claim that such know-how information can be structured as a map, so as to facilitate understanding and decision making about what technology to adopt or develop. Recent work has proposed to use a goal-oriented approach to address the challenge of constructing such a map. In this paper, we examine the hypothesis that a goal-oriented approach can be used for mapping and analyzing technological domains. First, we apply the approach to several domains, to verify the applicability and expressiveness of the approach. Second, we perform a feature-based analysis and examine the extent to which the approach addresses the desired characteristics of a know-how map. Third, we conduct a controlled experiment in which the comprehension of goal-oriented know-how maps in comparison to a textual summary from a literature review was examined. The evaluation results indicate that the goal-oriented know-how maps have sufficient expressiveness, are easy to read and understand, and address a number of desired characteristics.

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Author information

Authors and Affiliations

  1. University of Toronto, Toronto, Canada

    Arnon Sturm, Eric Yu & Sadra Abrishamkar

  2. Ben-Gurion University of the Negev, Beer Sheva, Israel

    Arnon Sturm

Authors
  1. Arnon Sturm
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  2. Eric Yu
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  3. Sadra Abrishamkar
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Corresponding author

Correspondence to Arnon Sturm .

Editor information

Editors and Affiliations

  1. University of Haifa , Haifa, Israel

    Iris Reinhartz-Berger

  2. University of Duisburg-Essen , Duisburg, Germany

    Jens Gulden

  3. Université de Paris 1 Panthéon - Sorbonne, Paris, France

    Selmin Nurcan

  4. Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg

    Wided Guédria

  5. Saint Louis University , St. Louis, Missouri, USA

    Palash Bera

Appendix

Appendix

The comprehension questions.

  1. 1.

    What are the alternative methods for discovering hyperlinked web structure?

  2. 2.

    What are the alternative methods for text and web page pre-processing for data mining?

  3. 3.

    What is the problem that HITS and SALSA methods aim to solve?

  4. 4.

    What is the problem that the Feature Extractor method aims to solve?

  5. 5.

    Solutions to the web template detection problem include batch web page processing and page level template detection. Are both of these techniques required to address this problem?

  6. 6.

    How do Site Style Trees (SST) affect noise data in the web page?

  7. 7.

    Describe the effects of “stopword” removal.

  8. 8.

    Provide a summary of the solution trade-offs when crawling the web for specific topics.

  9. 9.

    Which of the alternative techniques for batch web template processing has the advantage? Please explain.

  10. 10.

    What are the distinguishing effects of focused crawlers and context-focused crawlers?

  11. 11.

    In the provided material, can you identify any gaps in the knowledge in this domain? Explain how you are able to identify these gaps (if any).

The reflection questions (in scale of strongly disagree to strongly agree).

  1. 1.

    The approach helps a newcomer to a domain learn about the domain in a short amount of time.

  2. 2.

    The approach helps a newcomer to obtain an overview of the domain comprehensively.

  3. 3.

    The approach enables researchers to identify knowledge gaps in a short amount of time.

  4. 4.

    The approach enables researchers to easily identify knowledge gaps.

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Sturm, A., Yu, E., Abrishamkar, S. (2017). Know-How Mapping – A Goal-Oriented Approach and Evaluation. In: Reinhartz-Berger, I., Gulden, J., Nurcan, S., Guédria, W., Bera, P. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2017 2017. Lecture Notes in Business Information Processing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-59466-8_17

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