Name
Abstract | ||
|---|---|---|
Purpose - The purpose of this paper is to report on research that aims to make knowledge, and in particular know-how, more easily accessible to both academic and industrial communities, as well as to the general public. The paper proposes a novel approach to map out know-how information, so all knowledge stakeholders are able to contribute to the knowledge and expertise accumulation, as well as using that knowledge for research and applying expertise to address problems. Design/methodology/ approach - This research followed a design science approach in which mapping of the know-how information was done by the research team and then tested with graduate students. During this research, the mapping approach was continuously evaluated and refined, and mapping guidelines and a prototype tool were developed. Findings - Following an evaluation with graduate students, it was found that the know-how maps produced were easy to follow, allowed continuous evolution, facilitated easy modification through provided modularitycapabilities, further supported reasoning about know-how and overall provided adequate expressiveness. Furthermore, we applied the approach with various domains and found that it was a good fit for its purpose across different knowledge domains. Practical implications - This paper argues that mapping out know-how within research and industry communities can further improve resource knowledge) utilization, reduce the phenomena of "re- inventing the wheel" and further create linkage across communities. Originality/value - With the qualities mentioned above, know- how maps can both ease and support the increase of access to expert knowledge to various communities, and thus, promote re-use and expansion of knowledge for various purposes. Having an explicit representation of know- how further encourages innovation, as knowledge from various domains can be mapped, searched and reasoned, and gaps can be identified and filled. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1108/JKM-04-2016-0173 | JOURNAL OF KNOWLEDGE MANAGEMENT |
Keywords | Field | DocType |
Modeling,Visualization,Knowledge mapping,Domain exploration | Body of knowledge,Domain knowledge,Know-how,Computer science,Personal knowledge management,Visualization,Knowledge management,Originality,Design science,Modularity,Management science | Journal |
Volume | Issue | ISSN |
21.0 | 2.0 | 1367-3270 |
Citations | PageRank | References |
3 | 0.39 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arnon Sturm | 1 | 410 | 44.76 |
| Daniel Gross | 2 | 326 | 39.68 |
| Jian Wang | 3 | 179 | 73.08 |
| Eric S. K. Yu | 4 | 1480 | 200.75 |