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Patinformatics as a business process: A guideline through patent research tasks and tools

Author

Listed:
  • Moehrle, Martin G.
  • Walter, Lothar
  • Bergmann, Isumo
  • Bobe, Sebastian
  • Skrzipale, Svenja

Abstract

Since Trippe [1] introduced the term 'patinformatics' a lot of progress has been made in this particular field of information science. However, there is still need for a more comprehensive framework to structure the variety of tasks related to 'patinformatics', to highlight essential functions within the patinformatics process and to identify those process parts, which are supported by currently available software tools, and others, which are not. In this paper we apply business process modeling to describe the patinformatics process for supporting managerial decision making. The process model enables an overview of major tasks within patinformatics and links them to currently available tools. This paper provides a guideline through patent research for most users of patent information. It may also be employed as a fundamental model for the comparison of patinformatics software applications and approaches.

Suggested Citation

  • Moehrle, Martin G. & Walter, Lothar & Bergmann, Isumo & Bobe, Sebastian & Skrzipale, Svenja, 2010. "Patinformatics as a business process: A guideline through patent research tasks and tools," World Patent Information, Elsevier, vol. 32(4), pages 291-299, December.
    • Handle: RePEc:eee:worpat:v:32:y:2010:i:4:p:291-299
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    Citations

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    Cited by:

    1. Ansgar Moeller & Martin G. Moehrle, 2015. "Completing keyword patent search with semantic patent search: introducing a semiautomatic iterative method for patent near search based on semantic similarities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 77-96, January.
    2. Travis J. Lybbert & Nikolas J. Zolas, 2012. "Getting Patents & Economic Data to Speak to Each Other: An ‘Algorithmic Links with Probabilities’ Approach for Joint Analyses of Patenting & Economic Activity," WIPO Economic Research Working Papers 05, World Intellectual Property Organization - Economics and Statistics Division, revised Oct 2012.
    3. Martin G. Moehrle & Jan M. Gerken, 2012. "Measuring textual patent similarity on the basis of combined concepts: design decisions and their consequences," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 805-826, June.
    4. repec:wip:wpaper:5 is not listed on IDEAS
    5. Lothar Walter & Alfred Radauer & Martin G. Moehrle, 2017. "The beauty of brimstone butterfly: novelty of patents identified by near environment analysis based on text mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 103-115, April.
    6. Lybbert, Travis J. & Zolas, Nikolas J., 2014. "Getting patents and economic data to speak to each other: An ‘Algorithmic Links with Probabilities’ approach for joint analyses of patenting and economic activity," Research Policy, Elsevier, vol. 43(3), pages 530-542.
    7. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    8. Guifeng Liu, 2013. "Visualization of patents and papers in terahertz technology: a comparative study," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1037-1056, March.

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