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Your Notes are an Information System: Lessons from Information Systems for Personal Knowledge Management

Abstract

In recent years, systematized approaches—such as Zettelkasten and Building a Second Brain—to taking effective notes have proliferated as “Personal Knowledge Management” systems, especially among researchers. Fundamental to these approaches is the practice of note-taking. When taking notes, a person instantiates a concept, idea, question, or other knowledge material in static form, typically as text. Notes can then be used as reminders, to help organize thinking, and more. In this sense, these note-based systems are a kind of information system: they maintain a representation of one’s thinking, they provide information about the state of one’s thinking, and they may be used to change one’s thinking (and the products of that thinking). In this research sketch, I use this reframing of note-taking systems to apply theory on Information Systems (IS) to Personal Knowledge Management (PKM). In particular, I draw on theory of the ontology of information systems and on data quality to provide a set of principles on how to take and use effective notes. For example, if you consider your notes a kind of dataset for your PKM IS, then every note you take is an item of data. In turn, existing research on ensuring data quality applies to improving the quality of your notes. I illustrate how to apply these principles to the design of your notes. By presenting these ideas about note-taking and IS, I hope to help researchers recognize the importance of their own PKM practices while providing them with productive ways of improving their knowledge management skills.

References

Murphy, R. J. A. (2021). Obsidian, Roam, and the rise of Integrated Thinking Environments—what they are, what they do, and what’s next. Axle. https://axle.design/obsidian-roam-and-the-rise-of-integrated-thinking-environments—what-they-are-what-they-do-and-what-s

Negash, S. (2004). Business Intelligence. Communications of the Association for Information Systems, 13, 177-195. https://aisel.aisnet.org/cais/vol13/iss1/15/

Olivé, A. (2007). Conceptual Modeling of Information Systems. Springer Science & Business Media. https://play.google.com/store/books/details?id=61mT383WC78C&source=gbs_api

Wang, T. (2013). Why Big Data Needs Thick Data. Ethnography Matters. http://ethnographymatters.net/blog/2013/05/13/big-data-needs-thick-data

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