Personal knowledge base

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A personal knowledge base (PKB) is an electronic tool used by an individual to express, capture, and later retrieve personal knowledge. It differs from a traditional database in that it contains subjective material particular to the owner, that others may not agree with nor care about. Importantly, a PKB consists primarily of knowledge, rather than information; in other words, it is not a collection of documents or other sources an individual has encountered, but rather an expression of the distilled knowledge the owner has extracted from those sources or from elsewhere. [1] [2] [3]

Contents

The term personal knowledge base was mentioned as early as the 1980s, [4] [5] [6] [7] but the term came to prominence in the 2000s when it was described at length in publications by computer scientist Stephen Davies and colleagues, [1] [2] who compared PKBs on a number of different dimensions, the most important of which is the data model that each PKB uses to organize knowledge. [1] :18 [3]

Data models

Davies and colleagues examined three aspects of the data models of PKBs: [1] :19–36

Davies and colleagues also emphasized the principle of transclusion, "the ability to view the same knowledge element (not a copy) in multiple contexts", which they considered to be "pivotal" to an ideal PKB. [1] [2] They concluded, after reviewing many design goals, that the ideal PKB was still to come in the future. [1] [2]

Personal knowledge graph

In their publications on PKBs, Davies and colleagues discussed knowledge graphs as they were implemented in some software of the time. [1] [2] Later, other writers used the term personal knowledge graph (PKG) to refer to a PKB featuring a graph structure and graph visualization. [8] However, the term personal knowledge graph is also used by software engineers to refer to the different subject of a knowledge graph about a person, [9] in contrast to a knowledge graph created by a person in a PKB. [10]

Software architecture

Davies and colleagues also differentiated PKBs according to their software architecture: file-based, database-based, or client–server systems (including Internet-based systems accessed through desktop computers and/or handheld mobile devices). [1] :37–41

History

Non-electronic personal knowledge bases have probably existed in some form for centuries: Leonardo da Vinci's journals and notes are a famous example of the use of notebooks. Commonplace books, florilegia , annotated private libraries, and card files (in German, Zettelkästen) of index cards and edge-notched cards are examples of formats that have served this function in the pre-electronic age. [11]

Undoubtedly the most famous early formulation of an electronic PKB was Vannevar Bush's description of the "memex" in 1945. [1] [2] [12] In a 1962 technical report, human–computer interaction pioneer Douglas Engelbart (who would later become famous for his 1968 "Mother of All Demos" that demonstrated almost all the fundamental elements of modern personal computing) described his use of edge-notched cards to partially model Bush's memex. [13]

Examples

In their 2005 paper, Davies and colleagues mentioned the following, among others, as examples of software applications that had been used to build PKBs using various data models and architectures: [1]

Open source
Closed source

See also

Related Research Articles

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References

  1. 1 2 3 4 5 6 7 8 9 10 Davies, Stephen; Velez-Morales, Javier; King, Roger (August 2005). Building the memex sixty years later: trends and directions in personal knowledge bases (Technical report). Boulder, Colo.: Department of Computer Science, University of Colorado at Boulder. CU-CS-997-05.
  2. 1 2 3 4 5 6 Davies, Stephen (February 2011). "Still building the memex". Communications of the ACM . 54 (2): 80–88. doi:10.1145/1897816.1897840. S2CID   9551946. Archived from the original on 2021-06-24.
  3. 1 2 See also the dissertation of Max Völkel, which examined personal knowledge data models, and proposed a meta-model called "Conceptual Data Structures": Völkel, Max (January 2010). Personal knowledge models with semantic technologies (Ph.D. thesis). Karlsruhe: Faculty of Economics, Karlsruhe Institute of Technology, University of the State of Baden-Württemberg, and National Laboratory of the Helmholtz Association. doi:10.5445/IR/1000019641. OCLC   837821583.
  4. Brooks, Tom (April 1985). "New technologies and their implications for local area networks". Computer Communications. 8 (2): 82–87. doi:10.1016/0140-3664(85)90218-X.
  5. Krüger, Gerhard (1986). "Future information technology—motor of the 'information society'". In Henn, Rudolf (ed.). Employment and the transfer of technology. Berlin; New York: Springer-Verlag. pp. 39–52. doi:10.1007/978-3-642-71292-0_4. ISBN   3540166394. OCLC   14108228.
  6. Forman, George E. (1988). "Making intuitive knowledge explicit through future technology" . In Forman, George E.; Pufall, Peter B. (eds.). Constructivism in the computer age. The Jean Piaget Symposium series. Hillsdale, NJ: Lawrence Erlbaum Associates. pp.  83–101. ISBN   0805801014. OCLC   16922453.
  7. Smith, Catherine F. (1991). "Reconceiving hypertext" . In Hawisher, Gail E.; Selfe, Cynthia L. (eds.). Evolving perspectives on computers and composition studies: questions for the 1990s. Urbana, IL: National Council of Teachers of English. pp.  224–252. ISBN   0814111661. OCLC   23462809.
  8. Pyne, Yvette; Stewart, Stuart (March 2022). "Meta-work: how we research is as important as what we research". British Journal of General Practice . 72 (716): 130–131. doi:10.3399/bjgp22X718757. PMC   8884432 . PMID   35210247.
  9. For example: Li, Xiang; Tur, Gokhan; Hakkani-Tür, Dilek; Li, Qi (December 2014). "Personal knowledge graph population from user utterances in conversational understanding". SLT 2014: 2014 IEEE Workshop on Spoken Language Technology: proceedings: December 7–10, 2014, South Lake Tahoe, Nevada, U.S.A. Piscataway, NJ: IEEE. pp. 224–229. doi:10.1109/SLT.2014.7078578. ISBN   9781479971305. OCLC   945951970. S2CID   6428777. And: Cao, Lei; Zhang, Huijun; Feng, Ling (January 2022). "Building and using personal knowledge graph to improve suicidal ideation detection on social media". IEEE Transactions on Multimedia . 24: 87–102. arXiv: 2012.09123 . doi:10.1109/TMM.2020.3046867. S2CID   229210559.
  10. Balog, Krisztian; Mirza, Paramita; Skjæveland, Martin G.; Wang, Zhilin (June 2022). "Report on the Workshop on Personal Knowledge Graphs (PKG 2021) at AKBC 2021" (PDF). ACM SIGIR Forum. 56 (1): 1–11 (8). Archived (PDF) from the original on 2022-07-11. What does 'personal' in PKG mean? It could be taken to mean (objective) facts about the user (I ate lunch at restaurant X on date Y. I like fish.), subjective beliefs of the user ([I believe that] Pineapple pizza is just wrong. The Earth is flat.), or objective facts that are of particular interest to the user (Pineapple pizza is also often called Hawaiian Pizza).
  11. For example, two articles that describe the use of edge-notched cards as a personal knowledge base in health and medicine are: Hoff, Wilbur (May 1967). "A health information retrieval system for personal use". Journal of School Health . 37 (5): 251–254. doi:10.1111/j.1746-1561.1967.tb00505.x. PMID   5182183. And: Manning, Phil R.; DeBakey, Lois (1987). "The personal information center" . Medicine, preserving the passion (1st ed.). New York: Springer-Verlag. pp.  57–71 (59). doi:10.1007/978-1-4757-1954-3_3. ISBN   0387963618. OCLC   13580831. Another mention of its use by a writer is: Piercy, Marge (1982). Parti-colored blocks for a quilt . Ann Arbor: University of Michigan Press. pp.  27. doi:10.3998/mpub.7442. ISBN   0472063383. OCLC   8476006. I have a memory annex which serves my purposes. It uses edge-notched cards.
  12. Bush, Vannevar (July 1945). "As we may think". Atlantic Monthly . 176 (1): 101–108.
  13. Engelbart, Douglas C. (1962). "Some possibilities with cards and relatively simple equipment". Augmenting human intellect: a conceptual framework. Menlo Park, CA: Stanford Research Institute. OCLC   8671016. Archived from the original on 2011-05-04. Retrieved 2018-08-12.