Abstract
The contribution analyses the forms of regional knowledge, its sources and the characteristics of information that can be collected, filtered, represented and managed to extract knowledge to benefit territorial decision makers. Regional knowledge emerges and develops over long periods of time, shaping types of regional activities, vocations and industry structures. Thus, the main aspects of the definition of regional knowledge are the geographic and temporal dimensions. Starting from a categorization of regional knowledge into conscious knowledge, that is explicit knowledge held by individuals; objectified knowledge, that is explicit knowledge held by organizations and experts; preconscious knowledge, that is automatic knowledge held by individuals expressed unintentionally; and collective knowledge, implicit knowledge expressed in the practice of organizations, three frameworks for representing and managing information of different nature are indicated as suitable to extract different forms of knowledge, namely: non classical logics, and specifically fuzzy logic, to represent and reason on imprecise conscious and collective knowledge; machine learning to extract preconscious knowledge implicit in geo big data and created by both IoT and within social networks; Petri Nets to formalize objectified knowledge in the form of laws and regulations. For each form of knowledge case studies are illustrated and discussed highlighting the benefits of the adopted formal frameworks. Conclusions summarize the main message and open issues.
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Notes
- 1.
The Spatials3 project is financed by the European Regional Development Fund under the Regional Occupational Program of the Lombardy Region (ERDF 2014–2020—Axis I “Strengthen technological research, development and innovation”—Action 1.b.1.3 “Support for co-operative R&D activities to develop new sustainable technologies, products and services”).
References
Andreasen T, De Tré G, Kacprzyk J, Legind Larsen H, Bordogna G, Zadrozny S (2021) Perspectives and views of flexible query answering. In: Proceedings of 14th international conference on flexible query answering systems FQAS 2021. Springer, LNAI 12871, pp 3–14
Anthony B (2022) Employing case-based reasoning to provide knowledge for sustainable regional development, pp 45–60
Arcaini P, Bordogna G, Ienco D, Sterlacchini S (2016) Geo-temporal density based clustering for exploring periodic and aperiodic events reported in social networks. Information Science 340–341:122–143
Balan A, Alboaie S, Kourtit K, Nijkamp P (2022) Blockchain systems for smart cities and regions: an illustration of self-sovereign data governance, pp 163–190
Berman T (2017) Public participation as a tool for integrating local knowledge into spatial planning. Springer, Cham
Bordogna G (2021) A semantic approach for quality assurance and assessment of volunteered geographic information. Information 12(12):492. https://doi.org/10.3390/info12120492
Bordogna G, Sterlacchini S (2017) Volunteered geographic information management supported by fuzzy ontologies and level-based approximate reasoning. IEA/AIE 2017, ISBN 978-3-319-60042-0 Part I, LNAI 10350, Springer, Cham, pp 466–476
Bordogna G, Chiesa S, Geneletti D (2006) Linguistic modelling of imperfect spatial information as a basis for simplifying spatial analysis. Inf Sci 176(4):366–389
Bordogna G, Carrara P, Frigerio L, Kliment T, Sterlacchini S (2015) Volunteered geographic information and spatial data infrastructures to promote s-low resources: the case study of the Orti di Bergamo smart application.In: Casti E, Burini F (eds) Centrality of territories. Bergamo University Press, Sestante edizioni, pp 165–182
Bordogna G, Frigerio L, Cuzzocrea A, Psaila G (2016) An effective and efficient similarity-matrix-based algorithm for clustering big mobile social data. In: Proceedings of the 15th IEEE international conference on machine learning and applications (ICMLA), vol 1, pp 514–521
Bordogna G, Cuzzocrea A, Frigerio L, Psaila G, Toccu M (2017) An interoperable open data framework for discovering popular tours based on geo-tagged tweets. Int Journal of Intelligent Information and Database Systems (IJIIDS) 10(3–4):246–268. https://doi.org/10.1504/IJIIDS.2017.10004160, Print ISSN: 1751-5858 Online ISSN: 1751-5866
Caruso G, Pumain D, Thomas I (2022) No “prêt à porter” but a multiscalar perspective to smart cities, pp 123–148
ERIK—European regions knowledge-based innovation network (2007) Knowledge and innovation for regional growth, policy recommendations based on European good practices (Huntingford J, Frosini P (eds) with the support of Etruria Innovazione SCpA eds). Siena, IT. http://www.eriknetwork.net/documents.html. 18 May 2022
European Parliament and Council of the European Union (2016) Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). https://eur-lex.europa.eu/eli/reg/2016/679/oj. 18 May 2022
Favetta F, Duchateau F (2022) Knowledge management at multiple decision levels. A use case about COVID-19 pandemic, pp 61–88
Fritsch M, Wyrwich M (2018) Regional knowledge, entrepreneurial culture, and innovative start-ups over time and space: an empirical investigation. Small Business Economics 51:337–353. https://doi.org/10.1007/s11187-018-0016-6. 03 March 2020
Goodchild MF (2007) Citizens as voluntary sensors: spatial data infrastructure in the World of Web 2.0. Int J Spat Data Infrastruct Res 2:24–32
Hichri S (2022) The beginnings of smart cities and big data, a public sector organizational learning approach initiated by “Tunisian Smart Cities”, pp 191–222
Laurini R (2022) Semantic analysis of feedforward knowledge for regional policymaking, pp 89–110
Mamdani EH, Assilian S (1974) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man-Mach Stud 7:1–13
Mehaffy MW, Elmlund P (2022) Smart cities: missing the stigmergy? pp 149–162
Naseem U, Razzak I, Khan SK, Prasad M (2021) A comprehensive survey on word representation models: from classical to state-of-the-art word representation language models. ACM Transactions on Asian and Low-Resource Language Information Processing 20(5):74:1–35
Petri CA (1966) Kommunikation mit Automaten. Bonn: Institut fur lnstrumentelle Mathematik, Schriften des IIM Nr. 3, 1962. [Communication with Automata. New York: Griffiss Air Force Base Tech Rep RADC-TR-65–377, 1(1) (1966)]
Sterlacchini S, Bordogna G, Cappellini G (2018) SIRENE—a spatial data infrastructure to enhance communities’ resilience to disaster-related emergency. Int Journal of Disaster Risk Science 9:129–142
Treakle J, Krell R (2014) Territorial development and local knowledge systems, FAO publication. https://www.fao.org/3/mk953e/mk953e.pdf. 18 May 2022)
Tsoukas H (1996) The firm as a distributed knowledge system: a constructionist approach. Strateg Manag J 17(S2):11–25
Valverdù J (2010) Thinking machines and the philosophy of computer science: concepts and principles. Information Science Reference
Various Authors(2017) Applied social science research in a regional knowledge system. Garmann HC, Johnsen ES, Hauge ML, Magnussen R Ennals R (eds) Taylor and Francis group. https://doi.org/10.4324/9781315411415
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zadeh LA (2012) Computing with words: principal concepts and ideas. Studies in Fuzziness and Soft Computing Series 277:41–72
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Bordogna, G. (2022). Regional Knowledge: Sources, Representation and Management. In: Laurini, R., Nijkamp, P., Kourtit, K., Bouzouina, L. (eds) Knowledge Management for Regional Policymaking. Springer, Cham. https://doi.org/10.1007/978-3-031-15648-9_2
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