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An exploratory approach to archaeological knowledge production

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Abstract

The current scientific context is characterized by intensive digitization of the research outcomes and by the creation of data infrastructures for the systematic publication of datasets and data services. Several relationships can exist among these outcomes. Some of them are explicit, e.g. the relationships of spatial or temporal similarity, whereas others are hidden, e.g. the relationship of causality. By materializing these hidden relationships through a linking mechanism, several patterns can be established. These knowledge patterns may lead to the discovery of information previously unknown. A new approach to knowledge production can emerge by following these patterns. This new approach is exploratory because by following these patterns, a researcher can get new insights into a research problem. In the paper, we report our effort to depict this new exploratory approach using Linked Data and Semantic Web technologies (RDF, OWL). As a use case, we apply our approach to the archaeological domain.

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Notes

  1. https://www.go-fair.org/fair-principles/.

  2. https://www.w3.org/TR/rdf11-concepts/.

  3. https://www.w3.org/TR/owl2-primer/.

  4. https://collectionstrust.org.uk/resource/getty-art-and-architecture-thesaurus-aat/.

  5. http://legacy.ariadne-infrastructure.eu/.

  6. http://www.cidoc-crm.org/crmarchaeo/home-3.

  7. https://perio.do/en/.

  8. https://www.fitzmuseum.cam.ac.uk/about-us/collections/coins-and-medals.

References

  1. Meghini, C., Scopigno, R., Richards, J., Wright, H., Geser, G., Cuy, S., Vlachidis, A.: ARIADNE: a research infrastructure for archaeology. J. Comput. Cult. Herit. (JOCCH) 10(3), 1–27 (2017)

    Article  Google Scholar 

  2. Yu, C.H.: Exploratory data analysis in the context of data mining and resampling. Int. J. Psychol. Res. 3(1), 9–22 (2010). https://doi.org/10.21500/20112084.819

    Article  Google Scholar 

  3. Idreos, S.: Big Data Exploration. Big Data Computing, 3 ISBN: 9780429101366 (2013)

  4. Bizer, C.: Interlinking scientific data on a global scale. Data Sci. J. 12, GRDI6–GRDI12 (2013). https://doi.org/10.2481/dsj.GRDI-002

    Article  Google Scholar 

  5. Auer, S., Bryl, V., Tramp, S (eds.).: Linked Open Data–Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project, LNCS, vol. 8661, Springer, Berlin (2014) https://doi.org/10.1007/978-3-319-09846-3

  6. Guarino, N (ed.).: Formal ontology in information systems. In Proceedings of the First International Conference, FOIS’98, June 6–8, Trento, Italy (1998)

  7. Matsumoto, M., Uleberg, E. (eds.).: CAA2016: oceans of data. In Proceedings of the 44th Conference on Computer Applications and Quantitative Methods in Archaeology (2016)

  8. Ore, C.E.S.: Oceans of data: Creating a Safe Haven for Information (2018)

  9. Gruber, E., Matsumoto, M., Uleberg, E.: Linked open data for numismatic library, archive and museum integration. In: CAA2016: Oceans of Data. In Proceedings of the 44th Conference on Computer Applications and Quantitative Methods in Archaeology. p. 55. Archaeopress Publishing Ltd (2018)

  10. Kadar, M.: Data modeling and relational database design in archaeology. Acta Univ. Apulensis 3, 73–80 (2002)

    Google Scholar 

  11. Smith, J.R.: Database design, archaeological classification and geographic information systems: A case study from southeast Queensland. Unpublished thesis (PhD), University of Queensland (2000)

  12. Miller, T.M.: Specify for Archaeology: A Proposed Data Model for Archaeological Collection Database Management, Unpublished thesis (PhD), University of Kansas (2012)

  13. Wynholds, L.: Linking to scientific data: identity problems of unruly and poorly bounded digital objects. Int. J. Digit. Curation (2011). https://doi.org/10.1080/09558543.1991.12031189

    Article  Google Scholar 

  14. Farnel, S., Shiri, A.: Metadata for research data: current practices and trends. In International Conference on Dublin Core and Metadata Applications, DC-2018, Porto, Portugal, pp. 74–82 (2014)

  15. Willis, C., Greenberg, J., White, H.: Analysis and synthesis of metadata goals for scientific data. J. Am. Soc. Inf. Sci. Technol. 63(8), 1505–1520 (2012)

    Article  Google Scholar 

  16. Belussi, A., Migliorini, S.: A spatio-temporal framework for managing archeological data. Ann. Math. Artif. Intell. 80(3–4), 175–218 (2017). https://doi.org/10.1007/s10472-017-9535-0

    Article  MathSciNet  MATH  Google Scholar 

  17. Hallot, P., Billen, R.: Enhancing spatio-temporal identity: states of existence and presence. Int. J. Geo-Inf. (2016). https://doi.org/10.3390/ijgi5050062

    Article  Google Scholar 

  18. Storey, V.C.: Understanding semantic relationships. VLDB J. 2(4), 455–488 (1993). https://doi.org/10.1007/BF01263048

    Article  Google Scholar 

  19. Gullo, F.: From patterns in data to knowledge discovery: what data mining can do. Phys. Proc. 62, 18–22 (2015). https://doi.org/10.1016/j.phpro.2015.02.005

    Article  Google Scholar 

  20. Waterworth, J.A., Chignell, M.H.: A model for information exploration. Hypermedia 3(1), 35–58 (1991). https://doi.org/10.1080/09558543.1991.12031189

    Article  Google Scholar 

  21. Paskin, N.: Digital object identifiers for scientific data. Data Sci. J. 4, 12–20 (2005). https://doi.org/10.2481/dsj.4.12

    Article  Google Scholar 

  22. Thanos, C., Klan, F., Kritikos, K., Candela, L.: White paper on research data service discoverability. Publications (2017). https://doi.org/10.3390/publications5010001

    Article  Google Scholar 

  23. Gerth, P.: ARIADNE Deliverable D14.2: Pilot Deployment Experiments. ARIADNE Project. Available at http://legacy.ariadne-infrastructure.eu/resources-2/deliverables/d14-2-pilot-deployment-experiments/. Accessed 21 April 2021 (2016)

  24. Felicetti, A., Gerth, P., Meghini, C., Theodoridou, M.: Integrating heterogeneous coin datasets in the context of archaeological research. In: EMF-CRM@ TPDL, pp. 13–27 (2015)

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Correspondence to Valentina Bartalesi.

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Thanos, C., Meghini, C., Bartalesi, V. et al. An exploratory approach to archaeological knowledge production. Int J Digit Libr 23, 231–239 (2022). https://doi.org/10.1007/s00799-022-00324-3

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  • DOI: https://doi.org/10.1007/s00799-022-00324-3

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