Abstract
Semantic Warehouses integrate data from various sources for offering a unified view of the data and enabling the answering of queries which cannot be answered by the individual sources. However, such semantic warehouses have to be refreshed periodically as the underlying datasets change. This is a challenging requirement, not only because the mappings and transformations that were used for constructing the semantic warehouse can be invalidated, but also because additional information (not existing in the initial datasets) may have been added in the semantic warehouse, and such information needs to be preserved after every reconstruction. In this paper we focus on this particular problem in a real setting: the Global Record of Stocks and Fisheries, a semantic warehouse that integrates data about stocks and fisheries from various information systems. We propose and detail a process that can tackle these requirements and we report our experiences from implementing it.
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Notes
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BlueBRIDGE (H2020-BG-2019-1), GA no 675680.
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BlueCloud (H2020-EU.3.2.5.1), GA no: 862409.
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References
Assante, M., et al.: Enacting open science by d4science. Futur. Gener. Comput. Syst. 101, 555–563 (2019)
Dividino, R.Q., Gottron, T., Scherp, A., Gröner, G.: From changes to dynamics: dynamics analysis of linked open data sources. In: Proceedings of PROFILES@ESWC. CEUR-WS.org (2014)
Dos Reis, J.C., Pruski, C., Da Silveira, M., Reynaud-Delaître, C.: Dykosmap: a framework for mapping adaptation between biomedical knowledge organization systems. J. Biomed. Inform. 55, 153–173 (2015)
Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G.: Ontology change: classification and survey. Knowle. Eng. Rev. 23(2), 117–152 (2008)
Hyvönen, E., et al.: WarSampo data service and semantic portal for publishing linked open data about the second world war history. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 758–773. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-34129-3_46
Jaradeh, M.Y., et al.: Open research knowledge graph: next generation infrastructure for semantic scholarly knowledge. In: Proceedings of the 10th International Conference on Knowledge Capture, pp. 243–246 (2019)
Käfer, T., Abdelrahman, A., Umbrich, J., O’Byrne, P., Hogan, A.: Observing linked data dynamics. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 213–227. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38288-8_15
Kohlmeier, S., Lo, K., Wang, L.L., Yang, J.: Covid-19 open research dataset (cord-19) (2020). https://doi.org/10.5281/zenodo.3813567
Kondylakis, H., Plexousakis, D.: Ontology evolution without tears. Web Semant. Sci. Serv. Agents World Wide Web 19, 42–58 (2013)
Marketakis, Y., et al.: X3ml mapping framework for information integration in cultural heritage and beyond. Int. J. Digit. Libr. 18(4), 301–319 (2017). https://doi.org/10.1007/s00799-016-0179-1
Mountantonakis, M., Minadakis, N., Marketakis, Y., Fafalios, P., Tzitzikas, Y.: Quantifying the connectivity of a semantic warehouse and understanding its evolution over time. IJSWIS 12(3), 27–78 (2016)
Mountantonakis, M., Tzitzikas, Y.: Large-scale semantic integration of linked data: a survey. ACM Comput. Surv. (CSUR) 52(5), 103 (2019)
R. Gazzotti, F. Michel, F.G.: Cord-19 named entities knowledge graph (cord19-nekg) (2020)
Reis, R.B., Morshed, A., Sellis, T.: Understanding link changes in LOD via the evolution of life science datasets (2019)
Roussakis, Y., Chrysakis, I., Stefanidis, K., Flouris, G., Stavrakas, Y.: A flexible framework for understanding the dynamics of evolving RDF datasets. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9366, pp. 495–512. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25007-6_29
Tzitzikas, Y., et al.: Matware: constructing and exploiting domain specific warehouses by aggregating semantic data. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 721–736. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07443-6_48
Tzitzikas, Y., et al.: Unifying heterogeneous and distributed information about marine species through the top level ontology marineTLO. Program 50(1), 16–40 (2016)
Tzitzikas, Y., Kampouraki, M., Analyti, A.: Curating the specificity of ontological descriptions under ontology evolution. J. Data Semant. 3(2), 75–106 (2013). https://doi.org/10.1007/s13740-013-0027-z
Tzitzikas, Y., et al.: Methods and tools for supporting the integration of stocks and fisheries. In: Salampasis, M., Bournaris, T. (eds.) HAICTA 2017. CCIS, vol. 953, pp. 20–34. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-12998-9_2
Vandenbussche, P.Y., Umbrich, J., Matteis, L., Hogan, A., Buil-Aranda, C.: SPARQLES: monitoring public SPARQL endpoints. Semantic web 8(6), 1049–1065 (2017)
Wishart, D.S., et al.: Drugbank 5.0: a major update to the drugbank database for 2018. Nucleic Acids Res. 46(D1), D1074–D1082 (2018)
Yumusak, S., Dogdu, E., Kodaz, H., Kamilaris, A., Vandenbussche, P.: Spend: linked data SPARQL endpoints discovery using search engines. IEICE Trans. Inf. Syst. 100(4), 758–767 (2017)
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This work has received funding from the European Union’s Horizon 2020 innovation action BlueCloud (Grant agreement No 862409).
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Marketakis, Y., Tzitzikas, Y., Gentile, A., van Niekerk, B., Taconet, M. (2021). On the Evolution of Semantic Warehouses: The Case of Global Record of Stocks and Fisheries. In: Garoufallou, E., Ovalle-Perandones, MA. (eds) Metadata and Semantic Research. MTSR 2020. Communications in Computer and Information Science, vol 1355. Springer, Cham. https://doi.org/10.1007/978-3-030-71903-6_26
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