Research Article
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Transforming Meteorological Data into Linked Data: Case of the Black Sea Region

Year 2021, Volume: 2 Issue: 1, 47 - 58, 13.03.2021

Deniztan Ulutaş Karakol Çetin Cömert

https://doi.org/10.48123/rsgis.869992

Abstract

Linked Open Data creation, which is a requirement of the semantic Web, is important for all public and private parties related with spatial and non-spatial data with the advantages of linked data technologies. Among these advantages are data being more discoverable, data sharing, increased reusability of data and preventing data duplication. It is necessary and important to transform meteorological data, which are used significantly in many areas such as geographical information systems, risk management, weather forecasts, modeling of air pollution, water resources, agriculture, air traffic and industry, into linked open data. In this study, the transformation of meteorological data into linked data was carried out with the case of the Black Sea region. RDF data was generated by referencing the meteorological station and observation data of the region with ontologies containing the relevant weather and meteorology concepts. Linked meteorological data were obtained by establishing links between the generated Meteorological RDF Data and DBpedia data set, which is an open linked data source. The automatically found link results with the Silk link editor show that the similarity values calculated between the meteorological data and the DBpedia data source are high.

Keywords

Linked Data Meteorological Linked Data RDF Semantic Web Ontology

References

  • Atemezing, G., Corcho, O., Garijo, D., Mora, J., Villalón, P., M., Rozas, P., Suero, V.D., & Terrazas, V.B. (2011). Transforming meteorological data into linked data. Semantic Web journal, 1(2011), 1-5.
  • BioPortal. (2021, Ocak 21). Semantic Web for Earth and Environment Technology Ontology. Retrieved from https://bioportal.bioontology.org/ontologies/SWEET.
  • Bischof, S., Harth, A., Kämpgen, B., Polleres, A. & Schneider, P. (2018). Enriching integrated statistical open city data by combining equational knowledge and missing value imputation, Web Semantics: Science, Services and Agents on the World Wide Web, 48, 22-47, https://doi.org/10.1016/j.Websem.2017.09.003.
  • Consolia, S., Presuttia, V., Recuperoa, R.D., Nuzzolesea, G.A., Peronia, S., Mongiovi, M., Gangemi, A. (2017). Producing Linked Data for Smart Cities: The Case of Catania, Big Data Research, 7, 1-15.
  • DBpedia. (2021, Ocak 21). Retrieved from https://dbpedia.org/ontology/.
  • DBpedia Mappings Wiki (2021, Ocak 21). Retrieved from http://mappings.dbpedia.org/index.php/Main_Page.
  • Debruyne, C., Clinton, É., McNerney, L., Nautiyal, A. & O’Sullivan, D. (2016). Serving Ireland's Geospatial Information as Linked Data, International Semantic Web Conference 2016, October 17-21, Kobe, Japan.
  • Geo. (2021, Ocak 21). Retrieved from https://www.w3.org/2003/01/geo/.
  • GeoNames. (2021, Ocak 21). Retrieved from https://www.geonames.org/.
  • GeoNames Ontology. (2021, Ocak 21). Retrieved from http://www.geonames.org/ontology.
  • Hamdi, F., Abadie, N., Bucher, B., & Feliachi, A. (2015). GeomRDF: A geodata converter with a fine-grained structured representation of geometry in the Web. arXiv preprint, arXiv:1503.04864.
  • Hietanen, E., Lehto, L., Latvala, P. (2016). Providing Geographic Datasets As Linked Data In SDI, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B2, 2016 XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic.
  • Iwaniak, A., Leszczuk, M., Strzelecki, M., Harvey, F., & Kaczmarek, I. (2017). A novel approach for publishing linked open geodata from national registries with the use of semantically annotated context dependent web pages. ISPRS International Journal of Geo-Information, 6(8), 252. doi:10.3390/ijgi6080252.
  • Kara, G., Yılmaz, C., Ulutaş Karakol, D., Akyazı, İ. & Cömert, Ç. (2018). Bağlantılı Verilerin Yayımlanması ve Görselleştirilmesi, VII. Uzaktan Algılama-CBS Sempozyumu (Uzal-CBS 2018), 18-21 Eylül 2018, Eskişehir.
  • Kara, G., Akyazı, İ., Cömert, Ç. (2020). Konumsal Verilerin Bağlantılı Veri Olarak Yayınlanması: Trabzon Örneği. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 36(2), 228-237.
  • Karma. (2021, Ocak 21). A Data Integration Tool. Retrieved from https://usc-isi-i2.github.io/karma/.
  • Koho, M. K., Heino, E., Ikkala, E., Hyvönen, E. A., Nikkilä, R., Miettinen, K., & Suominen, P. (2018). Integrating prisoners of war dataset into the warsampo linked data infrastructure. In Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference (DHN 2018). CEUR Workshop Proceedings. 241-249.
  • Kyzirakos, K., Vlachopoulos, I., Savva, D., Manegold, S. & Koubarakis, M. (2014). GeoTriples: a Tool for Publishing Geospatial Data as RDF Graphs Using R2RML Mappings, International Semantic Web Conference (Posters & Demos) (pp. 393-396).
  • Margan, B., Hakimpour, F., & Saber, M. (2018, April). Linked data geo-statistical analysis of air pollution in urban areas. In 2018 4th International Conference on Web Research (ICWR) (pp. 86-91). IEEE.
  • OpenRefine. (2021, Ocak 21). Retrieved from https://openrefine.org/.
  • Patroumpas, K., Alexakis, M., Giannopoulos, G., & Athanasiou, S. (2014, March). TripleGeo: an ETL Tool for Transforming Geospatial Data into RDF Triples. In Edbt/Icdt Workshops (pp. 275-278).
  • Qiu, L., Du, Z., Zhu, Q. & Fan, Y. (2017). An integrated flood management system based on linking environmental models and disaster-related data, Environmental Modelling & Software, 91, 111-126.
  • Saavedra, J., Vilches-Blázquez, L.M. & Boada, A. (2014). Cadastral data integration through Linked Data, Proceedings of the AGILE 2014 International Conference on Geographic Information Science, Castellón.
  • Schabus, S., & Scholz, J. (2017). Spatially-Linked Manufacturing Data to Support Data Analysis, GI_Forum 2017, 1, 126 –140, DOI: 10.1553/giscience2017_01_s126.
  • Szekely, P., Knoblock, A., C., Yang, F., Zhu, X., Fink, E., E., Allen, R. & Goodlander, G. (2013), Connecting the Smithsonian American Art Museum to the Linked Data Cloud, P. Cimiano et al. (Eds.): ESWC 2013, LNCS 7882, pp. 593-607, Springer-Verlag, Berlin Heidelberg.
  • The LOD cloud. (2021, Ocak 21). Retrieved from https://lod-cloud.net/#about.
  • Berners-Lee, Tim. (2021, Ocak 21). Linked Data, Retrieved from, https://www.w3.org/DesignIssues/LinkedData.html.
  • Time. (2021, Ocak 21). Retrieved from https://raw.githubusercontent.com/w3c/sdw/gh-pages/time/rdf/time.ttl
  • Time Ontology in OWL (2021, Ocak 21). Retrieved from https://www.w3.org/TR/owl-time/
  • Ulutaş Karakol, D., Kara, G., Yılmaz, C. & Cömert, Ç. (2018). Semantic Linking Spatial RDF Data to the Web Data Sources. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4, 2018 ISPRS TC IV Mid-term Symposium “3D Spatial Information Science-The Engine of Change”, 1-5 October 2018, Delft, The Netherlands.
  • Volz, J., Bizer, C., Gaedke, M., & Kobilarov, G. (2009, January). Silk-a link discovery framework for the web of data. In Ldow. LDOW 2009, April 20, Madrid, Spain.
  • Wetz, P., Stern, H., Jakobitsch, J. & Pammer, V. (2012). Matching Linked Open Data Entities to Local Thesaurus Concepts, Proceedings of the I-SEMANTICS 2012 Posters & Demonstrations Track, pp. 6-11.
  • Zhua, Y., Zhu, A., Song, J., Yang, J., Feng, M., Sun, K., Zhang, J., Hou, Z. & Zhao, H. (2017). Multidimensional and quantitative interlinking approach for Linked Geospatial Data, International Journal Of Digital Earth, 10(9), pp. 923-943, http://dx.doi.org/10.1080/17538947.2016.1266041.

Meteorolojik Verilerin Bağlantılı Veriye Dönüştürülmesi: Karadeniz Bölgesi Örneği

Year 2021, Volume: 2 Issue: 1, 47 - 58, 13.03.2021

Deniztan Ulutaş Karakol Çetin Cömert

https://doi.org/10.48123/rsgis.869992

Abstract

Semantik Web’in gereği olan Bağlantılı Açık Veri üretimi, bağlantılı veri teknolojilerinin sağladığı avantajlar ile konumsal ve konumsal olmayan veri ile iş yapan bütün kamu ve özel kuruluşlar için önemlidir. Veriye daha kolay erişilebilmesi, veri paylaşımı, verinin kullanılabilirliğinin artması ve veri tekrarının önlenmesi bu avantajlar arasındadır. Coğrafi bilgi sistemleri, risk yönetimi, hava tahminleri ve hava kirliliğinin modellenmesi, su kaynakları, tarım, hava trafiği ve endüstri gibi birçok alanda önemli derecede kullanılan meteorolojik verilerin bağlantılı açık veriye dönüştürülmesi gerekli ve önemlidir. Bu çalışmada meteorolojik verilerin bağlantılı veriye dönüştürülmesi Karadeniz bölgesi örneği ile gerçekleştirilmiştir. Bölgeye ait meteorolojik istasyon ve gözlem verileri ilgili hava ve meteoroloji kavramlarını içeren ontolojilerle referanslandırılarak RDF verisi üretilmiştir. Üretilen Meteorolojik RDF Verisi ile bağlantılı açık veri kaynağı olan DBpedia veri seti arasında bağlantılar kurularak Bağlantılı Meteorolojik Veriler elde edilmiştir. Silk bağlantı editörü ile otomatik olarak bulunan bağlantı sonuçları, meteorolojik verilerle DBpedia veri kaynağı arasında hesaplanan benzerlik değerlerinin yüksek olduğunu göstermektedir.

Keywords

Bağlantılı Veri Meteorolojik Bağlantılı Veri RDF Semantik Web Ontoloji

References

  • Atemezing, G., Corcho, O., Garijo, D., Mora, J., Villalón, P., M., Rozas, P., Suero, V.D., & Terrazas, V.B. (2011). Transforming meteorological data into linked data. Semantic Web journal, 1(2011), 1-5.
  • BioPortal. (2021, Ocak 21). Semantic Web for Earth and Environment Technology Ontology. Retrieved from https://bioportal.bioontology.org/ontologies/SWEET.
  • Bischof, S., Harth, A., Kämpgen, B., Polleres, A. & Schneider, P. (2018). Enriching integrated statistical open city data by combining equational knowledge and missing value imputation, Web Semantics: Science, Services and Agents on the World Wide Web, 48, 22-47, https://doi.org/10.1016/j.Websem.2017.09.003.
  • Consolia, S., Presuttia, V., Recuperoa, R.D., Nuzzolesea, G.A., Peronia, S., Mongiovi, M., Gangemi, A. (2017). Producing Linked Data for Smart Cities: The Case of Catania, Big Data Research, 7, 1-15.
  • DBpedia. (2021, Ocak 21). Retrieved from https://dbpedia.org/ontology/.
  • DBpedia Mappings Wiki (2021, Ocak 21). Retrieved from http://mappings.dbpedia.org/index.php/Main_Page.
  • Debruyne, C., Clinton, É., McNerney, L., Nautiyal, A. & O’Sullivan, D. (2016). Serving Ireland's Geospatial Information as Linked Data, International Semantic Web Conference 2016, October 17-21, Kobe, Japan.
  • Geo. (2021, Ocak 21). Retrieved from https://www.w3.org/2003/01/geo/.
  • GeoNames. (2021, Ocak 21). Retrieved from https://www.geonames.org/.
  • GeoNames Ontology. (2021, Ocak 21). Retrieved from http://www.geonames.org/ontology.
  • Hamdi, F., Abadie, N., Bucher, B., & Feliachi, A. (2015). GeomRDF: A geodata converter with a fine-grained structured representation of geometry in the Web. arXiv preprint, arXiv:1503.04864.
  • Hietanen, E., Lehto, L., Latvala, P. (2016). Providing Geographic Datasets As Linked Data In SDI, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B2, 2016 XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic.
  • Iwaniak, A., Leszczuk, M., Strzelecki, M., Harvey, F., & Kaczmarek, I. (2017). A novel approach for publishing linked open geodata from national registries with the use of semantically annotated context dependent web pages. ISPRS International Journal of Geo-Information, 6(8), 252. doi:10.3390/ijgi6080252.
  • Kara, G., Yılmaz, C., Ulutaş Karakol, D., Akyazı, İ. & Cömert, Ç. (2018). Bağlantılı Verilerin Yayımlanması ve Görselleştirilmesi, VII. Uzaktan Algılama-CBS Sempozyumu (Uzal-CBS 2018), 18-21 Eylül 2018, Eskişehir.
  • Kara, G., Akyazı, İ., Cömert, Ç. (2020). Konumsal Verilerin Bağlantılı Veri Olarak Yayınlanması: Trabzon Örneği. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 36(2), 228-237.
  • Karma. (2021, Ocak 21). A Data Integration Tool. Retrieved from https://usc-isi-i2.github.io/karma/.
  • Koho, M. K., Heino, E., Ikkala, E., Hyvönen, E. A., Nikkilä, R., Miettinen, K., & Suominen, P. (2018). Integrating prisoners of war dataset into the warsampo linked data infrastructure. In Proceedings of the Digital Humanities in the Nordic Countries 3rd Conference (DHN 2018). CEUR Workshop Proceedings. 241-249.
  • Kyzirakos, K., Vlachopoulos, I., Savva, D., Manegold, S. & Koubarakis, M. (2014). GeoTriples: a Tool for Publishing Geospatial Data as RDF Graphs Using R2RML Mappings, International Semantic Web Conference (Posters & Demos) (pp. 393-396).
  • Margan, B., Hakimpour, F., & Saber, M. (2018, April). Linked data geo-statistical analysis of air pollution in urban areas. In 2018 4th International Conference on Web Research (ICWR) (pp. 86-91). IEEE.
  • OpenRefine. (2021, Ocak 21). Retrieved from https://openrefine.org/.
  • Patroumpas, K., Alexakis, M., Giannopoulos, G., & Athanasiou, S. (2014, March). TripleGeo: an ETL Tool for Transforming Geospatial Data into RDF Triples. In Edbt/Icdt Workshops (pp. 275-278).
  • Qiu, L., Du, Z., Zhu, Q. & Fan, Y. (2017). An integrated flood management system based on linking environmental models and disaster-related data, Environmental Modelling & Software, 91, 111-126.
  • Saavedra, J., Vilches-Blázquez, L.M. & Boada, A. (2014). Cadastral data integration through Linked Data, Proceedings of the AGILE 2014 International Conference on Geographic Information Science, Castellón.
  • Schabus, S., & Scholz, J. (2017). Spatially-Linked Manufacturing Data to Support Data Analysis, GI_Forum 2017, 1, 126 –140, DOI: 10.1553/giscience2017_01_s126.
  • Szekely, P., Knoblock, A., C., Yang, F., Zhu, X., Fink, E., E., Allen, R. & Goodlander, G. (2013), Connecting the Smithsonian American Art Museum to the Linked Data Cloud, P. Cimiano et al. (Eds.): ESWC 2013, LNCS 7882, pp. 593-607, Springer-Verlag, Berlin Heidelberg.
  • The LOD cloud. (2021, Ocak 21). Retrieved from https://lod-cloud.net/#about.
  • Berners-Lee, Tim. (2021, Ocak 21). Linked Data, Retrieved from, https://www.w3.org/DesignIssues/LinkedData.html.
  • Time. (2021, Ocak 21). Retrieved from https://raw.githubusercontent.com/w3c/sdw/gh-pages/time/rdf/time.ttl
  • Time Ontology in OWL (2021, Ocak 21). Retrieved from https://www.w3.org/TR/owl-time/
  • Ulutaş Karakol, D., Kara, G., Yılmaz, C. & Cömert, Ç. (2018). Semantic Linking Spatial RDF Data to the Web Data Sources. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4, 2018 ISPRS TC IV Mid-term Symposium “3D Spatial Information Science-The Engine of Change”, 1-5 October 2018, Delft, The Netherlands.
  • Volz, J., Bizer, C., Gaedke, M., & Kobilarov, G. (2009, January). Silk-a link discovery framework for the web of data. In Ldow. LDOW 2009, April 20, Madrid, Spain.
  • Wetz, P., Stern, H., Jakobitsch, J. & Pammer, V. (2012). Matching Linked Open Data Entities to Local Thesaurus Concepts, Proceedings of the I-SEMANTICS 2012 Posters & Demonstrations Track, pp. 6-11.
  • Zhua, Y., Zhu, A., Song, J., Yang, J., Feng, M., Sun, K., Zhang, J., Hou, Z. & Zhao, H. (2017). Multidimensional and quantitative interlinking approach for Linked Geospatial Data, International Journal Of Digital Earth, 10(9), pp. 923-943, http://dx.doi.org/10.1080/17538947.2016.1266041.
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Computer Software, Aerospace Engineering, Geological Sciences and Engineering (Other)
Journal Section Research Articles
Authors

Deniztan Ulutaş Karakol 0000-0002-2131-1057

Çetin Cömert 0000-0002-2019-6990

Publication Date March 13, 2021
Submission Date January 29, 2021
Acceptance Date March 8, 2021
Published in Issue Year 2021 Volume: 2 Issue: 1

Cite

APA Ulutaş Karakol, D., & Cömert, Ç. (2021). Meteorolojik Verilerin Bağlantılı Veriye Dönüştürülmesi: Karadeniz Bölgesi Örneği. Türk Uzaktan Algılama Ve CBS Dergisi, 2(1), 47-58. https://doi.org/10.48123/rsgis.869992
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