Araştırma Makalesi
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Petrol, Gaz ve Madencilik Endüstrisinde Bilgi Gösterimi için Ontoloji Temelli bir Yaklaşım

Yıl 2019, Cilt: 12 Sayı: 2, 147 - 158, 30.04.2019
https://doi.org/10.17671/gazibtd.469637

Öz

Petrol, gaz ve madencilik endüstrisinde semantik web teknolojilerini kullanan bazı çalışmalar olsa da bunların çoğu, sondaj, keşif ve üretim gibi çeşitli faaliyetlere ait verilerin toplanması ve analizi ile ilgilidir. Öte yandan, döngü sürelerini ve dolaylı maliyetleri önemli ölçüde azaltabilen semantik web uygulamaları geliştirmek de mümkündür. Bu çalışma, semantik web teknolojileri ile petrol, gaz ve madencilik endüstrisi arasındaki boşluğu dolduran bir uygulamadır. Bu çalışma kapsamında bir sondaj araçları ontolojisi prototipi önerilmektedir. Önerilen ontolojinin popülasyonu için başlangıç olarak matkap ucu örnekleri seçilmiştir. Ontoloji popülasyonu sürecinde mevcut e-tablo dokümanları, ürün katalogları ve ürün verilerini içeren web sayfaları kullanılmıştır. Bu makalede, çalışma sürecinde edinilen ontoloji geliştirme deneyimi ve bu deneyimin diğer çalışmalarda nasıl kullanılabileceği açıkça anlatılmaktadır. Seçilen ontoloji popülasyonu yöntemleri, matkap uçlarının yanısıra değişik alanlardaki birçok ürün için de uygulanabilir. Bu nedenle, önerdiğimiz yöntemin uygulanabilirliği, bu çalışmada ele alınan ürünlerin ötesine uzanmaktadır. Bu çalışmada ayrıca, önerilen ontolojiyi kullanarak, farklı satıcılara ait matkap uçlarını aramayı ve karşılaştırmayı destekleyen bir matkap ucu portalı da sunulmaktadır.

Kaynakça

  • [1] B. Zhang, X. Wang, H. Li, M. Jiang, “Knowledge modelling of coal mining equipments based on ontology”, IOP Conference Series- Earth and Environmental Science, 69, 121-136, 2017.
  • [2] L. Overa, Semantic technology in the oil and gas drilling domain, Masters Thesis, University of Oslo, 2010.
  • [3] T. Berners-Lee, J.Hendler, O. Lassila, “The Semantic Web”, Scientific American, 284, 34-43, 2010.
  • [4] T.R. Gruber, “A Translation Approach to Portable Ontology Specifications”, Knowledge Acquisition, 5, 199 -220, 1993.
  • [5] M.K. Smith, C. Welty, D.L. McGuinness, OWL Web Ontology Language Guide, W3C Technical Report, 2004.
  • [6] S. Lemaignan, A. Siadat, J. Y. Dantan, A. Semenenko, “MASON: A proposal for an ontology of manufacturing domain”, IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06), Prague, Czech Republic, 195-200, 15-16 June, 2006.
  • [7] D. Ç. Ertuğrul, “FoodWiki: a mobile app examines side effects of food additives via semantic web“, Journal of medical systems, 40(2), 41, 2016.
  • [8] X. Aimé, S. George, J. Hornung. "VetiVoc: a modular ontology for the fashion, textile and clothing domain.", Applied Ontology, 11(1), 1-28, 2016.
  • [9] Ö. Can , M. Ünalır, “Ontoloji Tabanlı Bilgi Sistemlerinde Politika Yönetimi”, Bilişim Teknolojileri Dergisi, 3(2), 1-16, 2010.
  • [10] C. Aydın, V. Tecim, “Afet Yönetimi İçin Coğrafi Tabanlı Deprem Ontolojileri”, Bilişim Teknolojileri Dergisi, 8(1), 1-8, 2015.
  • [11] Ö. Gümüş, Ö. Gürcan, O. Dikenelli, “Anlamsal Servis Aracılığı İçin Bir Çok Etmenli Sistem ve Aracılık Etkileşim Protokolü”, Bilişim Teknolojileri Dergisi, 5(2), 9-24, 2012.
  • [12] H. Sevindik Menteş, Design and Development of a Mineral Exploration Ontology, Masters Thesis, Georgia State University, 2012.
  • [13] N.F. Noy, R.W. Fergerson, M.A. Musen, “The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility”, Knowledge Engineering and Knowledge Management Methods, Models, and Tools, Juan-les-Pins, France, 17-32, 2000.
  • [14] L. Yu, A Developer’s Guide to the Semantic Web, Springer, Berlin Heidelberg, Germany, 2011.
  • [15] M. Janik, A. Scherp, S. Staab, “The Semantic Web: Collective Intelligence on the Web”, Informatik Spektrum, 34, 469-483, 2011.
  • [16] R.V. Guha, D. Brickley, S. Macbeth, “Schema.org: Evolution of Structured Data on the Web”, Communications of the ACM, 59, 44-51, 2016.
  • [17] M. Hepp, “GoodRelations: An Ontology for Describing Products and Services Offers on the Web”, International conference on Knowledge Engineering- Practice and Patterns, Acitrezza, Italy, 329-346, 2008.
  • [18] M.E. Hossain, A.A. Al-Majed, Fundamentals of Sustainable Drilling Engineering, Wiley, Massachusetts, USA, 2015.
  • [19] A. Rustan, C. Cunningham, W. Fourney, A. Spathis, K.R.Y. Simha, Mining and Rock Construction Technology Desk Reference: Rock Mechanics, Drilling & Blasting, Florida, USA, CRC Press, 2010.
  • [20] T.A. Inglis, Directional drilling, London, UK, Graham & Trotman, 1987.
  • [21] Grand View Research, Oil and Gas Drill Bit Market Worth $7.62 Billion By 2022, Technical Report, 2015.
  • [22] T. Ozacar, “Iris: a protege plug-in to extract and serialize product attribute name-value pairs”, Second International Workshop on Finance and Economics on the Semantic Web co-located with 11th European Semantic Web Conference, Creete, Greece, 2014.
  • [23] T. Ozacar, “A tool for producing structured interoperable data from product features on the web”, Information Systems, 56, 36-54, 2016.
  • [24] Internet: M. Bowler, “HtmlUnit”, http://htmlunit.sourceforge.net/, 11.10.2018.
  • [25] O. Ozturk, “OPPCAT: Ontology population from tabular data”, Journal of Information Science, https://doi.org/10.1177/0165551519827892, 2019. [26] Internet: M. Aristaran, M. Tigas, J.B. Merrill, “Introducing Tabula”, https://source.opennews.org/en-US/articles/introducing-tabula, 11.10.2018.
  • [27] J. Brank, M. Grobelnik, D. Mladenic, “A survey of ontology evaluation techniques”, Conference on Data Mining and Data Warehouses, Copenhagen, Denmark, 2005.
  • [28] H. Hlomani, D. Stacey, “Approaches, methods, metrics, measures, and subjectivity in ontology evaluation: A survey”, Semantic Web Journal, 1-5, 2014.
  • [29] V. Sugumaran, J.A. Gulla, Applied Semantic Web Technologies, CRC Press, Germany, 2011.
  • [30] F. Ensan, W. Du, “A semantic metrics suite for evaluating modular ontologies”, Information Systems, 38, 745-770, 2013.
  • [31] R. Porzel, R. Malaka, “A task-based approach for ontology evaluation”, ECAI 2004 Workshop on Ontology Learning and Population, Valencia, Spain, 2004.
  • [32] M.A. Sicili, D. Rodriguez, E. Garcia-Barriocanal, S. Sanchez-Alonso, “Empirical findings on ontology metrics”, Expert Systems with Applications, 39, 6706-6711, 2012.
  • [33] A. Lozano-Tello, A. Gómez-Pérez, “ONTOMETRIC: A Method to Choose the Appropriate Ontology”, Journal of Database Management, 15, 2004.
  • [34] S. Tartir, I.B. Arpinar, “Ontology Evaluation and Ranking using OntoQA”, International Conference on Semantic Computing, San Francisco, USA, 185-192, 2007.
  • [35] H. Yao, A.M. Orme, L. Etzkorn, “Cohesion Metrics for Ontology Design and Application”, Journal of Computer Science, 1, 107-113, 2005.

An Ontology Based Approach for Knowledge Representation in Oil, Gas and Mining Industry

Yıl 2019, Cilt: 12 Sayı: 2, 147 - 158, 30.04.2019
https://doi.org/10.17671/gazibtd.469637

Öz

Although there are some works applying semantic web technologies in oil, gas, and mining industry, most of them involve finding and analyzing the data from a variety of activities such as drilling, exploration and production. On the other hand, it is also possible to develop semantic web applications that may dramatically reduce cycle times and indirect costs. This work is a practice that bridges the gap between semantic web technologies and oil, gas, and mining industry. We propose a prototype drilling tools ontology. We populate the ontology focusing on drill bit concept as a starting point. In the population phase, we used existing spreadsheet documents, product catalogs and web pages containing product data. We document clearly what has been learned from the experience of building the ontology and how the experience can inform the work of other investigators. The same ontology population methods apply also to other products; therefore, the applicability of our work extends well beyond the specific products we are considering in our project. This ontology is also used in a prototype drill bit marketplace portal, which supports searching and comparing drill bits of different vendors.

Kaynakça

  • [1] B. Zhang, X. Wang, H. Li, M. Jiang, “Knowledge modelling of coal mining equipments based on ontology”, IOP Conference Series- Earth and Environmental Science, 69, 121-136, 2017.
  • [2] L. Overa, Semantic technology in the oil and gas drilling domain, Masters Thesis, University of Oslo, 2010.
  • [3] T. Berners-Lee, J.Hendler, O. Lassila, “The Semantic Web”, Scientific American, 284, 34-43, 2010.
  • [4] T.R. Gruber, “A Translation Approach to Portable Ontology Specifications”, Knowledge Acquisition, 5, 199 -220, 1993.
  • [5] M.K. Smith, C. Welty, D.L. McGuinness, OWL Web Ontology Language Guide, W3C Technical Report, 2004.
  • [6] S. Lemaignan, A. Siadat, J. Y. Dantan, A. Semenenko, “MASON: A proposal for an ontology of manufacturing domain”, IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06), Prague, Czech Republic, 195-200, 15-16 June, 2006.
  • [7] D. Ç. Ertuğrul, “FoodWiki: a mobile app examines side effects of food additives via semantic web“, Journal of medical systems, 40(2), 41, 2016.
  • [8] X. Aimé, S. George, J. Hornung. "VetiVoc: a modular ontology for the fashion, textile and clothing domain.", Applied Ontology, 11(1), 1-28, 2016.
  • [9] Ö. Can , M. Ünalır, “Ontoloji Tabanlı Bilgi Sistemlerinde Politika Yönetimi”, Bilişim Teknolojileri Dergisi, 3(2), 1-16, 2010.
  • [10] C. Aydın, V. Tecim, “Afet Yönetimi İçin Coğrafi Tabanlı Deprem Ontolojileri”, Bilişim Teknolojileri Dergisi, 8(1), 1-8, 2015.
  • [11] Ö. Gümüş, Ö. Gürcan, O. Dikenelli, “Anlamsal Servis Aracılığı İçin Bir Çok Etmenli Sistem ve Aracılık Etkileşim Protokolü”, Bilişim Teknolojileri Dergisi, 5(2), 9-24, 2012.
  • [12] H. Sevindik Menteş, Design and Development of a Mineral Exploration Ontology, Masters Thesis, Georgia State University, 2012.
  • [13] N.F. Noy, R.W. Fergerson, M.A. Musen, “The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility”, Knowledge Engineering and Knowledge Management Methods, Models, and Tools, Juan-les-Pins, France, 17-32, 2000.
  • [14] L. Yu, A Developer’s Guide to the Semantic Web, Springer, Berlin Heidelberg, Germany, 2011.
  • [15] M. Janik, A. Scherp, S. Staab, “The Semantic Web: Collective Intelligence on the Web”, Informatik Spektrum, 34, 469-483, 2011.
  • [16] R.V. Guha, D. Brickley, S. Macbeth, “Schema.org: Evolution of Structured Data on the Web”, Communications of the ACM, 59, 44-51, 2016.
  • [17] M. Hepp, “GoodRelations: An Ontology for Describing Products and Services Offers on the Web”, International conference on Knowledge Engineering- Practice and Patterns, Acitrezza, Italy, 329-346, 2008.
  • [18] M.E. Hossain, A.A. Al-Majed, Fundamentals of Sustainable Drilling Engineering, Wiley, Massachusetts, USA, 2015.
  • [19] A. Rustan, C. Cunningham, W. Fourney, A. Spathis, K.R.Y. Simha, Mining and Rock Construction Technology Desk Reference: Rock Mechanics, Drilling & Blasting, Florida, USA, CRC Press, 2010.
  • [20] T.A. Inglis, Directional drilling, London, UK, Graham & Trotman, 1987.
  • [21] Grand View Research, Oil and Gas Drill Bit Market Worth $7.62 Billion By 2022, Technical Report, 2015.
  • [22] T. Ozacar, “Iris: a protege plug-in to extract and serialize product attribute name-value pairs”, Second International Workshop on Finance and Economics on the Semantic Web co-located with 11th European Semantic Web Conference, Creete, Greece, 2014.
  • [23] T. Ozacar, “A tool for producing structured interoperable data from product features on the web”, Information Systems, 56, 36-54, 2016.
  • [24] Internet: M. Bowler, “HtmlUnit”, http://htmlunit.sourceforge.net/, 11.10.2018.
  • [25] O. Ozturk, “OPPCAT: Ontology population from tabular data”, Journal of Information Science, https://doi.org/10.1177/0165551519827892, 2019. [26] Internet: M. Aristaran, M. Tigas, J.B. Merrill, “Introducing Tabula”, https://source.opennews.org/en-US/articles/introducing-tabula, 11.10.2018.
  • [27] J. Brank, M. Grobelnik, D. Mladenic, “A survey of ontology evaluation techniques”, Conference on Data Mining and Data Warehouses, Copenhagen, Denmark, 2005.
  • [28] H. Hlomani, D. Stacey, “Approaches, methods, metrics, measures, and subjectivity in ontology evaluation: A survey”, Semantic Web Journal, 1-5, 2014.
  • [29] V. Sugumaran, J.A. Gulla, Applied Semantic Web Technologies, CRC Press, Germany, 2011.
  • [30] F. Ensan, W. Du, “A semantic metrics suite for evaluating modular ontologies”, Information Systems, 38, 745-770, 2013.
  • [31] R. Porzel, R. Malaka, “A task-based approach for ontology evaluation”, ECAI 2004 Workshop on Ontology Learning and Population, Valencia, Spain, 2004.
  • [32] M.A. Sicili, D. Rodriguez, E. Garcia-Barriocanal, S. Sanchez-Alonso, “Empirical findings on ontology metrics”, Expert Systems with Applications, 39, 6706-6711, 2012.
  • [33] A. Lozano-Tello, A. Gómez-Pérez, “ONTOMETRIC: A Method to Choose the Appropriate Ontology”, Journal of Database Management, 15, 2004.
  • [34] S. Tartir, I.B. Arpinar, “Ontology Evaluation and Ranking using OntoQA”, International Conference on Semantic Computing, San Francisco, USA, 185-192, 2007.
  • [35] H. Yao, A.M. Orme, L. Etzkorn, “Cohesion Metrics for Ontology Design and Application”, Journal of Computer Science, 1, 107-113, 2005.
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Yazılımı
Bölüm Makaleler
Yazarlar

Övünç Öztürk 0000-0001-7127-7902

Yayımlanma Tarihi 30 Nisan 2019
Gönderilme Tarihi 11 Ekim 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 12 Sayı: 2

Kaynak Göster

APA Öztürk, Ö. (2019). An Ontology Based Approach for Knowledge Representation in Oil, Gas and Mining Industry. Bilişim Teknolojileri Dergisi, 12(2), 147-158. https://doi.org/10.17671/gazibtd.469637