nach oben

Erschienen in:

2020 | OriginalPaper | Buchkapitel

Constructing Knowledge Graphs from Data Catalogues

verfasst von : Adegboyega Ojo, Oladipupo Sennaike

Erschienen in: Distributed Computing and Internet Technology

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

We have witnessed about a decade’s effort in opening up government institutions around the world by making data about their services, performance and programmes publicly available on open data portals. While these efforts have yielded some economic and social value particularly in the context of city data ecosystems, there is a general acknowledgment that the promises of open data are far from being realised. A major barrier to better exploitation of open data is the difficulty in finding datasets of interests and those of high value on data portals. This article describes how the implicit relatedness and value of datasets can be revealed by generating a knowledge graph over data catalogues. Specifically, we generate a knowledge graph based on a self-organizing map (SOM) constructed from an open data catalogue. Following this, we show how the generated knowledge graph enables value characterisation based on sociometric profiles of the datasets as well as dataset recommendation.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel A Very Gentle Introduction to Multiparty Session Types

Nächstes Kapitel Round-Message Trade-Off in Distributed Steiner Tree Construction in the CONGEST Model

http://dublinked.ie/.

Ojo, A., Curry, E., Zeleti, F.A.: A tale of open data innovations in five smart cities. In: 2015 48th Hawaii International Conference on System Sciences, pp. 2326–2335 (2015)

Ojo, A., et al.: Realizing the innovation potentials from open data: stakeholders’ perspectives on the desired affordances of open data environment. In: Afsarmanesh, Hamideh, Camarinha-Matos, Luis M., Lucas Soares, António (eds.) PRO-VE 2016. IAICT, vol. 480, pp. 48–59. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45390-3_5CrossRef

Hogan, M., et al.: Governance, transparency and the collaborative design of open data collaboration platforms: understanding barriers, options, and needs BT. In: Ojo, A., Millard, J. (eds.) Government 3.0 – Next Generation Government Technology Infrastructure and Services: Roadmaps, Enabling Technologies & Challenges, pp. 299–332. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63743-3CrossRef

Sennaike, O.A., Waqar, M., Osagie, E., Hassan, I., Stasiewicz, A., Ojo, A.: Towards intelligent open data platforms, pp. 414–421, September 2017

Scarano, V., et al.: Fostering citizens’ participation and transparency with social tools and personalization. In: Ojo, A., Millard, J. (eds.) Government 3.0 – Next Generation Government Technology Infrastructure and Services: Roadmaps, Enabling Technologies & Challenges, pp. 197–218. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63743-3CrossRef

Ojo, A., et al.: A comprehensive architecture to support Open Data access, co-creation, and Dissemination. In: ACM International Conference Proceeding Series, pp. 0–1 (2018)

Janowski, M., Ojo, A., Curry, E., Porwol, L.: Mediating open data consumption - identifying story patterns for linked open statistical data. In: ACM International Conference Proceeding Series, vol. Part F148155, pp. 156–163 (2019)

Musa Aliyu, F., Ojo, A.: Towards building a knowledge graph with open data – a roadmap. In: AFRICOMM 2017: International Conference on e-Infrastructure and e-Services for Developing Countries, pp. 157–162 (2018)

Noy, N., Paulheim, H.: Knowledge graph refinement: a survey of approaches and evaluation methods. Semant. Web 8, 489–508 (2016)CrossRef

10.

Bonatti, P.A., Decker, S., Polleres, A., Presutti, V.: Knowledge graphs: new directions for knowledge representation on the semantic web. Report from Dagstuhl Seminar, vol. 8, no. 9, pp. 29–111 (2019)

11.

Le-Phuoc, D., Nguyen Mau Quoc, H., Ngo Quoc, H., Tran Nhat, T., Hauswirth, M.: The Graph of Things: a step towards the Live Knowledge Graph of connected things. J. Web Semant. 37–38, 25–35 (2016)

12.

Halaschek-wiener, C., Kolovski, V.: Towards a sales assistant using a product knowledge graph. Web Semant. Sci. Serv. Agents World Wide Web 6, 171–190 (2017)

13.

Jaradeh, M.Y., et al.: Open Research Knowledge Graph: Next Generation Infrastructure for Semantic Scholarly Knowledge (2019)

14.

Kejriwal, M.: What is a knowledge graph? Springer Briefs in Computer Science, pp. 1–7 (2019)CrossRef

15.

Kohonen, T.: The self-organizing map. Proc. IEEE 78(9), 1464–1480 (1990)CrossRef

16.

Kohonen, T., et al.: Self organization of a massive text document collection. Kohonen Maps 11(3), 171–182 (1999)CrossRef

17.

Yin, H.: The self-organizing maps: background, theories, extensions and applications. Stud. Comput. Intell. 115, 715–762 (2008)

18.

Weir, B.S., Anderson, A.D., Hepler, A.B.: Genetic relatedness analysis: Modern data and new challenges. Nat. Rev. Genet. 7(10), 771–780 (2006)CrossRef

19.

Nocker, E., Bowen, H.P., Stadler, C., Matzler, K.: Capturing relatedness: comprehensive measures based on secondary data. Br. J. Manag. 27, 197–213 (2016)CrossRef

20.

Budanitsky, A., Hirst, G.: Evaluating WordNet-based measures of lexical semantic relatedness. Comput. Linguist. 32(1), 13–47 (2006)CrossRef

21.

Patwardhan, S., Banerjee, S., Pedersen, T.: Using measures of semantic relatedness for word sense disambiguation. In: Gelbukh, A. (ed.) CICLing 2003. LNCS, vol. 2588, pp. 241–257. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36456-0_24CrossRef

22.

Stevenson, M., Greenwood, M.A.: A semantic approach to IE pattern induction. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL 2005 (2005)

23.

Zhu, Y., Yan, E., Wang, F.: Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec. BMC Med. Inform. Decis. Mak. 17, 95 (2017)CrossRef

24.

Lee, M.D., Pincombe, B., Welsh, M.: An empirical evaluation of models of text document similarity. In: Proceedings of the Annual Meeting of the Cognitive Science Society, pp. 1254–1259 (2005)

25.

Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. IJCAI Int. Jt. Conf. Artif. Intell. 7, 1606–1611 (2007)

26.

Rybinski, M., Aldana-Montes, J.F.: tESA: a distributional measure for calculating semantic relatedness. J. Biomed. Semantics 7, 67 (2016)CrossRef

27.

Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRef

28.

Shambour, Q., Lu, J.: Government-to-business personalized e-services using semantic-enhanced recommender system. In: Andersen, K.N., Francesconi, E., Grönlund, Å., van Engers, T.M. (eds.) EGOVIS 2011. LNCS, vol. 6866, pp. 197–211. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22961-9_16CrossRef

Titel: Constructing Knowledge Graphs from Data Catalogues
verfasst von: Adegboyega Ojo
Oladipupo Sennaike
Verlag: Springer International Publishing
Buch: Distributed Computing and Internet Technology
Print ISBN: 978-3-030-36986-6

Electronic ISBN: 978-3-030-36987-3

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-36987-3_6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"