Classifying the LOD cloud: Digging into the knowledge graph

Daniel Martínez Ávila; Richard P. Smiraglia; Rick Szostak; Andrea Scharnhorst; Wouter Beek; Ronald Siebes; Laura Ridenour; Vanessa Schlais

doi:10.36311/1981-1640.2018.v12n4.02.p6

Autores/as

Daniel Martínez Ávila Universidade Estadual Paulista https://orcid.org/0000-0003-2236-553X
Richard P. Smiraglia School of Information Studies, University of Wisconsin-Milwaukee (USA) https://orcid.org/0000-0003-0724-1926
Rick Szostak University of Alberta https://orcid.org/0000-0001-8570-4418
Andrea Scharnhorst Data Archiving and Networked Services, Royal Netherlands Academy of the Arts and Sciences, The Hague, The Netherlands) https://orcid.org/0000-0001-8879-8798
Wouter Beek Vrije Universiteit (Amsterdam, The Netherlands) https://orcid.org/0000-0003-0250-9655
Ronald Siebes Data Archiving and Networked Services, Royal Netherlands Academy of the Arts and Sciences, The Hague, The Netherlands) https://orcid.org/0000-0001-8772-7904
Laura Ridenour School of Information Studies, University of Wisconsin-Milwaukee (USA) https://orcid.org/0000-0003-0460-789X
Vanessa Schlais School of Information Studies, University of Wisconsin-Milwaukee (USA) https://orcid.org/0000-0001-7690-4389

DOI:

https://doi.org/10.36311/1981-1640.2018.v12n4.02.p6

Palabras clave:

Linked Open Data, Knowledge Organisation Systems, Big Data, Knowledge Graph

Resumen

Massive amounts of data from different contexts and producers are collected and connected relying often solely on statistical techniques. Problems to the acclaimed value of data lie in the precise definition of data and associated contexts as well as the problem that data are not always published in meaningful and open ways. The Linked Data paradigm offers a solution to the limitations of simple keywords by having unique, resolvable and shared identifiers instead of strings This paper reports on a three-year research project “Digging Into the Knowledge Graph,” funded as part of the 2016 Round Four Digging Into Data Challenge (https://diggingintodata.org/awards/2016/project/digging-knowledge-graph). Our project involves comparing terminology employed within the LOD cloud with terminology employed within two general but different KOSs – Universal Decimal Classification and Basic Concepts Classification. We are exploring whether these classifications can encourage greater consistency in LOD terminology and linking the largely distinct scholarly literatures that address LOD and KOSs. Our project is an attempt to connect the Linked Open Data community, which has tended to be centered in computer science, and the KO community, with members from linguistics, metaphysics, library and information science. We focus on the shared challenges related to Big Data between both communities.

Descargas

Los datos de descarga aún no están disponibles.

Biografía del autor/a

Richard P. Smiraglia, School of Information Studies, University of Wisconsin-Milwaukee (USA)

Referencias

Berners-Lee, Tim; Hendler, James; Lassila, Ora (2001). The Seman-tic Web. // Scientific American. (May 2001) 1-4.
Borgman, Christine L. (2016). Big data, little data, no data: scholar-ship in the networked world. Cambridge, MA: The MITPress, 2016.
Bizer, Christian; Boncz, Peter; Brodie, Michael L.; Erling, Orri. (2011). The Meaningful Use of Big Data: Four Perspectives -Four challenges. // SIGMOD. 40:4 (2011). 56-60.
Gregory, Kathleen; Cousijn, Helena; Groth, Paul; Scharnhorst, An-drea; Wyatt, Sally. (2018). Understanding Data Retrieval Practices: A Social Informatics Perspective. Preprint, Retrieved from http://arxiv.org/abs/1801.04971.
Hey, Tony, Stewart Tansley and Kristin Tolle. (2009). The Fourth Paradigm: Data-Intensive ScientificDiscovery. Redmond: Mi-crosoft research, 2009.
Hitzler, Pascal and Krzysztof Janowicz. (2013). Linked Data, Big Data, and the 4th Paradigm. // Semantic Web. 4:3 (2013)233-235.
Hjørland, Birger. (2015). Theories are Knowledge Organizing Sys-tems(KOS). // Knowledge Organization. 42:2 (2015)113-128.
Hjørland, Birger. (2016). Knowledge Organization (KO). // Knowledge Organization. 43:6 (2016)475-484.
Ibekwe-SanJuan, Fidelia and Bowker, Geoffrey C. (2017). Implications of Big Data for Knowledge Organization. // Knowledge Organization. 44:3 (2017)187-198.Mai, Jens-Erik. (2016). Big data privacy: The datafication of personal information. // The Information Society. 32:3 (2016)192-199.
Martínez-Ávila, Daniel. (2015). Knowledge Organization in the Intersection with Information Technologies. // Knowledge Or-ganization 42:7 (2015)486-498.
Martínez-Ávila, Daniel. (2018). Hacía una base teórica social de la Ciencia de la Información. // Anuario ThinkEPI. 12 (2018)83-89.
Martínez-Ávila, Daniel; SanSegundo, Rosa; Zurian, Francisco A. (2014). Retos y oportunidadesen organización del conocimiento en la intersección con las tecnologías de la información. // Revista Española de Documentación Científica. 37:3 e053 (2014). DOI: http://dx.doi.org/10.3989/redc.2014.3.1112.
Mayer-Scho?nberger, Viktor; Cukier, Kenneth. (2013). Big data: A revolution that will transform how we live, work, and think. New York: Houghton Mifflin Harcourt, 2013.
Mazzocchi, Fulvio. (2015). Could Big Data be the end of theory in science? A few remarks on the epistemology of data-driven sci-ence. //EMBO reports. 16:10 (2015). 1250-1255.
Pauleen, David J.; Rooney, David; Intezari, Ali. (2016). Big data, little wisdom: trouble brewing? Ethical implications for the information systems discipline. // Social Epistemology, DOI: 10.1080/02691728.2016.1249436.
Shiri, Ali. (2014). Linked Data Meets Big Data: A Knowledge Or-ganization Systems Perspective. // Advances in Classification Research Online 24: 16-20. DOI:10.7152/acro.v24i1.14672.
Smiraglia, Richard P. (2012). Knowledge Organization: Some Trendsin an Emergent Domain. // El Profesional de la Infor-mación. 21:3 (2012). 225-227.
Smiraglia, Richard P.; Szostak, Rick. (2018). Converting UDC to BCC: Comparative Approaches to Interdisciplinarity. // Challenges and Opportunities for Knowledge Organization in the Digital Age: Proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal, ed. Fernanda Ribei-ro, Maria Elisa Cerveira. Advances in Knowledge Organization 16.Würzburg: Ergon Verlag, 530-38.
Soergel, Dagobert. (2015).Unleashing the Power of Data through Organization: Structure and Connections for Meaning, Learning and Discovery. // Knowledge Organization 42:6 (2015). 401-427.
Szostak, Rick; Scharnhorst, Andrea; Beek, Wouter; Richard P. Smiraglia, Richard P. (2018). Connecting KOSs and the LOD Cloud. // Challenges and Opportunities for Knowledge Organization in the Digital Age: Proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal, ed. Fernanda Ribei-ro, Maria Elisa Cerveira. Advances in Knowledge Organization 16. Würzburg: Ergon Verlag, 521-29.