Magazine article AI Magazine

Semantics for Big Data

Magazine article AI Magazine

Semantics for Big Data

Article excerpt

One of the key challenges in making use of big data lies in finding ways of dealing with heterogeneity, diversity, and complexity of the data, while its volume and velocity forbid solutions available for smaller data sets as based, for example, on manual curation or manual integration of data. Semantic web technologies (Hitzler, Krötzsch, and Rudolph 2010) are meant to deal with these issues, and indeed since the advent of linked data (Bizer, Heath, and Berners-Lee 2009) a few years ago, they have become central to mainstream semantic web research and development. We can easily understand linked data as being a part of the greater big data landscape, as many of the challenges are the same (Hitzler and Janowicz 2013). The linking component of linked data, however, puts an additional focus on the integration and conflation of data across multiple sources.

At the AAAI Fall Symposium in November 2013, we explored opportunities and challenges arising from transferring and adapting semantic web technologies to the big data quest. This issue of AI Magazine is a follow-up from that meeting and contains significantly extended, enhanced, and updated contributions. We summarize the articles in the following paragraphs.

The introductory article, Why the Data Train Needs Semantic Rails, by Krzysztof Janowicz, Frank van Harmelen, James A. Hendler, and Pascal Hitzler, discusses the opportunities and challenges related to combining formal semantics with data analytics approaches. It is followed by Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation by Lora Aroyo and Chris Welty, which discusses how to deal with subjectivity using a crowd-based approach.

Exploiting Semantics for Big Data Integration by Craig A. Knoblock and Pedro Szekely shows how to use semantics to integrate heterogeneous data in a cultural heritage use case, while Semantics-Empowered Big Data Processing with Applications by Krishnaprasad Thirunarayan and Amit Sheth addresses the role of semantics in analyzing and processing big data that arises in the context of physical-cyber-social systems. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.