Crowdsourcing Semantics for Big Data in Geoscience Applications

Document Type

Presentation

Publication Date

2013

Abstract

The interleaving of human, machine, and semantics have the potential to overcome some of the issues currently surrounding Big Data. Semantic technologies, in particular, have been shown to adequately address data integration when dealing with data size, variety, and complexity of data sources – the very definition of Big Data. Yet, for some tasks, semantic algorithms do not reach a level of accuracy that many production environments require. In this position paper, we argue that augmenting such algorithms with crowdsourcing is a viable solution. In particular, we examine Big Data within the geosciences and describe outstanding questions regarding the merger of crowdsourcing and semantics. We present our ongoing work in this area and discuss directions for future research.

Comments

Technical Report FS-13-04

Presented at the AAAI 2013 Fall Symposium Series Semantics for Big Data, Arlington, VA, November 15-17, 2013.

Additional Files
narock_hitzler_aaai.pdf (6264 kB)
Presentation
Link to Full Text

Additional Files

narock_hitzler_aaai.pdf (6264 kB)
Presentation


Share

COinS