Moon landing or safari? A study of systematic errors and their causes in geographic linked data

Krzysztof Janowicz*, Yingjie Hu, Grant McKenzie, Song Gao, Blake Regalia, Gengchen Mai, Rui Zhu, Benjamin Adams, Kerry Taylor

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

12 Citations (Scopus)


While the adoption of Linked Data technologies has grown dramatically over the past few years, it has not come without its own set of growing challenges. The triplification of domain data into Linked Data has not only given rise to a leading role of places and positioning information for the dense interlinkage of data about actors, objects, and events, but also led to massive errors in the generation, transformation, and semantic annotation of data. In a global and densely interlinked graph of data, even seemingly minor error can have far reaching consequences as different datasets make statements about the same resources. In this work we present the first comprehensive study of systematic errors and their potential causes. We also discuss lessons learned and means to avoid some of the introduced pitfalls in the future.

Original languageEnglish
Title of host publicationGeographic Information Science - 9th International Conference, GIScience 2016, Proceedings
EditorsDavid O’Sullivan, Nancy Wiegand, Jennifer A. Miller
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319457376
Publication statusPublished - 2016
Event9th International Conference on Geographic Information Science, GIScience 2016 - Montreal, Canada
Duration: 27 Sept 201630 Sept 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9927 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Geographic Information Science, GIScience 2016

Bibliographical note

Funding Information:
The authors would like to acknowledge partial support by the National Science Foundation (NSF) under award 1440202 EarthCube Building Blocks: Collaborative Proposal: GeoLink Leveraging Semantics and Linked Data for Data Sharing and Discovery in the Geosciences, NSF award 1540849 EarthCube IA: Collaborative Proposal: Cross-Domain Observational Metadata Environmental Sensing Network (X-DOMES), and the USGS award on Linked Data for the National Map.

Publisher Copyright:
© Springer International Publishing Switzerland 2016.


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