• Computer Science
  • Published in IEEE Data Eng. Bull. 2018

Making Open Data Transparent: Data Discovery on Open Data

@article{Miller2018MakingOD,
  title={Making Open Data Transparent: Data Discovery on Open Data},
  author={Ren{\'e}e J. Miller and Fatemeh Nargesian and Erkang Zhu and Christina Christodoulakis and Ken Q. Pu and Periklis Andritsos},
  journal={IEEE Data Eng. Bull.},
  year={2018},
  volume={41},
  pages={59-70}
}
Open Data plays a major role in open government initiatives. Governments around the world are adopting Open Data Principles promising to make their Open Data complete, primary, and timely. These properties make this data tremendously valuable. Open Data poses interesting new challenges for data integration research and we take a look at one of those challenges, data discovery. How can we find new data sets within this ever expanding sea of Open Data. How do we make this sea transparent? 

Tables and Topics from this paper.

Explore Further: Topics Discussed in This Paper

Citations

Publications citing this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 48 REFERENCES

Aurum: A Data Discovery System

  • 2018 IEEE 34th International Conference on Data Engineering (ICDE)
  • 2018
VIEW 1 EXCERPT

Building Data Civilizer Pipelines with an Advanced Workflow Engine

  • 2018 IEEE 34th International Conference on Data Engineering (ICDE)
  • 2018
VIEW 1 EXCERPT

J

E. Abel, J. A. Keane, +3 authors N. Konstantinou
  • C. C. Rı́os, N. A. Azuan, and S. M. Embury. User driven multi-criteria source selection. Inf. Sci., 430:179–199
  • 2018

Seeping Semantics: Linking Datasets Using Word Embeddings for Data Discovery

  • 2018 IEEE 34th International Conference on Data Engineering (ICDE)
  • 2018
VIEW 1 EXCERPT

T

A. Joulin, E. Grave, P. Bojanowski
  • Mikolov. Bag of tricks for efficient text classification. ACL
  • 2017
VIEW 2 EXCERPTS