Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Databases

arXiv:2007.06540 (cs)
[Submitted on 9 Jul 2020 (v1), last revised 15 Jun 2022 (this version, v2)]

Title:Open Data Quality

Authors:Anastasija Nikiforova
View PDF
Abstract:The research discusses how (open) data quality could be described, what should be considered developing a data quality management solution and how it could be applied to open data to check its quality. The proposed approach focuses on development of data quality specification which can be executed to get data quality evaluation results, find errors in data and possible problems which must be solved. The proposed approach is applied to several open data sets to evaluate their quality. Open data is very popular, free available for every stakeholder - it is often used to make business decisions. It is important to be sure that this data is trustable and error-free as its quality problems can lead to huge losses.
Comments: 10 pages, 3 figures, 13th International Baltic Conference on Databases and Information Systems & The Baltic DB&IS 2018 Doctoral Consortium (Baltic DB&IS 2018) At: Lithuania, Trakai, Volume: 2158. arXiv admin note: substantial text overlap with arXiv:2007.04697
Subjects: Databases (cs.DB); Computers and Society (cs.CY)
Cite as: arXiv:2007.06540 [cs.DB]
  (or arXiv:2007.06540v2 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.2007.06540
Journal reference: Baltic DB&IS 2018 Joint Proceedings of the Conference Forum and Doctoral Consortium

Submission history

From: Anastasija Nikiforova [view email]
[v1] Thu, 9 Jul 2020 11:10:22 UTC (386 KB)
[v2] Wed, 15 Jun 2022 08:20:12 UTC (350 KB)
Full-text links:

Access Paper:

license icon view license
Current browse context:
cs.DB
< prev   |   next >
new | recent | 2020-07
Change to browse by:
cs
cs.CY

References & Citations

DBLP - CS Bibliography

listing | bibtex
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)