loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Anastasija Nikiforova and Janis Bicevskis

Affiliation: Faculty of Computing, University of Latvia, 19 Raina Blvd., Riga and Latvia

Keyword(s): Data Quality, Contextual Control, Data Object, Executable Models, Domain-specific Modelling Language.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: This research is an extension of a data object-driven approach to data quality evaluation allowing to analyse data object quality in scope of multiple data objects. Previously presented approach was used to analyse one particular data object, mainly focusing on syntactic analysis. It means that the primary data object quality can be analysed against secondary data objects of unlimited number. This opportunity allows making more comprehensive, in-depth contextual data object analysis. The given analysis was applied to open data sets, making comparison between previously obtained results and results of application of the extended approach, underlying importance and benefits of the given extension.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.156.48.192

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Nikiforova, A. and Bicevskis, J. (2019). An Extended Data Object-driven Approach to Data Quality Evaluation: Contextual Data Quality Analysis. In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-372-8; ISSN 2184-4984, SciTePress, pages 274-281. DOI: 10.5220/0007838602740281

@conference{iceis19,
author={Anastasija Nikiforova. and Janis Bicevskis.},
title={An Extended Data Object-driven Approach to Data Quality Evaluation: Contextual Data Quality Analysis},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2019},
pages={274-281},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007838602740281},
isbn={978-989-758-372-8},
issn={2184-4984},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - An Extended Data Object-driven Approach to Data Quality Evaluation: Contextual Data Quality Analysis
SN - 978-989-758-372-8
IS - 2184-4984
AU - Nikiforova, A.
AU - Bicevskis, J.
PY - 2019
SP - 274
EP - 281
DO - 10.5220/0007838602740281
PB - SciTePress