A Quality Management Workflow Proposal for a Biodiversity Data Repository- A User-Centered Methodology for the Evaluation of (Semantic) Web Service Discovery and Selection
- Aggregation of similarity measures in schema matching based on generalized mean
- An Introduction to the Data Retrieval Facilities of the XQt Language for Scientific Data
- Explorative Analysis of Heterogeneous, Unstructured, and Uncertain Data: A Computer Science Perspective on Biodiversity Research
- Improving Clustering-based Schema Matching using Latent Semantic Indexing
- Partitioning-based Ontology Matching Approaches: A Comparative Analysis
- Preparing Array Analytics for the Data Tsunami
- Process-oriented Semantic Knowledge Management in Product Lifecycle Management
- Recommending Judgment Targets for Rating Provision
- Towards Semantic Recommendation of Biodiversity Datasets based on Linked Open Data
A Quality Management Workflow Proposal for a Biodiversity Data Repository
| Title: | A Quality Management Workflow Proposal for a Biodiversity Data Repository |
|---|---|
| Authors: | Michael Owonibi, Birgitta Koenig-Ries |
| Source: | 33rd International Conference on Conceptual Modeling, Atlanta, GA, USA |
| Date: | 2014-10-23 |
| Type: | Publication |
| Abstract: |
The importance of quality-assured data in scientific analysis necessitates the inclusion of data quality management (DQM) functionality in research data repositories in addition to their primary role of data storage, sharing and integration. Typically, the DQM workflow in data repositories is fixed and semi-automated for datasets whose structure and semantics is known a-priori, however, for other types of datasets, DQM is either manual or minimal. In comparison, classical DQM methodology (especially in data warehousing research) has established standard, typically manually undertaken, DQM procedures for different types of data. Therefore, our proposal aims at customizing and semi-automating the classical DQM procedures for bio-diversity data repositories. As opposed to reviewing scientific contents of the data, we focus on technical data quality. Our proposed workflow includes DQM criteria specification, client and server-side validation, data profiling, error detection analysis, data enhancement and correction, and quality monitoring. |
| URL: | http://link.springer.com/chapter/10.1007%2F978-3-319-12256-4_17 |
| BibTex: |
@incollection{
year={2014},
isbn={978-3-319-12255-7},
booktitle={Advances in Conceptual Modeling},
volume={8823},
series={Lecture Notes in Computer Science},
editor={Indulska, Marta and Purao, Sandeep},
doi={10.1007/978-3-319-12256-4_17},
title={A Quality Management Workflow Proposal for a Biodiversity Data Repository},
url={http://dx.doi.org/10.1007/978-3-319-12256-4_17},
publisher={Springer International Publishing},
author={Owonibi, Michael and Koenig-Ries, Birgitta},
pages={157-167},
language={English}
} |