Determining category metadata in open data portals – an approach based on Formal Concept Analysis

The efforts for data transparency and open government initiatives have resulted in a large amount of data being published on open data portals. These portals are organized to enhance published data accessibility by providing search mechanisms that utilize metadata such as category, tags, format, and publisher. However, due to the metadata incompleteness, such as missing category information, datasets are harder to find. Therefore, within this paper, we address the issue of missing category information by proposing an approach for categorizing datasets using keywords and their usage within categories. The presented approach is based on the Formal Concept Analysis method, which is used to create a hierarchical order of keywords grounded on their usage within categories on one open data portal. Further, we present the evaluation of the presented method using data from the Canadian open data portal.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/telfor63250.2024.10819115
Primary Topic
Semantic Web and Ontologies
Type
article
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article

Determining category metadata in open data portals – an approach based on Formal Concept Analysis

Leonid Stoimenov, Miloš Bogdanović, Milena Frtunić Gligorijević
Semantic Web and Ontologies
article

Determining category metadata in open data portals – an approach based on Formal Concept Analysis

Leonid Stoimenov, Miloš Bogdanović, Milena Frtunić Gligorijević
article en

Abstract

The efforts for data transparency and open government initiatives have resulted in a large amount of data being published on open data portals. These portals are organized to enhance published data accessibility by providing search mechanisms that utilize metadata such as category, tags, format, and publisher. However, due to the metadata incompleteness, such as missing category information, datasets are harder to find. Therefore, within this paper, we address the issue of missing category information by proposing an approach for categorizing datasets using keywords and their usage within categories. The presented approach is based on the Formal Concept Analysis method, which is used to create a hierarchical order of keywords grounded on their usage within categories on one open data portal. Further, we present the evaluation of the presented method using data from the Canadian open data portal.

University of Nis (RS)
Openalex Percentile: Top 77%
Semantic Web and Ontologies
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