Metadata Management for Textual Documents in Data Lakes

Abstract : Data lakes have emerged as an alternative to data warehouses for the storage, exploration and analysis of big data. In a data lake, data are stored in a raw state and bear no explicit schema. Thence, an efficient metadata system is essential to avoid the data lake turning to a so-called data swamp. Existing works about managing data lake metadata mostly focus on structured and semi-structured data, with little research on unstructured data. Thus, we propose in this paper a methodological approach to build and manage a metadata system that is specific to textual documents in data lakes. First, we make an inventory of usual and meaningful metadata to extract. Then, we apply some specific techniques from the text mining and information retrieval domains to extract, store and reuse these metadata within the COREL research project, in order to validate our proposals.
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Communication dans un congrès
INSTICC. 21st International Conference on Enterprise Information Systems (ICEIS 2019), May 2019, Heraklion, Greece. 2019, 〈http://www.iceis.org/〉
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https://hal.archives-ouvertes.fr/hal-02012092
Contributeur : Jérôme Darmont <>
Soumis le : vendredi 8 février 2019 - 14:26:05
Dernière modification le : samedi 9 février 2019 - 01:22:25

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  • HAL Id : hal-02012092, version 1

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Pegdwendé Sawadogo, Tokio Kibata, Jérôme Darmont. Metadata Management for Textual Documents in Data Lakes. INSTICC. 21st International Conference on Enterprise Information Systems (ICEIS 2019), May 2019, Heraklion, Greece. 2019, 〈http://www.iceis.org/〉. 〈hal-02012092〉

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