DatAasee -- A Metadata-Lake as Metadata Catalog for a Virtual Data-Lake
Metadata management for distributed data sources is a long-standing but ever-growing problem. To counter this challenge in a research-data and library-oriented setting, this work constructs a data architecture, derived from the data-lake: the metadata-lake. A proof-of-concept implementation of this proposed metadata aggregator is presented and also evaluated.
Code (1)
Tasks
ManagementSimilar Papers 제목 키워드 기반
Auto-Tag: Tagging-Data-By-Example in Data Lakes
As data lakes become increasingly popular in large enterprises today, there is a growing need to tag or classify data assets (e.g., files and databases) in data lakes with additional metadata (e.g., semantic column-types…
TAGLeveraging Retrieval Augmented Generative LLMs For Automated Metadata Description Generation to Enhance Data Catalogs
Data catalogs serve as repositories for organizing and accessing diverse collection of data assets, but their effectiveness hinges on the ease with which business users can look-up relevant content. Unfortunately, many d…
LakeQuest: A Three-Domain Benchmark for Grounded Question Answering across Data Lakes
While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering questions over enterprise and scientific data lakes requires systems to na…
Question AnsweringExploring LLM Capabilities in Extracting DCAT-Compatible Metadata for Data Cataloging
Efficient data exploration is crucial as data becomes increasingly important for accelerating processes, improving forecasts and developing new business models. Data consumers often spend 25-98 % of their time searching …
Semantic Data Management in Data Lakes
In recent years, data lakes emerged as away to manage large amounts of heterogeneous data for modern data analytics. One way to prevent data lakes from turning into inoperable data swamps is semantic data management. Som…
Data IntegrationKnowledge GraphsManagement