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Data Integration

Data integration (also called information integration) is the process of consolidating data from a set of heterogeneous data sources into a single uniform data set (materialized integration) or view on the data (virtual integration). Data integration pipelines involve subtasks such as schema matching, table annotation, entity resolution, value normalization, data cleansing, and data fusion. Application domains of data integration include data warehousing, data lakes, and knowledge base consolidation. Surveys on Data integration:

Papers

Showing 3140 of 431 papers

TitleStatusHype
MapperGPT: Large Language Models for Linking and Mapping EntitiesCode1
Know2BIO: A Comprehensive Dual-View Benchmark for Evolving Biomedical Knowledge GraphsCode1
Towards Lightweight Data Integration using Multi-workflow Provenance and Data ObservabilityCode1
Is your data alignable? Principled and interpretable alignability testing and integration of single-cell dataCode1
Column Type Annotation using ChatGPTCode1
Using ChatGPT for Entity MatchingCode1
Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data IntegrationCode1
Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and ToolkitCode1
Unsupervised Entity Alignment for Temporal Knowledge GraphsCode1
WDC Products: A Multi-Dimensional Entity Matching BenchmarkCode1
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