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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 251260 of 431 papers

TitleStatusHype
Current and future directions in network biology0
When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence System0
A Multimodal Learning Framework for Comprehensive 3D Mineral Prospectivity Modeling with Jointly Learned Structure-Fluid Relationships0
Scaling Data Science Solutions with Semantics and Machine Learning: Bosch Case0
Crowd Safety Manager: Towards Data-Driven Active Decision Support for Planning and Control of Crowd Events0
BIM-to-BRICK: Using graph modeling for IoT/BMS and spatial semantic data interoperability within digital data models of buildings0
A Primer on the Data Cleaning Pipeline0
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity0
Alternative Telescopic Displacement: An Efficient Multimodal Alignment MethodCode0
A Comparison of Neuroelectrophysiology Databases0
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