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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

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Showing 21–30 of 431 papers

TitleStatusHype
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference—0
TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset—0
CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis—0
CDE-Mapper: Using Retrieval-Augmented Language Models for Linking Clinical Data Elements to Controlled Vocabularies—0
Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking—0
Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer—0
Deep Multi-modal Breast Cancer Detection Network—0
Leveraging Language Models for Automated Patient Record Linkage—0
Generalized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observationsCode0
Simplifying Data Integration: SLM-Driven Systems for Unified Semantic Queries Across Heterogeneous Databases—0
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