The data resources in toxicology are characterised primarily by their variety, with the data volume also becoming significant when considering integration with biological databases such as toxicogenomics data. The chapter presents an overview of data integration approaches from the information technology point of view (data warehouses, virtual integration, schema and entity matching techniques) as well as from the bioinformatics point of view, i.e., integrative data analysis. Integration of different data sources requires the “shared representation of a domain”, which is best implemented by the use of ontologies, standard representations and Application Programming Interfaces (API). The chapter refers to an extensive number of resources and applications as an illustration of the existing approaches of data resource sharing, linking and integration. The importance of cloud technology, encompassing data storage, cheminformatics and data analysis tools is highlighted and the existing and emerging data sharing infrastructure is outlined, all supporting the handling and use of big data in the field of (predictive) toxicology.