Integration of heterogeneous data sources into unified systems that support analysis, search, and knowledge-driven applications.
The work can include schema mapping, data normalization, APIs, metadata, entity matching, storage design, and synchronization.
Examples include scientific data portals, organizational knowledge platforms, biodiversity systems, and multi-source research databases.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.