Lecture
Automated Graph-Based Data Integration and Information Fusion
- at -
- ICM Saal 3
- Type: Lecture
Lecture description
Information is a vital part of research. While there are likely exceptions, almost all research projects process or produce data, or both. Storage of information in digital form provides many advantages, such as large capacities or easy and immediate access across locations. However, new challenges arise as well necessitating specialized software and paradigms for efficient data storage, integration, and analysis. The ever-growing number of available online databases is a vast source of information for research projects. Data integration tools and workflows are available providing researchers with the means to combine and interconnect heterogeneous source
databases. Each tool uses specific database systems and integration methodologies but also introduces certain constraints.
The BioDWH2 ecosystem of tools provides a fully automated and customizable process for the creation of analysis-ready graph databases from heterogeneous data sources. A wide range of data source modules give access to common information sources in the
life sciences such as DrugBank, BRENDA, and more. An extensible core architecture further allows the addition of new data source modules where required. Depending on project requirements select data sources can be integrated and mapped. A web-based interface allows this process to be as simple and straightforward as possible. New methodologies in information disambiguation allow concise mapping of chemical molecules increasing data quality and subsequent analyses.
Several use cases utilize different levels of BioDWH2 data integration and mapping results, demonstrating the ability to support projects with up-to-date information for analyses as well as in larger data integration pipelines.
databases. Each tool uses specific database systems and integration methodologies but also introduces certain constraints.
The BioDWH2 ecosystem of tools provides a fully automated and customizable process for the creation of analysis-ready graph databases from heterogeneous data sources. A wide range of data source modules give access to common information sources in the
life sciences such as DrugBank, BRENDA, and more. An extensible core architecture further allows the addition of new data source modules where required. Depending on project requirements select data sources can be integrated and mapped. A web-based interface allows this process to be as simple and straightforward as possible. New methodologies in information disambiguation allow concise mapping of chemical molecules increasing data quality and subsequent analyses.
Several use cases utilize different levels of BioDWH2 data integration and mapping results, demonstrating the ability to support projects with up-to-date information for analyses as well as in larger data integration pipelines.
