Annotation Workbench - Improve data interoperability through semantic Annotation

The Metadata Annotation Workbench facilitates the categorization of data collection instruments in clinical and epidemiological studies, thereby improving data categorisation and findability for increased research efficiency

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In clinical and epidemiologic studies, data collection instruments such as case report forms, data dictionaries, and questionnaires are essential for metadata collection. These instruments contain complex and specific information for research. Categorization, i.e. the assignment of individual data to categories, helps to gain a quicker overview and understanding of the usually large and complex data.

Establishing semantic interoperability through accurate and unique data descriptions and variable information enables the exact meaning of the data to be preserved.

The Metadata Annotation Workbench helps to

  • make the data interoperable for cross-study comparisons,
  • categorise the data for better findability

and thus promote data reuse.

The Metadata Annotation Workbench supports enriching spreadsheet documents with standardised semantic codes from terminologies and ontologies. The web application uses the terminology service SemLookP to gain access to up-to-date and domain-relevant vocabulary and to ensure quality and interoperability of the semantic codes. The service comes as web application that provides a user-friendly interface, enabling researchers to upload data collection instruments in standard formats, such as Microsoft Excel spreadsheets. The annotation process benefits from SemLookP's search and visualisation functionalities. For the NFDI4Health relevant Maelstrom Research Taxonomy, an automatic annotation feature is integrated.

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What is Semantic Interoperability?

Semantic interoperability enables the automatic interpretation of shared information in a meaningful way. In health research, achieving semantic interoperability is critical for cross-study comparisons and analyses to preserve the meaning of the data. Terminologies and ontologies play a key role in achieving semantic interoperability by providing standardized concepts and relationships for annotation.

Beispiele

Annotation with the terminology FoodEx2:

The current variable and annotations are displayed in the upper area. In this example, the variable 'vegetable' was annotated with the concept 'Vegetables and vegetable products'. At the bottom left is the SemLookP-based search, at the bottom right metadata on the current concept is displayed. .

Annotation mit der medizinischen Terminologie SNOMED CT:

The current variable and annotations are displayed in the upper area. In this example, the variable ‚Do you suffer from an acute or chronic mental illness?‘ was annotated with the concept ‚Chronic disease (disorder)‘. At the bottom left is the SemLookP-based search, at the bottom right metadata on the current concept is displayed.