# Semantic Metadata Annotation Services in the Biomedical Domain--A Literature Review
## 2 Definition and Requirements of a Semantic Metadata Annotation Service  
Data harmonization refers to the process of annotating/enriching data elements with vocabulary semantic codes. Ideally, a community agreed standard or quasi standard is used. As a result, harmonized data are more interoperable, correspond to the \"I\" in FAIRand allow the computer to \"understand\" the meaning of data. In this context, we define a metadata annotation service as a supporting tool to enrich data elements within a digital object (e.g., a data dictionary or questionnaire) with semantic codes. Figure 1 illustrates the process of semantic metadata annotation of data collection instruments. Based on harmonization efforts published in the Maelstroem project and on use cases and a number of data annotation pilots addressed in NFDI4 Health, we have gathered requirements for suitable software supporting this process. A typical harmonization use case in both projects would be the enrichment with semantic codes of all questions and response items in a questionnaire used in a public health survey. In the following, we describe the challenges for a semantic metadata annotation service and the basic requirements that derive from the health and epidemiology domain, especially from the NFDI4 Health project. Beyond NFDI4 Health, we also consider open science and generalization aspects as important requirements. All identified requirements are summarized in Table 1 with short descriptions and a prioritization order we agreed upon in NFDI4 Health. The first requirement addresses openness and generalization of the tools. Since different formats are expected to some extent and adaptation of the software to a specific use case is required, the software must be available under an open-source license or should at least be openly accessible (Requirement 1). A key feature is the combinability with existing, optimally specified and standardized data exchange formats. This is a mandatory requirement for a service that enables the annotation of data elements within a data object. Examples include the standard formats HL7 FHIR [13] and CDISC ODM [14] in the medical field. Therefore, different input and output formats must be supported or the technical interface must allow extension to other formats (Requirement 2). Figure 1: Data collection instruments are released in different standard and nonstandard formats. Without semantic annotation, they are not semantically interoperable. A metadata annotation service could facilitate semantic annotation and conversion to a standardized format. Semi-automatic support through annotation suggestions and integrated concept searching by providing interfaces to terminologies/ontologies and terminology services could help researchers overcome the challenges of this process. The enrichment of metadata should follow FAIR principles. Consequently, the vocabularies and thus terminologies used for annotation must also be FAIR (Requirement 3), as stated in the FAIR Interoperability Principle: \"(Meta)data use vocabularies that follow the FAIR principles\" ([PERSON] et al. 2016) [2]. Two other requirements (Requirements 4 and 5) relate to the functionality of the system. Annotation of data elements is labor intensive and often involves a large number of elements, so this process should be as simple as possible. As a result, simply releasing or rejecting autonomously created annotations (Requirement 5) is preferred to manually searching for the appropriate concept (Requirement 4). However, we consider the feature of searching for a concept more important than an autonomous recommendation system, and hence prioritized the former as a must and the latter as a recommendation. In addition, the semantic classes that can be annotated should be configurable, as each specific use case may require its own set. This requirement can either mean that custom ontologies/terminologies can be used or integrated into the software, or that a connection to a terminology/ontology or SPARQL [15] service can be configured.