# Charting Past, Present, and Future Research in the Semantic Web and Interoperability
## 5 Co-Citation Clustering Analysis
### Bioinformatics  
The theme in the sixth cluster was labeled \"bioinformatics\" and consists of 16 articles. With the exponential increase in both the volume and diversity of so-called \"omics\" data (i.e., proteomics, genomics, transcriptomics), there is a need to develop and adopt data standards to achieve the promise of systems biology [120]. The interrelated and complex nature of biological data raises several data and tool integration barriers. For this reason, several scholars within the bioinformatics community have studied several interoperability standards, solutions, and projects over the past decades. For example, ref. [106] illustrates the BioMoby project, which aims to standardize methodologies to synchronize information exchange and access to analytical resources through a consensus-driven approach. Unlike other semantic web service interoperability initiatives, this project is realized using a new type of XML schema derived from an ontology, aiming to define the biological intent and syntax of the data passed into and out of a service. The authors of [121] present Semantic Automated Discovery and Integration (SADI), a lightweight approach to simplify the discovery and consumption of semantic web services in bioinformatics and other scientific domains based on foundational web standards. The suggested approach enables bioinformatics software development with new interoperable and integrative behaviors. It helps accurately model the services and the end-user needs for the automated discovery of key services, the integration of the resulting data, and the automation of service pipelines. Similarly, ref. [122] describes another project, Open PHACTS, which aims to deliver and sustain an open pharmacological space based on existing and improved state-of-the-art semantic web standards and technologies. The project also improves drug discovery in academia and industry and drives open innovation and in-house non-public discovery research. To ensure user-oriented semantic service discovery, [123] proposes a data model and lightweight semantic discovery architecture that enables interoperability and composition across different autonomous third-party services, thereby providing a good fit for user requirements in bioinformatics and other domains. Finally, ref. [124] discusses three projects employing semantic web technologies to facilitate services' automated discovery and compositions and enable seamless and transparent interoperability, including Grid, MOBY-Services, and Semantic-MOBY. Overall, the literature highlights that the semantic web promises to foster integration and interoperability among different bioinformatics resources on the web. However, this promise is not broadly realizable in practice, as the reasons for failure may be attributed to the basic difference between semantic web technologies and web services. Therefore, researchers should develop more advanced and scalable solutions that address the deficiencies in the reuse of Universal Resource Identifiers (URIs), the lack of accessibility of bioinformatics data, and the need for large-scale data integration for biological phenomena. Methods and tools that provide a semantics-rich representation of data and efficiently exploit highly heterogenous data are required [125]. Moreover, it is necessary to adjust current computational systems to assimilate and integrate the diversification in bioinformatics research and solve existing knowledge-related and interoperability challenges [126].