Deepak Unni

SPHN is a national initiative led by the Swiss Academy of Medical Sciences and the SIB Swiss Institute of Bioinformatics. Broadly speaking, SPHN develops, implements, and validates coordinated data infrastructures that make health-related data available, interoperable, and shareable for research in Switzerland. As a Scientific Coordinator at the SPHN Data Coordination Center, I focus on the semantic and metadata foundations of these FAIR data infrastructures, where my work includes:

• ·Engaging with clinical, research, and data provider stakeholders to capture domain semantics and formalize them in RDF
• ·Leading the adoption of semantic web technologies for data modeling, knowledge representation, and validation of health-related data
• ·Contributing to the design and evolution of the SPHN RDF Schema, integrating standard terminologies and ontologies to ensure semantic interoperability across Swiss hospitals
• ·Supporting the development and maintenance of open-source tools and ETL pipelines that help data providers produce, validate, and deliver FAIR-compliant data
• ·Building and deploying the SPHN Metadata Catalog, an end-to-end platform that makes SPHN data assets discoverable through rich, standards-based metadata
• ·Interfacing with local and international initiatives to ensure that SPHN Metadata Catalog is interoperable with other FAIR data infrastructures and aligned with global standards
• ·Promoting FAIR principles through documentation, training, and engagement with data providers, researchers and the broader scientific community

The German Human Genome-Phenome Archive (GHGA) is a national initiative within Germany's National Research Data Infrastructure (NFDI) that provides a secure, FAIR-compliant platform for storing, sharing, and analyzing human omics data. In this role, I:

• ·Collaborated with the Architecture Working Group to design and establish the GHGA platform, building on existing frameworks and well-established community standards
• ·Led the Metadata Task Force to design, curate, and maintain the GHGA Metadata Schema, enabling consistent description and discovery of human omics datasets

• ·Contributed to the design and development of the Monarch API, improving access to integrated genotype–phenotype data
• ·Collaborated with the UI development team to enhance the Monarch web interface and user experience
• ·Partnered with the data ingest team to explore new strategies for building and improving the integrated Monarch knowledge graph

• ·Extended the scope and functionality of the GO API in collaboration with the development team
• ·Worked with scientists and developers to apply next-generation GO annotations to model biological systems

• ·Helped define community standards for representing biological and biomedical data as knowledge graphs
• ·Modeled diverse types of biomedical data and coordinated ETL efforts across the project
• ·Developed tools for exchanging data between heterogeneous knowledge graph initiatives
• ·Led the development and evolution of the Biolink Model, a universal schema for knowledge graphs in clinical, biomedical, and translational science

• ·Built a flexible ETL pipeline for generating a knowledge graph focused on COVID-19 datasets
• ·Assisted in setting up RDF and Neo4j endpoints for the COVID-19 knowledge graph
• ·Engaged with researchers to prioritize potential therapeutic targets for COVID-19
• ·Integrated the COVID-19 knowledge graph into the National COVID Cohort Collaborative (N3C) and the COVID-19 International Research Team (COV-IRT)

• ·Development and maintenance of Apollo, a collaborative genome annotation editing tool
• ·Implementation and maintenance of tools for the Bovine Genome Database and Hymenoptera Genome Database
• ·Implementation, deployment and maintenance of a data warehouse for Bovine genomics (BovineMine), Hymenoptera genomics (HymenopteraMine), and Maize genetics (MaizeMine)