BioMedIT hosts a full repository of documentation on the BioMedIT Git Wiki.

BioMedIT nodes also provide standard data management solutions on-demand basis for the research projects based on OpenBis, LabKey, SLIMS etc. Please contact BioMedIT or your assigned BioMedIT node for more details. 

BioMedIT secure HPC service enables researchers to connect secure (HPC) clusters in the BioMedIT nodes directly from their home organizations to execute compute or memory intensive workflows leveraging the large CPU, memory and GPU resources of the nodes. BioMedIT secure HPC service is setup in an access-controlled, private environment offering network isolation, data isolation and computational resources isolation ensuring high standards of data security. Please E-mail BioMedIT or your assigned BioMedIT node for more details on this service. 

BioMedIT secure remote desktop service enables researchers to connect to a remote server in the BioMedIT nodes from their home organisation using a web browser. Please E-mail BioMedIT or your assigned BioMedIT node for more details.

The BioMedIT Code Repository Service (based on Git), is accessible to registered BioMedIT users to create, collaborate and share their application codes with other BioMedIT users.

Confluence is a collaboration space and repository for the working- and implementation groups, projects and iniatives.

Provides a secure, easy-to-use registry for hosting, vulnerabilities scanning and sharing of OCI compatible container images. E-mail BioMedIT to request access.

The SPHN Data Coordination Centre has produced a set of templates for legal agreements for data transfers and cross institutional collaboration within the scope of BioMedIT.

The single point of entry into the BioMedIT environment allowing access to central services, node services, user management for collaborative projects and data transfer request management.

sett is BioMedIT's bespoke secure encyption and transfer tool. This tool allows users to package and move their data around the BioMedIT network in a safe and legal manner.

The SPHN Dataset contains the main concept definitions for clinical and genomic data used in SPHN.

The SPHN RDF Schema enables the semantic encoding of clinical routine data in a FAIR (findable, accessible, interoperable, and reusable) format, using other existing standard ontologies. 

SPHN provides a set of tools to enable schema visualization, quality control, automatic SPARQL query generation, etc. Setup and installation of these tools are a time consuming process, which is why we developed an easy-to-use web service enabling users to get all files from a single application. This web service includes the following tools: Dataset2RDF, SHACLer, SPHN Schema Visualization Tool, SPARQLer.

SPHN provides the Dataset Template, a template to extend the SPHN Dataset, that can be used to design project specific concepts in Excel. This file can be used as input for the SPHN Schema Forge to get your project-specific RDF Schema.

The SPHN data quality control files contain a set of SHACL rules (e.g.validity of classes and properties. cardinalities and timeframe) and statistical SPARQL queries (e.g. counting instances or providing min and max values for quantities and datetimes) to validate the compliance of the RDF data produced.

The SPHN Mocker is an open-source Python library designed to facilitate the generation of SPHN-compatible mock data. The SPHN Mocker allows users to effortlessly generate realistic mock data in RDF (.ttl format), compliant with the SPHN RDF Schema.

The DCC Terminology Service provides SPHN compatible, machine-readable versions of national (CHOP or ICD-10 GM) and international (e.g. SNOMED CT, LOINC, ATC, SO, GENO, HGNC, UCUM) terminologies and classifications in RDF format. They are available directly in the individual project spaces on the BioMedIT nodes or for download through the BioMedIT Portal (via SWITCH edu-ID). 

The SPHN Schema Scope, the SPHN metadata catalogue, is available for discovering and exploring datasets of SPHN-funded and SPHN-related projects. It offers both intuitive accessibility for human users as well as structured metadata in machine-readable formats. The schema visualization allows researchers to traverse data schemas in a highly interactive way, simplifying the navigation of even the most complex data structures. The FAIR Data Point complements the visualization by providing corresponding metadata in both human and machine-readable formats, improving discoverability and helping datasets to meet the FAIR principles (findability, accessibility, interoperability, and reusability). Please note that the visualization may not reflect the full details of an individual concept in every case to improve readability. Please consult the pyLODE concept documentation for full details of individual concepts

Triple store and knowledge discovery tools enabling the visualization, exploration, knowledge inference and querying of specific data in RDF on a local instance. 

These tools are available on request in BioMedIT project spaces. 

The SPHN Connector is a tool developed to facilitate the creation of valid SPHN-compliant graph data based on relational, semantically described data from data-providing institutions.The connector creates an input interface based on an RDF Schema conforming to the SPHN Semantic Interoperability Framework. The ingested data is converted into RDF, validated to check its conformity with the schema, and de-identified.

Funding agencies commonly require researchers to submit a data management plan (DMP) when writing research proposals. The SPHN DMP guidelines offer general recommendations for the use of sensitive biomedical data to help researchers to plan the entire life cycle of their data, with particular focus on SPHN-funded projects using health-related data for research purposes, and data processing on the BioMedIT infrastructure.

The Swiss Cohort consortia is a network of Swiss Cohorts available on the internationally renowned Maelstrom metadata catalogue.

The SPHN Federated Query System allows researchers to assess, whether and where patients or patient data potentially suitable for a specific research question exists at Swiss University Hospitals.