Our organisation

Edelweiss Connect is a Swiss SME located in Basel, specialised in developing and implementing integrated scientific and technology solutions for industrial use and regulatory acceptance in areas of significant societal and market impact. EwC has extensive experience in scientific research and innovation integrating data, in silico and in vitro methods and related infrastructure into solutions, and has been involved in organising scientific, technical and knowledge management solution development projects since 2008.

Our role in the project

EwC is leading WP 1, which will

  • provide a Safe and Sustainable Design (SSbD) Framework,
  • develop, refine and evaluate a SSbD4CheM task library and workflow, and
  • develop, test, deploy and evaluate knowledge resources supporting workflows for case studies

Our main role is in developing and implementing a data management ecosystem to deliver structured, harmonised, and semantically annotated using established ontologies data and rich metadata as per the FAIR data principles. Open Science practices will be implemented, where possible considering commercially sensitive data. These will be expressed in a detailed data management plan (DMP) that will be produced using the Horizon Europe template and digitised via OpenAire’s Argos tool. The ecosystem will translate to the data infrastructure (including the SSbD4CheM knowledgebase) required by the systems design and implemented as part of the SSbD workflows in T1.4. This will include database technology to capture and store: (a) processed data and metadata required as inputs (WPs 2-7) by workflow tasks or provided as outputs from workflow tasks (WPs 2, 4-6), (b) data from background knowledge resources including literature and public databases, (c) data provided by tasks and local databases existing within WPs 2-7. All data will be directly linked to their metadata (including a methods and protocols repository) and FAIRified with the use of unique identifiers. (d) Data and metadata exchange interfaces with external databases and tools developed within SSbD4CheM. (e) A user-friendly software application with a user interface for acceptance of user inputs and generation of tasks results and reports.

We will apply and refine algorithms and protocols (and develop new ones where appropriate) that assist and enable the effective execution of SSbD workflows in T1.4 (WPs 2, 3). We will consider selection from a) knowledge mining, graph, discovery and language model approaches applied to background knowledge, b) scoring criteria and protocols to be applied to data provided to any specific workflow task e.g., read across, sustainability, economic analysis, life cycle, environmental scoring etc., c) definition of protocols for obtaining decision results e.g., an uncertainty threshold may flag the need for further evidence before a decision can be made; a weighting function can be specified to arrive at a consensus decision including across conflicting or heterogeneous evidence for the same or multiple endpoints and scoring factors, d) ability to document and store any protocol used by any task.

We will also design and develop a workflow framework and software for creating and executing SSbD4CheM workflows. The implementation will include:

  1. a task library where component tasks are defined and stored based on the outcomes of the data-driven tools (WP2), the human health and environmental safety assessment (WP4), the exposure assessment and risk management (WP5), and the sustainability and LCA assessment (WP6);
  2. a workflow design editor where tasks are assembled into a workflow for a specific product design, sustainability and risk assessment context and demonstrated via the case studies (WP7);
  3. a workflow execution system for running a specific workflow including a user interface for exchange of data, addition of interpretations and selection of decisions validated via the case studies (WP7);
  4. a reporting and memory module where all workflow execution results can be stored and reported; and
  5. a demonstration of the workflow based on the results of the case studies (WP7).
Main person involved

Barry Hardy
Exploitation & Data management expert