BioRI landscape

[dagendresen]

Biodiversity Research Infrastructure (bioRI) landscape

DiSSCo has made recent work on mapping the bioRI landscape

• https://www.dissco.eu/dissco/ri-landscape/
• Whitepaper on bioRIs, https://doi.org/10.3897/rio.6.e62361

[ErikKusch]

Following the bioRI workshop in Warsaw, I have identified a few ideas for how to approach our work task on the BioRI landscape supporting BioDT.

The three key aspects I aim to investigate are:

1. Quantifying the European BioRI landscape underpinning BioDT

Create a graph representation of the BioRI landscape like has been done in previous settings )here and here). Novelty: I have a few ideas for how to generate weighted graphs which, to my understanding, has not been done before.

2. Identifying and measuring relevant Key Performance Indicators (KPIs) for the BioRI landscape and its submodules

So far, I am considering a set of these KPIs:

1. Data Ingestion:

• Data Volume: Measure the total amount of biodiversity data ingested over a specific period.
• Data Completeness: Assess the percentage of available biodiversity data successfully ingested.
• Data Quality: Evaluate the accuracy, consistency, and reliability of ingested data.

  2. Data Distribution:

• Data Accessibility: Measure the ease of access to biodiversity data for users.
• Data Usage: Track the number of data queries or downloads made by users.
• User Satisfaction: Gather user feedback on the usefulness and usability of the distributed data.

  3. Infrastructure Performance:

• System Uptime: Measure the availability and reliability of the infrastructure.
• Response Time: Assess the speed at which the infrastructure responds to user requests.
• Scalability: Evaluate the ability of the infrastructure to handle increasing data volumes and user traffic.

  4. Data Integration and Interoperability:

• Data Harmonization: Evaluate the level of integration and compatibility of diverse biodiversity data sources.
• Interoperability: Measure the ease of integrating the infrastructure with other data systems or platforms.
• Standard Compliance: Assess adherence to relevant data standards and protocols (e.g., Darwin Core).

  5. Impact and Outreach:

• Data Usage in Research: Track the number of research studies or publications citing the infrastructure's data.
• Collaboration: Measure the number of partnerships and collaborations established with other organizations.
• Outreach and Engagement: Evaluate the efforts to engage with the scientific community, policymakers, and the general public.

3. Creating and proposing a strategy for improved BioRI collaboration and coordination

To this end, I am planning to put together a mock-up GitHub space, develop guidelines for using it and subsequently trialing it out with a set of BioRI staff before promoting these new means of intra- and cross-BioRI coordination.