Modelling & Workflows
A brief overview
Ecologists produce and have access to an incredible amount of data. These data come from diverse sources: European Research Infrastructures, national and regional monitoring schemes, and our own projects. We frequently use an equally diverse set of models to understand how humans affect biodiversity across scales. Yet, when we do analyses, we each develop our own ways of how to integrate data – even if they come from common sources (e.g., LTER or Copernicus). Once we publish our results, we rarely go back to validate our outputs as new information becomes available, meaning that our ability to anticipate ecological change remains limited.
In this working group, we aim to turn models into open, automated, interoperable, and scalable workflows for ecological predictions, building on the capabilities of LifeWatch ERIC. We integrate data and models into modular pipelines that are not only openly accessible to researchers and decision makers, but also are dynamic and sustainable as they are integrated into the cyberinfrastructure of LWE. We work as a community that consists of computer analysts, statisticians, ecologists, economists, social scientists, and resource managers – where we borrow from the methods and strengths of different fields to create integrated outputs.
Let’s transform ecological data into dynamic, open predictions that evolve with new knowledge. Be part of a collaborative community building interoperable, automated workflows to better anticipate ecological change, and stay connected for updates, tools, and opportunities to shape the future of ecological predictions!
Need help joining?
Check our FAQs
A brief overview
Ecologists produce and have access to an incredible amount of data. These data come from diverse sources: European Research Infrastructures, national and regional monitoring schemes, and our own projects. We frequently use an equally diverse set of models to understand how humans affect biodiversity across scales. Yet, when we do analyses, we each develop our own ways of how to integrate data – even if they come from common sources (e.g., LTER or Copernicus). Once we publish our results, we rarely go back to validate our outputs as new information becomes available, meaning that our ability to anticipate ecological change remains limited.
In this working group, we aim to turn models into open, automated, interoperable, and scalable workflows for ecological predictions, building on the capabilities of LifeWatch ERIC. We integrate data and models into modular pipelines that are not only openly accessible to researchers and decision makers, but also are dynamic and sustainable as they are integrated into the cyberinfrastructure of LWE. We work as a community that consists of computer analysts, statisticians, ecologists, economists, social scientists, and resource managers – where we borrow from the methods and strengths of different fields to create integrated outputs.
Let’s transform ecological data into dynamic, open predictions that evolve with new knowledge. Be part of a collaborative community building interoperable, automated workflows to better anticipate ecological change, and stay connected for updates, tools, and opportunities to shape the future of ecological predictions!
Need help joining?
Check our FAQs
In the spotilight
Key Objectives
- Create a shared glossary that standardizes terminology among computer scientists, ecologists, and stakeholders, enabling clear and effective communication of highly technical terminology, including of some resources offered by LWE (for instance, workflows have different meaning to different people).
- Publish glossary and make available to stakeholders.
- Identify core open source environmental and biodiversity data (e.g., geospatial, sensors) used across different disciplines.
- Map availability of workflows already exiting in the LWE catalogue to get and process the data and identify gaps.
- Develop interoperable workflows that allow to automatically download and process publicly available core data for predictions, complementing available workflows.
- Develop workflows that allow users to pick different models and scenarios to predict changes in target variables.
- Develop workflows that convert outputs into products that are relevant for a range of decision makers.
Photo by Leonid Nyshko
