A better way to model ecosystem services
An ecosystem of models
- Models and data are developed by the individual, independent experts;
- Open source technology allows researchers and institutions to add models and data to the network;
- Models and data can be made available to all users or restricted communities;
- Artificial Intelligence negotiates the most appropriate models to solve user queries;
- Transparent documentation can be generated for all the models used and their integrated results.
Two-step rapid assessment
- Step 1: set the context (for example, searching for a watershed name, or drawing a region on an online map)
- Step 2: find a concept representing the issue of interest using free-form search, and drop it on the context to observe it.
At that point, ARIES will use its internal knowledge and the data and models on the network to creates agents and processes, connect them into a flow network, and produce a complete assessment of socio-ecological structure and function in the context.
An adaptive modeling technology
Keeping it simple – not wrong!
ARIES is an intelligent modeler rather than a single model or collection of models. ARIES chooses ecological process models where appropriate, and turns to simpler models where process models do not exist or are inadequate. Based on a simple user query, ARIES builds all the agents involved in the nature/society interaction, connects them into a flow network, and creates the best possible models for each agent and connection. The result is a detailed, adaptive, and dynamic assessment of the real system providing benefits.
Modeling on the semantic web
ARIES is based on the radically novel k.LAB technology, which allows models and data to be contributed by independent researchers, hosted on the network, and automatically assembled into model workflows built upon a simple query by a user. The technology, not specific of ecosystem services, is the first operational example of semantically integrated, distributed, collaborative modeling. The ARIES ecosystem grows by itself, and each new assessment automatically adopts the best data and models available. In 2016, users will be able to not only develop, but also run models directly from the world wide web, enabling a simple, two-step modeling workflow suitable for non-technical users, such as decision makers and their staff.