ARIES maps the agents of provision of ecosystem services (sources), their beneficiaries (use), and any biophysical features that can deplete service flows (sinks) automatically choosing the best available models and data. Through artificial intelligence and innovative semantic modeling, ARIES assembles spatial data and expert-contributed model components – deterministic or probabilistic – to quantify and map ecosystem services, at the appropriate spatial scales and specifically for each ecological and socio-economic context.

Models and data used in ARIES are stored on an expanding semantic web. While users can provide their own data and models, an extensible network hosts data, models and model services that are assembled according to context. In this kind of collaborative modelling:

1. Models and data are developed by the individual, independent experts;
2. Open source technology allows researchers and institutions to add models and data to the network;
3. Models and data can be made available to all users or restricted communities;
4. Artificial Intelligence negotiates the most appropriate models to solve user queries;
5. Transparent documentation can be generated for all the models used and their integrated results.

On the user side, ARIES enables a simple, two-step ecosystem service assessment process. Client software (desktop & soon web-based) allows modeling with minimal configuration and training. After users are logged into the network (through a secure certificate), modeling reduces to

• 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 uses 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.