ARIES for SEEA Explorer

The Statistics Division of the UN Department of Economic and Social Affairs (UN DESA) and the UN Environment Program (UNEP), in collaboration with the international research and innovation platform Artificial Intelligence for Environment & Sustainability (ARIES) at the Basque Centre for Climate Change (BC3), have developed a pioneering Artificial Intelligence (AI)-powered application for rapid natural capital accounting: the ARIES for SEEA Explorer!

k.LAB's remote engine is available online!

Knowledge Laboratory (k.LAB) is the open-source software powering ARIES. It supports selection of the most appropriate data and models using cloud technology and following an open data paradigm: the resulting insight, in the same fashion, remains open and available to society at large, and becomes a base for further computations, contributing to an ever-increasing knowledge base.

Making science matter in policy-making where nature counts

ARIES is a networked software technology that redefines sustainability assessment and valuation for decision-making. The ARIES approach to mapping natural capital, natural processes, human beneficiaries, and service flows to society is a powerful new way to visualize, value, and manage the ecosystems on which the human economy and well-being depend.

An adaptive modelling technology

Keeping it simple, but realistic

ARIES is an artificial intelligent modeller 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  how nature provides benefits to people.

Modelling 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 a network, and automatically assembled into model workflows following a user’s simple. The technology, which can be applied beyond the field of ecosystem services, is the first operational example of semantically integrated, distributed, collaborative modelling. As an international network of scientific collaborators contribute data and models, the ARIES system grows by itself, and each new assessment automatically adopts the best data and models available. In the next year, 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.