A1. Interaction design for environmental information systems
Daryl H. Hepting, Steven Frysinger, Markus Wrobel
Environmental Informatics (or enviromatics) is a maturing subject with interdisciplinary roots. The application of information and communication technology (ICT) to the environment is emerging as one of great importance as the health of our planet gains priority on research agendas. Modelling is an important aspect of enviromatics, but it is not the only one.
Ultimately, environmental information must be put into peoples' hands so that they can make decisions. How best to involve stakeholders, so that they can access the information they need and put it to use in a satisfying manner, remains a topic of inquiry. Underlying the larger benefits of enviromatics as a tool for policy decisions, is the architecture that enables those decision making processes. To maximize the value of the enviromatics infrastructure, interaction design must be an integral part of the architectural plan. How do we best employ metaphor in educating users and influencing their mental models? What are the ethical concerns involved and how can they be addressed? Appropriate design helps the user to improve the quality of the information that is produced, presented, and used.
Contributions are sought that deal with human factors in enviromatics. We seek to put work on interaction design and human computer interaction into the specific context of enviromatics, with the goal of understanding how to draw on and apply existing knowledge to enviromatics so that efforts are focused on refinement and adaptation instead of reinvention.
Topics include, but are not limited to:
This session is linked with workshop A4 "Defining interaction design for environmental information systems".
A2. Striking the balance - advancing multi-objective decision support for a changing world
Andrea Castelletti, Alexander Lotov, Francesca Pianosi, Patrick Reed, Dragan Savic
The multi-objective nature of environmental modelling and planning problems has long been recognized to arise from the combined effects of increasing pressures on natural resources and diverse stakeholder perspectives. The discovery and negotiated exploitation of critical tradeoffs for environmental systems must embrace the growing spectrum of social groups playing an active role in decision-making processes. Multi-objective optimization (MOO) has been extensively used to support decision-making under conflicting objectives at all decision levels, from monitoring to model calibration, from planning to real-time operation, with application in a wide range of fields including agro-forestry systems, land use planning, water systems, air pollution, transport systems, etc. Despite the wide spectrum of theoretical and application advances, there is the need to advance the capabilities and use MOO given the dramatic innovations in computational and information services over the last decade.
This session is aimed at bringing together researchers and practitioners involved in developing and applying MOO, to discuss and compare experiences in facing novel challenges including:
A3. Intelligent Environmental Decision Support Systems (IEDSS): from single methods to an automatic semantic interoperability of artificial intelligence/mathematical/statistical methods (S-IEDSS-2012)
Miquel Sanchez Marre, Karina Gibert, Joaquim Comas, Ignasi Rodriguez Roda, Manel Poch, Ulises Cortes, Rick Sodja, Jean Philippe Steyer, Peter Struss, Mihaela Oprea, Franz Wotawa, Rene Banares-Alcantara
The session will establish a discussion platform for Artificial Intelligence (AI) and environmental researchers involved in the development of techniqes, frameworks, software platforms or applications in the Intelligent Environmental Decision Support Systems (IEDSS) area. Single AI techniques such as rule-based reasoning, fuzzy models, case-based reasoning, qualitative reasoning, artificial neural networks, genetic algorithms and programming, model-based reasoning, Bayesian networks, and multi-agent systems provide a solid basis for construction of reliable and real applications, but there is the general agreement among researchers that a semantic interoperability of AI techniques is the main open challenge in this field. Thus, this is the proposed main issue for the session. IEDSS are present in the environmental management process at different levels such as hazard identification, risk assessment, risk evaluation and intervention decision-making, but there is neither a well defined methodology or framework for the development of IEDSSs nor for model integration nor for model recommendation techniques nor for benchmarking and validation of IEDSSs. Outstanding applications and case studies of IEDSSs with important contributions are also welcome. Other open issues can be addressed, such as the spatial reasoning, temporal reasoning, and uncertainty modelling and management in IEDSSs. These are the open challenges to be addressed by the session papers, and special emphasis will be given to Environment's sake issues. Session participants may come from all environmental science and AI or statistical modelling fields.
This session is linked with workshop (D12).
A5. System Identification and Control Theory applications for Environmental Systems Management
Andrea Castelletti, Marialuisa Volta, Andrea E. Rizzoli
The session provides the forum for presenting and discussing new methodological and applicative developments in Systems Identification and Control Theory for environmental modelling and decision-making. The aim is to review the state-of-the-art of systems and control approaches, to discuss novel and improved techniques and to look at feasible developments to the future.
Environmental systems considered include, but are not limited to, air pollution (at the global, regional and local scale) and climate change, land (forests, biomasses, etc.) and water resource systems (surface and ground waters, marine and coastal waters).
Approaches include system identification, non-linear modelling and control techniques as well as artificial intelligence, data mining and machine learning methods. Particularly welcome are contributions on real time control, distributed control, and large scale system control.
A6. Innovative approaches and components in Environmental Modelling and Software
David Swayne, Holly C. Hartmann
Environmental modelling and software research projects frequently uncover surprising applications of informatics which are not always anticipated in advance. These innovative approaches are often buried in the details of the concepts and implementations. Innovations in informatics have to be demonstrated in practice to be understood and appreciated. For instance, the difficulties encountered in the implementation of probabilistic networks were largely solved in the 1980s, and yet their deployment in environmental applications is still evolving thirty years hence. Innovation also has difficulty keeping up with the huge speedups in computing power.
Papers to be considered should present interesting implications for environmental informatics research and application.