WASOS: An Ontology for Modelling Traditional Knowledge of Sustainable Water Stewardship

Recent work and publications concerning sustainable water stewardship in Rajasthan (India) highlight how contemporary challenges are eroding traditional, communal approaches to water stewardship through mechanised extraction beyond the renewable capacities of ecosystems. Our work is focused on developing a formal ontology for modelling the knowledge of traditional water stewardship in India’s drylands by capturing the key constitutional elements of regenerative methods. Our method follows an iterative evolving prototype process for delivering the first version of the Ontology for Sustainable Water Stewardship (WASOS). The ontology contains a moderate number of high-level classes and properties that represent the water management decisionmaking process. By making key relationships visible, we aim to support decision-making in complex catchments particularly where there are contested urban and rural claims on water

Scientific instruments for climate change adaptation: estimating and optimizing the efficiency of ecosystem service provision

Adaptation to the consequences of climate change can depend on efficient use of ecosystem services (ES), i.e. a better use of natural services through management of the way in which they are delivered to society. While much discussion focuses on reducing consumption and increasing production of services, a lack of scientific instruments has so far prevented other mechanisms to improve ecosystem services efficiency from being addressed systematically as an adaptation strategy. This paper describes new methodologies for assessing ecosystem services and quantifying their values to humans, highlighting the role of ecosystem service flow analysis in optimizing the efficiency of ES provision.Ecosystem services, flow analysis, Bayesian modeling, spatial analysis, Environmental Economics and Policy, Q01, Q54, Q55, Q57,

Modeling the semantics of contextual and content-specific research metadata using ontology languages: issues on combining CERIF and OWL

Current Research Information Systems (CRISs) enable the maintenance of information related to research activities of organizations and their members, including outputs or products from these activities. Such contextual information is of uttermost importance for the processing of datasets and with the retrieval of scientific documents, providing e.g. the key information on provenance and characteristics of research activities that are needed when searching for data or scholarly content. In the context of the expanding initiative of the Web of Linked Data, translating that information into semantic languages enables new ways of querying benefitting from the reuse of domain ontologies. In that direction, this paper reports on the engineering of an ontology based version of the CERIF standard for CRISs using the OWL language and a proposed mapping to research datasets

Modeling the semantics of contextual and content-specific research metadata using ontology languages: issues on combining CERIF and OWL

Current Research Information Systems (CRISs) enable the maintenance of information related to research activities of organizations and their members, including outputs or products from these activities. Such contextual information is of uttermost importance for the processing of datasets and with the retrieval of scientific documents, providing e.g. the key information on provenance and characteristics of research activities that are needed when searching for data or scholarly content. In the context of the expanding initiative of the Web of Linked Data, translating that information into semantic languages enables new ways of querying benefitting from the reuse of domain ontologies. In that direction, this paper reports on the engineering of an ontology based version of the CERIF standard for CRISs using the OWL language and a proposed mapping to research datasets

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

BRIDGING THE GAP BETWEEN TECHNOLOGY AND SCIENCE WITH EXAMPLES FROM ECOLOGY AND BIODIVERSITY

Early informatics focused primarily on the application of technology and computer science to a specific domain; modern informatics has broadened to encompass human and knowledge dimensions. Application of technology is but one aspect of informatics. Understanding domain members’ issues, priorities, knowledge, abilities, interactions, tasks and work environments is another aspect, and one that directly impacts application success. Involving domain members in the design and development of technology in their domain is a key factor in bridging the gap between technology and science. This user-centered design (UCD) approach in informatics is presented via an ecoinformatics case study in three areas: collaboration, usability, and education and training

Observatoire Scientifique en Appui à la GEstion du territoire (OSAGE) : entre espaces, temps, milieux, sociétés et informatique

L'article constitue une réflexion globale et conceptuelle autour de la notion d'observatoire scientifique en appui à la gestion du territoire. Il est le fruit d'une réflexion interdisciplinaire. Le terme observatoire recouvre de nombreuses acceptions et, à l'heure actuelle, de nombreuses réalisations existent sous diverses formes. Notre objectif est de tirer parti de la synergie entre scientifiques de divers domaines afin de prendre en compte la valeur ajoutée que constitue l'expertise scientifique pour clarifier la définition et les principes constitutifs fondamentaux de tels systèmes. Nous déclinons la vision de ce type d'observatoire au travers d’une approche conceptuelle. L'accent est mis sur le dispositif scientifique, et la déclinaison technique envisagée