4 research outputs found
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
Documenting models and workflows: the next challenge in the field of ecological data management
Los modelos ecológicos se han convertido en una pieza clave de esta ciencia. La generación de conocimiento se consigue en buena medida mediante procesos analíticos más o menos complejos aplicados sobre conjuntos de datos diversos. Pero buena parte del conocimiento necesario para diseñar e implementar esos modelos no está accesible a la comunidad científica. Proponemos la creación de herramientas informáticas para documentar, almacenar y ejecutar modelos ecológicos y flujos de trabajo. Estas herramientas (repositorios de modelos) están siendo desarrolladas por otras disciplinas como la biología molecular o las ciencias de la Tierra. Presentamos un repositorio de modelos (ModeleR) desarrollado en el contexto del Observatorio de seguimiento del cambio global de Sierra Nevada (Granada-Almería). Creemos que los repositorios de modelos fomentarán la cooperación entre científicos, mejorando la creación de conocimiento relevante que podría ser transferido a los tomadores de decisiones.Ecological models have become a key part of this scientific discipline. Most of the knowledge created by ecologists is obtained by applying analytical processes to primary data. But most of the information underlying how to create models or use analytic techniques already published in the scientific literature is not readily available to scientists. We are proposing the creation of computer tools that help to document, store and execute ecological models and scientific workflows. These tools (called model repositories) are being developed by other disciplines such as molecular biology and earth science. We are presenting a model repository (called ModeleR) that has been developed in the context of the Sierra Nevada Global Change Observatory (Granada-Almería. Spain). We believe that model repositories will foster cooperation among scientists, enhancing the creation of relevant knowledge that could be transferred to environmental managers.El desarrollo de ModeleR ha sido financiado por la Consejería de Medio Ambiente y Ordenación del Territorio de la Junta de Andalucía a través de la Red de Información Ambiental (REDIAM), gracias a un convenio llamado “Diseño y creación de un repositorio de modelos para la red de información ambiental de Andalucía”. A.J. Pérez-Luque agradece al MICINN por el contrato PTA 2011-6322-I
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Data-based, synthesis-driven: Setting the agenda for computational ecology
Computational thinking is the integration of algorithms, software, and data, tosolve general questions in a field. Computation ecology has the potential totransform the way ecologists think about the integration of data and models. Asthe practice is gaining prominence as a way to conduct ecological research, itis important to reflect on what its agenda could be, and how it fits within thebroader landscape of ecological research. In this contribution, we suggest areasin which empirical ecologists, modellers, and the emerging community ofcomputational ecologists could engage in a constructive dialogue to build on oneanother's expertise; specifically, about the need to make predictions frommodels actionable, about the best standards to represent ecological data, andabout the proper ways to credit data collection and data reuse. We discuss howtraining can be amended to improve computational literacy.TP thanks the Canadian Institute for Ecology and Evolution for financial support. BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP (NE/L002507/1)