EDI is a general purpose, template-driven metadata editor for creating XML-based descriptions. Originally aimed at defining rich and standard metadata for geospatial resources, It can be easily customised in order to comply with a broad range of schemata and domains. EDI creates HTML5 [9] metadata forms with advanced assisted editing capabilities and compiles them into XML files. The examples included in the distribution implement profiles of the ISO 19139 standard for geographic information [14], such as core INSPIRE metadata [10], as well as the OGC [8] standard for sensor description, SensorML [11]. Templates (the blueprints for a specific metadata format) drive form behaviour by element data types and provide advanced features like codelists 1 underlying combo boxes or autocompletion functionalities. Virtually, the editing of any metadata format can be supported by creating a specific template.
Abstract:Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify editing tools that can be easily tailored to the specificities of a given project, workgroup, and Community of Practice. Our solution is a template-driven metadata editing tool that can be customised to any XML-based schema. Its output is constituted by standards-compliant metadata records that also have a semantics-aware counterpart eliciting novel exploitation techniques. Moreover, external data sources can easily be plugged in to provide autocompletion functionalities on the basis of the data structures made available on the Web of Data. Beside presenting the essentials on customisation of the editor by means of two use cases, we extend the methodology to the whole life cycle of geospatial metadata. We demonstrate the novel capabilities enabled by RDF-based metadata representation with respect to traditional metadata management in the geospatial domain.
Delivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).-- 5 pages.Presentation (8 slides) available at http://prezi.com/6gmerli4l8ey/eurocris-2014-20140513-15/RITMARE is a Flagship Project by the Italian Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR) and coordinated by the National Research Council (CNR). It aims at the interdisciplinary integration of national marine research. In pursuing a Linked Open Data (LOD) vocation, the RITMARE sub-project 7 is building the necessary domain-related data structures by leveraging existing RDF-based schemata and sources. These data structures are grounding semantics-aware profiling of end users, data providers, and resources. The goal is designing a flexible infrastructure that adapts to the audience's specificities
The rapid growth and development in different fields related to sensors has, together with the huge increase of devices due to the decrease of device costs, led to a shift from traditional monitoring, where the data collected is not subject to any management actions, to sensor/processing networks, where in the life cycle more stages are devoted to make the data accessible. Data integration is the first step in advanced environmental monitoring, but assuring that heterogeneous systems can interoperate is still a challenge. The Sensor Web Enablement (SWE) initiative defines a framework to address this issue, offering a set of standard models and interfaces to improve sensor interoperability and to face quality issues in the reliability of sensors. The need for seamless access to observations from marine sensors has been the focus of several research projects. This chapter presents the actions taken in the development of the Spatial Data Infrastructure for project RITMARE to ease the adoption of SWE within the Italian marine community overcoming the main constraints in SWE adoption.
We present a novel approach to the management of Spatial Data Infrastrutures that leverages semantics-aware context information to model the distinct aspects involved in the management of geospatial data. RDF-based schemata are employed for encoding information about the user community, the terminologies in use in a specific research domain, gazetteer information representing the physical landscape underpinning data and, last but not least, resource metadata. The data structures are then interconnected to enable seamless exploitation for metadata creation and resource discovery, which we demonstrate through a worked-out example of SPARQL query on RDF graph data. The methodology is being applied by the National Research Council of Italy (CNR) to support creation of a distributed infrastructure for marine data in the context of the RITMARE Flagship Project.
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