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Essential Biodiversity Variables (EBVs) and Biological and Ecosystem Essential Ocean Variables (BioEco EOVs) are two cooperative conceptual frameworks which help harmonize and process multi-source marine biodiversity observations into robust indexes, in order to measure progress toward policy conservation goals. Long-term monitoring networks are encouraged to contribute to these frameworks by mobilizing historical times series which are suitable for detecting impacts of management policies. In this paper, we identify specific recommendations for increasing reuse in the EV frameworks of the biodiversity historical data collected and maintained by the Gulf of Venice (GOV) site, i.e., the monitoring facility that is selected as case study in the Italian Long-Term Ecological Research network (LTER-Italy). The recommendations are obtained through a practical approach comprising two phases. In the first phase, a literature review helps extract the guidelines for implementing the principles representing the most recent attempt to unify management of EBV and BioEco EOV data, i.e., Benson’s tenets. In the second phase, we compare the guidelines to the data management practices enacted by the selected monitoring site in order to recommend curation interventions. The outputs of the analysis are discussed in order to verify if the approach and the recommendations are general enough to be replicated in the marine component of monitoring networks to coordinate the LTER data contribution to the EV frameworks.

Metadata descriptions are typically monolithic data structures and their denormalized, text-based nature yields shortcomings such as inconsistencies and heterogeneities. Moreover, fluidity of research environments, coupled with single-tenancy of metadata descriptions, impedes enforcing authority on the related datasets effectively. We propose a novel paradigm for metadata articulation, delegation, that helps solve the aforementioned issues. After elaborating on the requirements to this practice, we present two worked-out implementation examples in the domain of geospatial metadata and discuss its advantages with respect to key issues in this domain; namely, metadata consistency, interoperability, and mitigating semantic heterogeneity. The technique and the supporting software we present are equally applicable to any XML-based metadata schema and application domain.

Precision Agriculture (PA) takes advantage of digital technologies to improve agricultural production and its economic and environmental sustainability. The main issues in the implementation and spread of PA include (a) harmonization and (b) interpretation of heterogeneous data collected from different sources; (c) interoperability of systems and data; (d) implementation of new algorithms and methodologies coming from research projects; (e) semantic enablement of meta-data. To help solve these issues we propose a software infrastructure prototype developed in the framework of the SATFARMING project, and based on Service Oriented Architecture (SOA) concept, free open-source software (FOSS), interoperability of data and web services through the accomplishment of international standards, semantic enablement of data description.

The sharing of research data allows for information reuse and knowledge advancement but its realization is often a challenge and seldom successful in practice. We propose a workflow for the design of a User Support System (USS) aimed at tutoring research groups in data sharing by considering their social and domain backgrounds. Our engagement approach focuses on multidisciplinary geospatial research, particularly when interoperable data sharing is required. Specifically, we first characterize the research community on the basis of the behavior and competences in data management by its groups and then target the needs of the latter with specific facilities. We address for the first time in literature the issue of modeling research groups as targets of the USS and provide a roadmap to standardize USS activities across different communities. We describe the implementation of the workflow in the context of an Italian research project and we assess the impact of the USS in terms of increase in the number of nodes and resources in the project’s data infrastructure, and of fulfilment of the expectations by the research groups.

Geospatial metadata are often encoded in formats that either are not aimed at efficient retrieval of resources or are plainly outdated. Particularly, the quantum leap represented by the Semantic Web did not induce so far a consistent, interlinked baseline in the geospatial domain. Datasets, scientific literature related to them, and ultimately the researchers behind these products are only loosely connected, the corresponding metadata intelligible only to humans, duplicated in different systems, seldom consistently. We address these issues by relating metadata items to resources that represent keywords, institutes, researchers, toponyms, and virtually any RDF data structure made available over the Web via SPARQL endpoints. Essentially, our methodology fosters delegated metadata management as the entities referred to in metadata are independent, decentralized data structures with their own life cycle. Our example implementation of delegated metadata envisages: (i) editing via customizable web-based forms (including injection of semantic information), (ii) encoding of records in any XML metadata schema, and (iii) translation into RDF. Among the semantics-aware features that this practice enables, we present a worked-out example focusing on automatic update of metadata descriptions. Our approach, demonstrated in the context of INSPIRE metadata (the ISO 19115/19119 profile eliciting integration of European geospatial resources) is also applicable to a broad range of metadata standards, including non-geospatial ones.

The chapter investigates the kinds of imperfection affecting Volunteer Geographic Information (VGI) created by users eager to participate in some citizen science project. An approach based on the use of fuzzy domain ontologies and level-based approximate reasoning is suggested to represent and manage both the uncertainty of volunteers when describing their observations and the vagueness of ill-defined domain knowledge. This way one can model more reliable smart applications for creating VGI as well as can design less ambiguous spatial data infrastructures (SDIs) for sharing VGI with final stakeholders.

Traditionally, maps and data were analyzed and created by desktop software tools. Today, thanks to World Wide Web, open source software tools and international standards, practitioners and researchers can share maps, data, and measures. Sharing can be done with different software tools, proprietary or open source, and with varying degrees of interoperability. Most geological maps and data collected by instruments are produced by governmental organizations and they are encoded in official languages and data schemas of their producers. Linguistic barrier, different visual representations and data schemas hinder the usefulness of online maps and data, obtained from different sources. In the present paper, we report a research aiming to overcome these aforementioned barriers. To this end, after having described their main characteristics, we exploited and summarized the main findings of using geoscience thesauri, international standards for web sharing, visual and data harmonization. We used GeoScience Markup Language (GeoSciML-Portayal) to harmonize geological maps collected in the context of a multidisciplinary study focused on a coastal area located in Southern Italy, (Costa Viola); Sensor Metadata Language (SensorML) to describe geological instruments; Observations and Measurements (O&M) to harmonize geological data collected by instruments. We used geoscience thesauri based on Simple Knowledge Organization System (SKOS) to enrich semantically the aforementioned geological maps, data and instruments. A distributed Spatial Data Infrastructure (SDI), implemented using free and open source software for geospatial (FOSS4G), was provided taking advantage on Open Geospatial Consortium (OGC) standards to share data and information in an interoperable, harmonized and semantically enriched way.

In the last few decades, functional trait-based approaches have undergone an extraordinary expansion in phytoplankton ecology, due to the relative simplicity and the well-defined traits that determine the ecological niche of these organisms. A large quantity of heterogeneous and distributed data has been produced on phytoplankton traits and their use could be made more effective and efficient if data harmonization and interoperability would be improved. The use of controlled vocabularies and thesauri is an acknowledged good practice to establish the foundation for semantic interoperability, a critical requirement for reuse and sharing of data. In fact, thesauri, collectively constructed, bypass ambiguity issues in natural language, facilitating the identification and integration of the information available in multiple data sources and allowing both scientists and computer applications to interpret more effectively the meaning of data. Here we present a semantic resource on phytoplankton functional traits: the PhytoTraits thesaurus ( http://thesauri.lifewatchitaly.eu/PhytoTraits/index.php ). PhytoTraits is the result of the interdisciplinary collaboration of experts both from the phytoplankton functional domain and from information and communication technologies, working together within LifeWatch Italy, the Italian node of the e-science European infrastructure for biodiversity and ecosystem research. PhytoTraits is the first initiative to deal with the semantics of phytoplankton functional traits, focusing on morpho-functional traits towards standardized bio-volume assessment. It reflects the agreement of a scientific expert community to fix semantic properties (e.g. label, definition) of approximately 120 traits. Following semantic web standard technologies, the thesaurus was implemented in Simple Knowledge Organization System (SKOS), a common data model based on the Resource Description Framework (RDF). PhytoTraits is freely available online, it can be queried through a SPARQL endpoint ( http://thesauri.lifewatchitaly.eu/PhytoTraits/sparql.php ) and is also accessible via API ( http://thesauri.lifewatchitaly.eu/PhytoTraits/services.php ) for integration with other systems. If adopted as a standard and rigorously applied and enriched by the scientific community, PhytoTraits, providing harmonized concepts with associated unique and resolvable URIs, has the potential to significantly reduce the barriers to data discovery, integration, and exchange.

RITMARE is a Flagship Project by the Italian Ministero dell'Istruzione, dell'Universita 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. © 2014 Published by Elsevier B.V.

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.

Water quality is a multi-source, multi-purpose problem that needs exploiting observations, often taken by a number of heterogeneous bodies. This problem has been tackled within the Italian Long Term Ecological research network (LTER-Italy) in an experiment aimed at testing how ecological observations of mountain lakes water can be shared by OGC (Open Geospatial Consortium) standard services of the Sensor Web Enablement (SWE) initiative. A friendly and easy implementation of these services is fostered by the usage of the open source software Geoinformation Enabling Toolkit StarterKit ® (GET-IT). It has been used in the experiment to create SOS services, upload observations and create SensorML metadata of the involved sensors. This contribution describes the experiment and presents its results.

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.

While spatial information quality is an established discipline in traditional scientific geographical information (GI), standards and protocols for representing and assessing the quality of geographic contributions generated by volunteers or by the generic ‘web crowd’ are still missing. This work offers an analysis of strategies for quality control and describes a simple representation of the components of the quality in crowdsourced GI. In this framework, and based on the research carried out in Criscuolo et al. (2014), we also introduce a methodology for quality assessment, based on the given representation, which goes beyond the limitations of previous methods in the literature defined for a specific purpose, being able to deal with many quality features, GI categories, and types of application. The method is designed as a decision making approach, so flexible as to take into account the purpose of GI analysis, and so transparent as to make explicit the criteria driving to quality evaluation, namely the quality features (e.g. the credibility of the volunteers, or the accuracy of the spatial features, etc.) and their relevance.

The need for continuous, accurate, and comprehensive environmental knowledge has led to an increase in sensor observation systems and networks. The Sensor Web Enablement (SWE) initiative has been promoted by the Open Geospatial Consortium (OGC) to foster interoperability among sensor systems. The provision of metadata according to the prescribed SensorML schema is a key component for achieving this and nevertheless availability of correct and exhaustive metadata cannot be taken for granted. On the one hand, it is awkward for users to provide sensor metadata because of the lack in user-oriented, dedicated tools. On the other, the specification of invariant information for a given sensor category or model (e.g., observed properties and units of measurement, manufacturer information, etc.), can be labor- and timeconsuming. Moreover, the provision of these details is error prone and subjective, i.e., may differ greatly across distinct descriptions for the same system. We provide a user-friendly, template-driven metadata authoring tool composed of a backend web service and an HTML5/javascript client. This results in a form-based user interface that conceals the high complexity of the underlying format. This tool also allows for plugging in external data sources providing authoritative definitions for the aforementioned invariant information. Leveraging these functionalities, we compiled a set of SensorML profiles, that is, sensor metadata blueprints allowing end users to focus only on the metadata items that are related to their specific deployment. The natural extension of this scenario is the involvement of end users and sensor manufacturers in the crowd-sourced evolution of this collection of prototypes. We describe the components and workflow of our framework for computer-aided management of sensor metadata.

In the geospatial realm, data annotation and discovery rely on a number of ad-hoc formats and protocols. These have been created to enable domain-specific use cases generalized search is not feasible for. Metadata are at the heart of the discovery process and nevertheless they are often neglected or encoded in formats that either are not aimed at efficient retrieval of resources or are plainly outdated. Particularly, the quantum leap represented by the Linked Open Data (LOD) movement did not induce so far a consistent, interlinked baseline in the geospatial domain. In a nutshell, datasets, scientific literature related to them, and ultimately the researchers behind these products are only loosely connected; the corresponding metadata intelligible only to humans, duplicated on different systems, seldom consistently. Instead, our workflow for metadata management envisages i) editing via customizable web- based forms, ii) encoding of records in any XML application profile, iii) translation into RDF (involving the semantic lift of metadata records), and finally iv) storage of the metadata as RDF and back-translation into the original XML format with added semantics-aware features. Phase iii) hinges on relating resource metadata to RDF data structures that represent keywords from code lists and controlled vocabularies, toponyms, researchers, institutes, and virtually any description one can retrieve (or directly publish) in the LOD Cloud. In the context of a distributed Spatial Data Infrastructure (SDI) built on free and open-source software, we detail phases iii) and iv) of our workflow for the semantics-aware management of geospatial metadata.

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 codelists1 underlying combo boxes or autocompletion functionalities. Virtually, the editing of any metadata format can be supported by creating a specific template. EDI is stored on GitHub at https://github.com/SP7-Ritmare/EDI-NG_client and https://github.com/SP7-Ritmare/EDI-NG_server.

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 spatial data. RDF-based schemata are employed for encoding information on the user community, the terminologies in use in a specific research domain, gazetteer information representing the physical landscape hosting data and, last but not least, spatial 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 by the National Research Council (CNR) of Italy to support creation of a distributed infrastructure for marine data in the context of the RITMARE Flagship Project.