SSONDE: Semantic Similarity On liNked Data Entities

Linked data offers a promising setting to encode, publish and share metadata of resources. As the matter of fact, it is already adopted by data producers such as European Environment Agency, US and some EU Governs, whose first ambition is to share (meta)data making their processes more effective and transparent. Such as an increasing interest and involvement of data providers surely represents a genuine witness of the web of data success, but in a longer perspective, frameworks supporting linked data consumers in their decision making processes will be a compelling need. In this respect, the talk is introducing SSONDE, a framework enabling in detailed comparison, ranking and selection of linked data resources through the analysis of their RDF ontology driven metadata. SSONDE implements an instance similarity especially designed to support in resource selection, namely the process stakeholders engage to choose a set of resources suitable for a given analysis purpose: (i) it deploys an asymmetric similarity assessment to emphasize information about gains and losses the stakeholders get adopting a resource in place of another; (ii) it relies on an explicit formalization of contexts to tailor the similarity assessment with respect to specific user-defined selection goals. The talk aims at providing an insight on SSONDE instance similarity and it will briefly describe some examples of SSONDE deployment in the context of linked data consumption.

Transforming meteorological data into linked data

This paper describes the process followed in order to make some of the public meterological data from the Agencia Estatal de Meteorología (AEMET, Spanish Meteorological Office) available as Linked Data. The method followed has been already used to publish geographical, statistical, and leisure data. The data selected for publication are generated every ten minutes by the 250 automatic stations that belong to AEMET and that are deployed across Spain. These data are available as spreadsheets in the AEMET data catalog, and contain more than twenty types of measurements per station. Spreadsheets are retrieved from the website, processed with Python scripts, transformed to RDF according to an ontology network about meteorology that reuses the W3C SSN Ontology, published in a triple store and visualized in maps with Map4rdf.

Augmenting PROV with Plans in P-PLAN: Scientific Processes as Linked Data

Provenance models are crucial for describing experimental results in science. The W3C Provenance Working Group has recently released the PROV family of specifications for provenance on the Web. While provenance focuses on what is executed, it is important in science to publish the general methods that describe scientific processes at a more abstract and general level. In this paper, we propose P-PLAN, an extension of PROV to represent plans that guid-ed the execution and their correspondence to provenance records that describe the execution itself. We motivate and discuss the use of P-PLAN and PROV to publish scientific workflows as Linked Data.

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

Multilingual Variation in the context of Linked Data

In this paper we present a revisited classification of term variation in the light of the Linked Data initiative. Linked Data refers to a set of best practices for publishing and connecting structured data on the Web with the idea of transforming it into a global graph. One of the crucial steps of this initiative is the linking step, in which datasets in one or more languages need to be linked or connected with one another. We claim that the linking process would be facilitated if datasets are enriched with lexical and terminological information. Being that the final aim, we propose a classification of lexical, terminological and semantic variants that will become part of a model of linguistic descriptions that is currently being proposed within the framework of the W3C Ontology-Lexica Community Group to enrich ontologies and Linked Data vocabularies. Examples of modeling solutions of the different types of variants are also provided.

Rights declaration in Linked Data

Linked Data is not always published with a license. Sometimes a wrong license type is used, like a license for software, or it is not expressed in a standard, machine readable manner. Yet, Linked Data resources may be subject to intellectual property and database laws, may contain personal data subject to privacy restrictions or may even contain important trade secrets. The proper declaration of which rights are held, waived or licensed is a must for the lawful use of Linked Data at its different granularity levels, from the simple RDF statement to a dataset or a mapping. After comparing the current practice with the actual needs, six research questions are posed.

Combinando Linked Data con servicios geoespaciales

La Web de Linked Data supone un nuevo paradigma que pretende explotar la Web como un espacio global de información. La aplicación de los principios de esta nueva Web a la información geoespacial superará la integración de información tradicional, logrando una articulación semántica de los datos que haga desaparecer los silos de datos presentes en las actuales Infraestructuras de Datos Espaciales. Ante esta propuesta, en este artículo se describe el trabajo desarrollado en el marco de un caso de uso utilizando una parte de los datos del SIGNA. En este caso de uso se ha llevado a cabo un proceso de generación y publicación de los mencionados datos conforme a los principios de Linked Data y estos se combinan con diversos servicios de la IDEE y CartoCiudad para explotar el componente geoespacial.

A Coreference Service for Enterprise Application Integration using Linked Data

The use of semantic and Linked Data technologies for Enterprise Application Integration (EAI) is increasing in recent years. Linked Data and Semantic Web technologies such as the Resource Description Framework (RDF) data model provide several key advantages over the current de-facto Web Service and XML based integration approaches. The flexibility provided by representing the data in a more versatile RDF model using ontologies enables avoiding complex schema transformations and makes data more accessible using Web standards, preventing the formation of data silos. These three benefits represent an edge for Linked Data-based EAI. However, work still has to be performed so that these technologies can cope with the particularities of the EAI scenarios in different terms, such as data control, ownership, consistency, or accuracy. The first part of the paper provides an introduction to Enterprise Application Integration using Linked Data and the requirements imposed by EAI to Linked Data technologies focusing on one of the problems that arise in this scenario, the coreference problem, and presents a coreference service that supports the use of Linked Data in EAI systems. The proposed solution introduces the use of a context that aggregates a set of related identities and mappings from the identities to different resources that reside in distinct applications and provide different views or aspects of the same entity. A detailed architecture of the Coreference Service is presented explaining how it can be used to manage the contexts, identities, resources, and applications which they relate to. The paper shows how the proposed service can be utilized in an EAI scenario using an example involving a dashboard that integrates data from different systems and the proposed workflow for registering and resolving identities. As most enterprise applications are driven by business processes and involve legacy data, the proposed approach can be easily incorporated into enterprise applications.

datos.bne.es and MARiMbA: an insight into Library Linked Data

Purpose – Linked data is gaining great interest in the cultural heritage domain as a new way for publishing, sharing and consuming data. The paper aims to provide a detailed method and MARiMbA a tool for publishing linked data out of library catalogues in the MARC 21 format, along with their application to the catalogue of the National Library of Spain in the datos.bne.es project. Design/methodology/approach – First, the background of the case study is introduced. Second, the method and process of its application are described. Third, each of the activities and tasks are defined and a discussion of their application to the case study is provided. Findings – The paper shows that the FRBR model can be applied to MARC 21 records following linked data best practices, librarians can successfully participate in the process of linked data generation following a systematic method, and data sources quality can be improved as a result of the process. Originality/value – The paper proposes a detailed method for publishing and linking linked data from MARC 21 records, provides practical examples, and discusses the main issues found in the application to a real case. Also, it proposes the integration of a data curation activity and the participation of librarians in the linked data generation process.

Multilingual variation in the context of Linked Data

In this paper we present a revisited classification of term variation in the light of the Linked Data initiative. Linked Data refers to a set of best practices for publishing and connecting structured data on the Web with the idea of transforming it into a global graph. One of the crucial steps of this initiative is the linking step, in which datasets in one or more languages need to be linked or connected with one another. We claim that the linking process would be facilitated if datasets are enriched with lexical and terminological information. Being that the final aim, we propose a classification of lexical, terminological and semantic variants that will become part of a model of linguistic descriptions that is currently being proposed within the framework of the W3C Ontology- Lexica Community Group to enrich ontologies and Linked Data vocabularies. Examples of modeling solutions of the different types of variants are also provided.