A Semantic Scraping Model for Web Resources - Applying Linked Data to Web Page Screen Scraping

In spite of the increasing presence of Semantic Web Facilities, only a limited amount of the available resources in the Internet provide a semantic access. Recent initiatives such as the emerging Linked Data Web are providing semantic access to available data by porting existing resources to the semantic web using different technologies, such as database-semantic mapping and scraping. Nevertheless, existing scraping solutions are based on ad-hoc solutions complemented with graphical interfaces for speeding up the scraper development. This article proposes a generic framework for web scraping based on semantic technologies. This framework is structured in three levels: scraping services, semantic scraping model and syntactic scraping. The first level provides an interface to generic applications or intelligent agents for gathering information from the web at a high level. The second level defines a semantic RDF model of the scraping process, in order to provide a declarative approach to the scraping task. Finally, the third level provides an implementation of the RDF scraping model for specific technologies. The work has been validated in a scenario that illustrates its application to mashup technologies

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.

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.

Linguistic linked data for sentiment analysis

In this paper we describe the specification of amodel for the semantically interoperable representation of language resources for sentiment analysis. The model integrates "lemon", an RDF-based model for the specification of ontology-lexica (Buitelaar et al. 2009), which is used increasinglyfor the representation of language resources asLinked Data, with Marl, an RDF-based model for the representation of sentiment annotations (West-erski et al., 2011; Sánchez-Rada et al., 2013)

LDP4j: a framework for the development of interoperable read-write linked data applications

Enterprises are increasingly using a wide range of heterogeneous information systems for executing and governing their business activities. Even if the adoption of service orientation has improved loose coupling and reusability, applications are still isolated data silos whose integration requires complex transformations and mediations. However, by leveraging Linked Data principles those data silos can now be seamlessly integrated, and this opens the door to new data-driven approaches for Enterprise Application Integration (EAI). In this paper we present LDP4j, an open souce Java-based framework for the development of interoperable read-write Linked Data applications, based on the W3C Linked Data Platform (LDP) specification.

morph-LDP: an R2RML-based Linked Data Platform implementation

The W3C Linked Data Platform (LDP) candidate recom- mendation defines a standard HTTP-based protocol for read/write Linked Data. The W3C R2RML recommendation defines a language to map re- lational databases (RDBs) and RDF. This paper presents morph-LDP, a novel system that combines these two W3C standardization initiatives to expose relational data as read/write Linked Data for LDP-aware ap- plications, whilst allowing legacy applications to continue using their relational databases.

Onyx: A Linked Data approach to emotion representation

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.

A Provenance Aware Linked Data Application for Trip Management and Organization

We present El Viajero, an application for exploiting, managing and organizing Linked Data in the domain of news and blogs about travelling. El Viajero makes use of several heterogeneous datasets to help users to plan future trips, and relies on the Open Provenance Model for modeling the provenance information of the resources