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The use of social network theory and methods of analysis have been applied to different domains in recent years, including public health. The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes. This research presents a multi-domain knowledge model capable of automatically gathering data and carrying out different social network analyses in different domains, without errors and obtaining the same conclusions that an expert in SNA would obtain. The model is represented in an ontology called OntoSNAQA, which is made up of classes, properties and rules representing the domains of People, Questionnaires and Social Network Analysis. Besides the ontology itself, different rules are represented by SWRL and SPARQL queries. A Knowledge Based System was created using OntoSNAQA and applied to a real case study in order to show the advantages of the approach. Finally, the results of an SNA analysis obtained through the model were compared to those obtained from some of the most widely used SNA applications: UCINET, Pajek, Cytoscape and Gephi, to test and confirm the validity of the model.

In this paper, we propose an architecture that combines Big Data and Stream Processing which can be applied to the Real Estate Domain. Our approach consists of a specialisation of Lambda architectu...

Diet is one of the main sources of exposure to toxic chemicals with carcinogenic potential, some of which are generated during food processing, depending on the type of food (primarily meat, fish, bread and potatoes), cooking methods and temperature. Although demonstrated in animal models at high doses, an unequivocal link between dietary exposure to these compounds with disease has not been proven in humans. A major difficulty in assessing the actual intake of these toxic compounds is the lack of standardised and harmonised protocols for collecting and analysing dietary information. The intestinal microbiota (IM) has a great influence on health and is altered in some diseases such as colorectal cancer (CRC). Diet influences the composition and activity of the IM, and the net exposure to genotoxicity of potential dietary carcinogens in the gut depends on the interaction among these compounds, IM and diet. This review analyses critically the difficulties and challenges in the study of interactions among these three actors on the onset of CRC. Machine Learning (ML) of data obtained in subclinical and precancerous stages would help to establish risk thresholds for the intake of toxic compounds generated during food processing as related to diet and IM profiles, whereas Semantic Web could improve data accessibility and usability from different studies, as well as helping to elucidate novel interactions among those chemicals, IM and diet., This work is receiving support from the project RTI2018-098288-B-I00 (MCIU/AEI/FEDER, UE) and is based on concepts developed partly funded by projects TIN2017-88877-R (AEI/FEDER, UE), TIN2017-87600-P (AEI/FEDER. UE) and IDI/2018/000176 (Asturian Government GRUPIN projects). SRS is the beneficiary of a training contract financed by project RTI2018-098288-B-I00. SA is granted by a Juan de la Cierva postdoctoral contract from the Spanish Ministry of Science and Innovation (Ref. IJCI-2017-32156) and NS is the recipient of a postdoctoral contract awarded by the Fundación para la Investigación y la Innovación Biosanitaria del Principado de Asturias (FINBA).

In this paper, the authors describe Musical Entities Reconciliation Architecture (MERA), an architecture designed to link music-related databases adapting the reconciliation techniques to each particular case. MERA includes mechanisms to manage third party sources to improve the results and it makes use of semantic technologies, storing and organizing the information in RDF graphs. They have implemented a prototype of their approach and have used it to link sources with different levels of data quality. The prototype has been effective in more than 94% of the cases under the conditions of their experiments. The authors have also compared their prototype with a well-known music-specialized search engine, outperforming the search results in the two experiments that they performed.

Integration of heterogeneous data sources in a single representation is an active field with many different tools and techniques. In the case of text-based approaches—those that base the definition of the mappings and the integration on a DSL—there is a lack of usability studies. In this work we have conducted a usability experiment (n = 17) on three different languages: ShExML (our own language), YARRRML and SPARQL-Generate. Results show that ShExML users tend to perform better than those of YARRRML and SPARQL-Generate. This study sheds light on usability aspects of these languages design and remarks some aspects of improvement.

AppWesomed is a website developed to test the suggestion of SNOMED CT terms in medical reports. When the user is writing the report, the web shows the terms that match the last written word. The use of SNOMED CT in medical applications is important because it can facilitate the integration of medical records. The tests were conducted with twenty-five people, divided into two groups, fifteen doctors and eleven non-doctors. The average age of the groups was 45 years and 32 years, respectively. A survey designed according to the Likert scale was used to test the website usability, the results of the survey were used to calculate the Cronbach's Alpha whose value was 0.894. According to the results, 44% of the participants considered the website usability as "Good", 36% as "Excellent" and 20% as "Regular". The app has been positively evaluated by the surveyed doctors. In response to the general experience, doctors highlight the great application utility, especially in their own research studies for the data analysis in medical reports.

We formalize the eGovernment transactions domain to reuse it in other contexts.We construct a knowledge base that encloses transactions domain requirements.We provide a mechanism to model and validate procedures aided by automated rules.We surveyed experts and the 61% of them strongly agree with our approach.Both consulted profiles gave marks with a mode of 4 in a 5 scale. Public administrations pursue the efficiency and quality of administrative services they offer as well as the reduction of time and operational costs in executing service transactions. However, some issues arise when trying to achieve these goals: (a) the lack of procedure formalization to describe public services, (b) a mechanism to guarantee services' obligatory compliance with frequently changing legal regulations, and (c) the efficient deployment of service transactions in e-government platforms. The aim of this work is to identify the phases of the development cycle of eGovernment transactions and provide the support to automatize them efficiently by using a model driven engineering (MDE) and knowledge-based approach. The main source of the knowledge extraction process comes from a collaborative learning environment where public servants share acquired domain knowledge. A web survey has been conducted to evaluate the approach acceptance degree by software developers and domain experts. The main conclusion is that 61% of the surveyed experts strongly agree that our approach improves actual eGovernment transactions practices and the phases needed to develop them.

The increasing publication of linked data makes the vision of the semantic web a probable reality. Although it may seem that the web of data is inherently multilingual, data usually contain labels, comments, descriptions, etc. that depend on the natural language used. When linked data appears in a multilingual setting, it is a challenge to publish and consume it. This paper presents a survey of patterns to publish Multilingual Linked Data and identifies some issues that should be taken into account. As a use case, the paper describes the patterns employed in the DBpedia Internationalization project.

Over the past few years, Public Administrations have been providing systems for procedures and files electronic processing to ensure compliance with regulations and provide public services to citizens. Although each administration provides similar services to their citizens, these systems usually differ from the internal information management point of view since they usually come from different products and manufacturers. The common framework that regulations demand, and that Public Administrations must respect when processing electronic files, provides a unique opportunity for the development of intelligent agents in the field of administrative processes. However, for this development to be truly effective and applicable to the public sector, it is necessary to have a common representation model for these administrative processes. Although a lot of work has already been done in the development of public information reuse initiatives and common vocabularies standardization, this has not been carried out at the processes level. In this paper, we propose a semantic representation model of both processes models and processes for Public Administrations: the procedures and administrative files. The goal is to improve public administration open data initiatives and help to develop their sustainability policies, such as improving decision-making procedures and administrative management sustainability. As a case study, we modelled public administrative processes and files in collaboration with a Regional Public Administration in Spain, the Principality of Asturias, which enabled access to its information systems, helping the evaluation of our approach.

The present paper introduces and reviews existing technology and research works in the field of e-Procurement. More specifically this survey aims to collect those relevant approaches that have tackled the challenge of delivering more advanced and intelligent e-Procurement management systems due to its relevance in the industry to afford more timely, adaptable and flexible decisions in purchasing processes. Although existing tools and techniques have demonstrated their ability to manage e-Procurement processes as a part of a supply management system there is a lack of interoperability among tools, tangled dependencies between processes or difficulties to exploit existing data and information to name a few that are preventing a proper use of the new dynamic and data-based environment. On the other hand semantic-based technologies emerge to provide the adequate building blocks to represent domain-knowledge and elevate the meaning of information resources through a common and shared data model (RDF) with a formal query language (SPARQL) and accessible via the Internet Protocols. In this sense the Linked Data effort has gained momentum to apply the principles of the aforementioned initiative to boost the re-use of information and data across different tools and processes. That is why authors review both existing open issues in the context e-Procurement with special focus on public procurement and semantic-based approaches to address them. To do so a preliminary research study is conducted to assess the state of the art in the context of e-Procurement and semantic-based systems. Afterwards main drawbacks of existing e-Procurement systems are presented to narrow down in semantic-based approaches applied to this field. Once the current status in both areas is reviewed, authors purpose the use and creation of an e-Procurement index to evaluate the quality of service of procurement systems. In this light the Analytical Hierarchy Process (AHP) method is used to set up an initial weight for each indicator in the index and to perform a first comparison between traditional and semantic-based approaches. Finally some discussion, conclusions and future challenges are also outlined.

The present paper introduces a method to promote existing controlled vocabularies to the Linked Data initiative. A common data model and an enclosed conversion method for knowledge organization systems based on semantic web technologies and vocabularies such as SKOS are presented. This method is applied to well-known taxonomies and controlled vocabularies in the business sector, more specifically to Product Scheme Classifications created by governmental institutions such as the European Union or the United Nations. Since these product schemes are available in a common and shared data model, the needs of the European e-Procurement sector are outlined to finally demonstrate how Linked Data can address some of the challenges for publishing and retrieving information resources. As a consequence, two experiments are also provided in order to validate the gain, in terms of expressivity, and the exploitation of this emerging approach to help both expert and end-users to make decisions on the selection of descriptors for public procurement notices.

This work has been funded by a collaboration with the Izertis company funded by the Ministerio de Industria, Energia y Turismo in the call of Accion Estrategica de Economia y Sociedad Digital del 2014. (TSI-100600-2014-44) Title: Linked Open Data Learning (LOP): Enriqueciendo la experiencia formativa en eLearning; the Department of Science and Innovation (Spain) under the National Program for Research, Development and Innovation: project EDU2014-57571-P; the European Union, through the European Regional Development Funds (ERDF); and the Principality of Asturias, through its Science, Technology and Innovation Plan (grant GRUPIN14-100). The authors also want to thank the State High School teachers: Modesto and Maria Jose, as well as their students for their willingness and collaboration with the experiment described in this work.

Chilecompra is the Chilean governmental agency in charge of Chile's Public Procurement System. One of its main current problems is that around 54% (supply indicator) of the public procurements that are submitted get less than three bids, which is the minimum required so that the procurement process may be free of technical, legal and ethical questionings. This article presents a method based on Natural Language Processing and Semantic Analysis in order to automatically identify prospective bidding candidates from a historical application dataset with a software tool which implements this method. The results are proven by using a dataset of procurement data and historical applications, biddings and adjudications of the suppliers. We compared the number of suppliers that applied for a tender and the number of prospective bidders identified by this method, and the domain procurement experts proved that the identified bidders were relevant to the new procurement.

The emerging Web of Data as part of the Semantic Web initiative and the sheer mass of information now available make it possible the deployment of new services and applications based on the reuse of existing vocabularies and datasets. A huge amount of this information is published by governments and organizations using semantic web languages and formats such as RDF, implicit graph structures developed using W3C standard languages: RDF-Schema or OWL, but new flexible programming models to process and exploit this data are required. In that sense the use of algorithms such as Spreading Activation is growing in order to find relevant and related information in this new data realm. Nevertheless the efficient exploration of the large knowledge bases has not yet been resolved and that is why new paradigms are emerging to boost the definitive deployment of the Web of Data. This cornerstone is being addressed applying new programming models such as MapReduce in combination with old-fashioned techniques of Document and Information Retrieval. In this paper an implementation of the Spreading Activation technique based on the MapReduce programming model and the problems of applying this paradigm to graph-based structures are introduced. Finally, a concrete experiment with real data is presented to illustrate the algorithm performance and scalability.

Automated medical diagnosis systems based on knowledge-oriented descriptions have gained momentum with the emergence of semantic descriptions. The objective of this paper is to propose a normalized design that solves some of the problems which have been detected by authors in previous tools. The authors bring together two different technologies to develop a new clinical decision support system: description logics aimed at developing inference systems to improve decision support for the prevention, treatment and management of illness and semantic technologies. Because of its new design, the system is capable of obtaining improved diagnostics compared with previous efforts. However, this evaluation is more focused in the computational performance, giving as result that description logics is a good solution with small data sets. In this paper, we provide a well-structured ontology for automated diagnosis in the medical field and a three-fold formalization based on Description Logics with the use of Semantic Web technologies This work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the project TRAZAMED (IPT 090000 2010 007). Publicado

The present editorial note introduces the concept of e-Procurement and the use of semantic technologies to improve some of the processes involved in electronic purchasing processes. Currently there is a growing interest to boost the use of electronic communications to deal with Business-to-Business (B2B), Business-to-Consumer (B2C) or Administration-to-Administration (A2A) relationships. New technologies are emerging with the aim of: (1) reducing costs; (2) providing more intelligent environments to make decisions in more timely and accurate fashion and (3) improving the overall efficiency of business processes. More specifically, e-Procurement defined as the business to business purchase and sale of supplies over the Internet can be found in a variety of ways from public marketplaces involving many firms to private exchanges that are currently facing a challenging environment to migrate from paper-based systems to an electronic ecosystem. However several interlinked challenges to achieve a successful transition have been identified such as lack of interoperable and standard-based infrastructures (data and services), legal uncertainties including the necessity of improving trust, privacy and provenance of data and information and lack of transparency, accessibility or usability to name a few. In this context semantic-based technologies arise to afford a common and standard data model that eases the interoperability, integration and creation of knowledge-based systems. Taking into account the necessity of a more interoperable and intelligent system to manage e-Procurement processes and the emerging application of semantics in different domains, this special issue is intended to provide researchers, developers and practitioners a summary of the current status of e-Procurement applying semantics.

The publication of different media types, like images, audio and video in the World Wide Web is getting more importance each day. However, searching and locating content in multimedia sites is challenging. In this paper, we propose a platform for the development of multimedia web information systems. Our approach is based on the combination between semantic web technologies and collaborative tagging. Producers can add meta-data to multimedia content associating it with different domain-specific ontologies. At the same time, users can tag the content in a collaborative way. The proposed system uses a search engine that combines both kinds of meta-data to locate the desired content. It will also provide browsing capabilities through the ontology concepts and the developed tags.

Nowadays there is a growing need of ubiquity for learning, research and development tools, due to the portability and availability problems concerning traditional desktop applications. In this paper, we suggest an approach to avoid any further download or installation. The main goal is to offer a collaborative and extensible web environment which will cover a series of domains highly demanded by different kinds of working groups, in which it is crucial to have tools which facilitate the exchange of information and the collaboration among their members. The result of those interactions would be the development of one or several diagrams accessible from any geographical location, independently of the device employed. The environment can be adapted through personalized components, depending on the type of diagram that the user wants to interact with and the users can also create new elements or search and share components with other users of the community. By means of this environment, it will be possible to do research on the usability of collaborative tools for design diagrams, as well as research on the psychology of group interactions, assessing the results coming from the employment of known methodologies, techniques, paradigms or patterns, both at an individual and at a collaborative group level.

Program slicing is an important decomposition technique. It has been widely used in many software activities, such as software analyzing, understanding, debugging, testing, and maintenance. The current slicing methods and tools, however, are monolithic, and mainly based on program or system dependence graph. This paper presents a novel formal tool for program slicing. It abstracts the computation of program slicing as a language-independent slice monad transformer, which can be applied to the semantic descriptions of the program in a modular way, forming the corresponding slicing algorithms. Such algorithms allow program slices to be computed directly on abstract syntax, with no need to explicitly construct intermediate structures such as dependence graphs or to record an execution history. It has reusability and language-flexibility properties in comparison with the current program slicing methods/tools.

This chapter introduces the promotion of statistical data to the Linked Open Data initiative in the context of the Web Index project. A framework for the publication of raw statistics and a method to convert them to Linked Data are also presented following the W3C standards RDF, SKOS, and OWL. This case study is focused on the Web Index project; launched by the Web Foundation, the Index is the first multi-dimensional measure of the growth, utility, and impact of the Web on people and nations. Finally, an evaluation of the advantages of using Linked Data to publish statistics is also presented in conjunction with a discussion and future steps sections.

The massive use of Internet and social networks leads us to a new dynamic environment with huge amounts of unstructured and unclassified information resources in continuous evolution. New classification, compilation, and recommendation systems based on the use of folksonomies and ontologies have appeared to deal with the requirements of data management in this environment. Nevertheless, using ontologies alone has some weaknesses due to the need of being statically modeled by a set of experts in a specific domain. On the other hand, folksonomies show a lack of formality because of their implicit ambiguity and flexibility by definition. The main objective of this chapter is to outline and evaluate a new way to exploit Web information resources and tags for bridging the gap between ontology modeling and folksonomies.

The aim of this chapter is to present a proposal and a case study to describe the information about organizations in a standard way using the Linked Data approach. Several models and ontologies have been provided in order to formalize the data, structure and behaviour of organizations. Nevertheless, these tries have not been fully accepted due to some factors: (1) missing pieces to define the status of the organization; (2) tangled parts to specify the structure (concepts and relations) between the elements of the organization; 3) lack of text properties, and other factors. These divergences imply a set of incomplete approaches to formalize data and information about organizations. Taking into account the current trends of applying semantic web technologies and linked data to formalize, aggregate, and share domain specific information, a new model for organizations taking advantage of these initiatives is required in order to overcome existing barriers and exploit the corporate information in a standard way. This work is especially relevant in some senses to: (1) unify existing models to provide a common specification; (2) apply semantic web technologies and the Linked Data approach; (3) provide access to the information via standard protocols, and (4) offer new services that can exploit this information to trace the evolution and behaviour of the organization over time. Finally, this work is interesting to improve the clarity and transparency of some scenarios in which organizations play a key role, like e-procurement, e-health, or financial transactions.

The present paper introduces a technique to deal with coporate names heterogeneities in the context of public procurement metadata. Public bodies are currently facing a big challenge trying to improve both the performance and the transparency of administrative processes. The e-Government and Open Linked Data initiatives have emerged as efforts to tackle existing interoperability and integration issues among ICT-based systems but the creation of a real transparent environment requires much more than the simple publication of data and information in specific open formats; data and information quality is the next major step in the pubic sector. More specifically in the e-Procurement domain there is a vast amount of valuable metadata that is already available via the Internet protocols and formats and can be used for the creation of new added-value services. Nevertheless the simple extraction of statistics or creation of reports can imply extra tasks with regards to clean, prepare and reconcile data. On the other hand, transparency has become a major objective in public administractions and, in the case of public procurement, one of the most interesting services lies in tracking rewarded contracts (mainly type, location, and supplier). Although it seems a basic kind of reporting service the truth is that its generation can turn into a complex task due to a lack of standardization in supplier names or the use of different descriptors for the type of contract. In this paper, a stepwise method based on natural language processing and semantics to address the unfication of corporate names is defined and implemented. Moreover a research study to evaluate the precision and recall of the proposed technique, using as use case the public dataset of rewarded public contracts in Australia during the period 2004-2012, is also presented. Finally some discussion, conclusions and future work are also outlined.

This chapter introduces the promotion of existing product scheme classifications to the Linked Open Data initiative in the context of the European Union and other official organizations such as United Nations. A common data model and an enclosed conversion method based on Semantic Web vocabularies such as SKOS are also presented to encode data and information following the W3C standards RDF and OWL. This work is applied to the e-procurement sector, more specifically, to enhance the access to the public procurement notices published in the European Union. Finally, an evaluation of the gain, in terms of expressivity, is reported with the objective of demonstrating the advantages of applying Linked Data to retrieve information resources.

The idea of "Web of data"[21] has been widely enhanced by the establishment of Linked Data principles on the Web [5]. The emergence of Linking Open Data Project opens the doors to the concept of Linked Open Data, establishing the basis for publishing open data, usable by anyone on the Web. However, even though the form (Linked Data) and the goal (Web of data) have been formally defined, the definition of a components architecture to support the implementation of such technologies is still fuzzy, as is a methodology of implementation associated with this architecture. The problem is that the definition and methodology together should enable both publishing and maintenance of semantic data in a standardized way for a subset of publishers, namely public administrators. In this paper we describe a first approach to an adoption process of Web Semantic technologies, specifically with regard to tools and methods that enable the publication and maintenance of Linked Open Data within the context of public administration. To this end, we review the related basic concepts, define infrastructure, describe its components and functions, and propose a sequence to be followed. Finally, we present a case of the use of our methodology in the Library of Congress of Chile.

The advent of the information age represents both a challenge and an opportunity for medicine. New forms of diagnosis, innovation-oriented supervision and expert location paths are deeply impacting medical sciences as we know it around the word. In this new scenario, semantic technologies can be seen as new and promising tool to support knowledge-based services, and particularly for the health domain, medical diagnosis. This chapter presents MedFinder, a system based on semantic technologies and social Web to improve patient care for medical diagnosis. The main breakthroughs of MedFinder are the follow-up once the diagnosis is performed, by using a medical ontology and formal reasoning together with rules, since it makes possible to locate the most appropriate doctor for a patient using Geographical Information Systems (GIS) and taking into account user preferences given via social Web feedback.

The annual accounts and other financial information of big companies is being worldwide standardized. The open standard that allows this standardization is XBRL, an XML vocabulary for exchanging financial information. In return for this initiative, the existence of different accounting standards in each country makes necessary to define specific XBRL taxonomies for each kind of accounting report, making the extraction of homogeneous information from different taxonomies difficult. This project seeks to incorporate a new level of abstraction through OWL ontologies, allowing the users of accounting reports to compare and exchange financial reports drawn up according to different standards. In addition, we propose a collaborative web environment through which experts in the Accounting domain will update the knowledge base of the system.

This article presents an analysis of the necessity to implement a tool of evaluation and measurement of the usability to support the ME-USitE methodology that contributes to the detection of problems and failures of usability from the perspective of the user of educative Web sites in a real work environment. Taking into account that the Web sites are designed and implemented for a domain and audience in particular, it's important to consider factors like these for the implementation of a tool that allows not only to carry out the evaluation process but also to support the analysis of the gathered data. Thus, the obtained results may allow us to establish policies for the improvement of the usability of the site, when providing a score that determines whether the level of usability offered covers the requirements for the proposed audience and the profile of the participant user in the evaluation.

Usability testing is normally used to determine the navigation map that better adapts to the average-user mental navigation model. However, usability testing is an expensive process, misses the influence that the computer environment has on navigation, and it is not able to record spontaneous user behaviour. The remote testing technique is an interesting and cheaper alternative that avoids the problems commented. We have developed our own set of tools based on data gathering agents for supporting remote testing. In this paper, we comment our experiences designing and developing such kind of systems and the results obtained when conducting human-computer interaction experiments based on access to web sites.

Language processors are not only important for the construction of compilers and interpreters but also for an increasing number of applications that relay on XML parsers like e-commerce software or grammar checkers like word processors.