Procedimiento para la obtención de un modelo ontológico para representar la información contenida en bases de datos

El presente trabajo propone un procedimiento a través del cual un razonador evalúa la información de una base de datos y la clasifica de forma automática en conceptos, relaciones, roles y atributos. Esta clasificación se desarrolla mediante un procedimiento dividido en dos métodos: primero, un Algoritmo de migración el cual genera una ontología con los elementos del esquema relacional de la base de datos. El segundo método es la Estrategia de clasificación de la información, esta consiste en una serie de consultas SPARQL mediante las que se clasifica la información de la base de datos.---ABSTRACT---This paper proposes a method by which a reasoner evaluates information from a database and automatically classifies in concepts, relationships, roles and attributes. This classification is developed through a procedure divided into two methods: first, a migration algorithm which generates an ontology with elements of relational schema database. The second method is the strategy classification of information, this is a series of SPARQL queries through that classified using the information the database.

Seven challenges for RESTful transaction models

The REpresentational State Transfer (REST) architectural style describes the design principles that made the World Wide Web scalable and the same principles can be applied in enterprise context to do loosely coupled and scalable application integration. In recent years, RESTful services are gaining traction in the industry and are commonly used as a simpler alternative to SOAP Web Services. However, one of the main drawbacks of RESTful services is the lack of standard mechanisms to support advanced quality-ofservice requirements that are common to enterprises. Transaction processing is one of the essential features of enterprise information systems and several transaction models have been proposed in the past years to fulfill the gap of transaction processing in RESTful services. The goal of this paper is to analyze the state-of-the-art RESTful transaction models and identify the current challenges.

A Linked Data Platform adapter for the Bugzilla issue tracker

The W3C Linked Data Platform (LDP) specification defines a standard HTTP-based protocol for read/write Linked Data and pro- vides the basis for application integration using Linked Data. This paper presents an LDP adapter for the Bugzilla issue tracker and demonstrates how to use the LDP protocol to expose a traditional application as a read/write Linked Data application. This approach provides a exible LDP adoption strategy with minimal changes to existing applications.

Towards workflow ecosystems through standard representations

Workflows are increasingly used to manage and share scientific computations and methods. Workflow tools can be used to design, validate, execute and visualize scientific workflows and their execution results. Other tools manage workflow libraries or mine their contents. There has been a lot of recent work on workflow system integration as well as common workflow interlinguas, but the interoperability among workflow systems remains a challenge. Ideally, these tools would form a workflow ecosystem such that it should be possible to create a workflow with a tool, execute it with another, visualize it with another, and use yet another tool to mine a repository of such workflows or their executions. In this paper, we describe our approach to create a workflow ecosystem through the use of standard models for provenance (OPM and W3C PROV) and extensions (P-PLAN and OPMW) to represent workflows. The ecosystem integrates different workflow tools with diverse functions (workflow generation, execution, browsing, mining, and visualization) created by a variety of research groups. This is, to our knowledge, the first time that such a variety of workflow systems and functions are integrated.

FragFlow: automated fragment detection in scientific workflows

Scientific workflows provide the means to define, execute and reproduce computational experiments. However, reusing existing workflows still poses challenges for workflow designers. Workflows are often too large and too specific to reuse in their entirety, so reuse is more likely to happen for fragments of workflows. These fragments may be identified manually by users as sub-workflows, or detected automatically. In this paper we present the FragFlow approach, which detects workflow fragments automatically by analyzing existing workflow corpora with graph mining algorithms. FragFlow detects the most common workflow fragments, links them to the original workflows and visualizes them. We evaluate our approach by comparing FragFlow results against user-defined sub-workflows from three different corpora of the LONI Pipeline system. Based on this evaluation, we discuss how automated workflow fragment detection could facilitate workflow reuse.

Language resources and linked data: a practical perspective

Recently, experts and practitioners in language resources have started recognizing the benefits of the linked data (LD) paradigm for the representation and exploitation of linguistic data on the Web. The adoption of the LD principles is leading to an emerging ecosystem of multilingual open resources that conform to the Linguistic Linked Open Data Cloud, in which datasets of linguistic data are interconnected and represented following common vocabularies, which facilitates linguistic information discovery, integration and access. In order to contribute to this initiative, this paper summarizes several key aspects of the representation of linguistic information as linked data from a practical perspective. The main goal of this document is to provide the basic ideas and tools for migrating language resources (lexicons, corpora, etc.) as LD on the Web and to develop some useful NLP tasks with them (e.g., word sense disambiguation). Such material was the basis of a tutorial imparted at the EKAW’14 conference, which is also reported in the paper.

SMART Protocols: seMAntic represenTation for experimental protocols

Two important characteristics of science are the ?reproducibility? and ?clarity?. By rigorous practices, scientists explore aspects of the world that they can reproduce under carefully controlled experimental conditions. The clarity, complementing reproducibility, provides unambiguous descriptions of results in a mechanical or mathematical form. Both pillars depend on well-structured and accurate descriptions of scientific practices, which are normally recorded in experimental protocols, scientific workflows, etc. Here we present SMART Protocols (SP), our ontology-based approach for representing experimental protocols and our contribution to clarity and reproducibility. SP delivers an unambiguous description of processes by means of which data is produced; by doing so, we argue, it facilitates reproducibility. Moreover, SP is thought to be part of e-science infrastructures. SP results from the analysis of 175 protocols; from this dataset, we extracted common elements. From our analysis, we identified document, workflow and domain-specific aspects in the representation of experimental protocols. The ontology is available at http://purl.org/net/SMARTprotocol

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.

Workflow reuse in practice: a study of neuroimaging pipeline users

Workflow reuse is a major benefit of workflow systems and shared workflow repositories, but there are barely any studies that quantify the degree of reuse of workflows or the practical barriers that may stand in the way of successful reuse. In our own work, we hypothesize that defining workflow fragments improves reuse, since end-to-end workflows may be very specific and only partially reusable by others. This paper reports on a study of the current use of workflows and workflow fragments in labs that use the LONI Pipeline, a popular workflow system used mainly for neuroimaging research that enables users to define and reuse workflow fragments. We present an overview of the benefits of workflows and workflow fragments reported by users in informal discussions. We also report on a survey of researchers in a lab that has the LONI Pipeline installed, asking them about their experiences with reuse of workflow fragments and the actual benefits they perceive. This leads to quantifiable indicators of the reuse of workflows and workflow fragments in practice. Finally, we discuss barriers to further adoption of workflow fragments and workflow reuse that motivate further work.

HDTourist: exploring urban data on Android

The Web of Data currently comprises ? 62 billion triples from more than 2,000 different datasets covering many fields of knowledge3. This volume of structured Linked Data can be seen as a particular case of Big Data, referred to as Big Semantic Data [4]. Obviously, powerful computational configurations are tradi- tionally required to deal with the scalability problems arising to Big Semantic Data. It is not surprising that this ?data revolution? has competed in parallel with the growth of mobile computing. Smartphones and tablets are massively used at the expense of traditional computers but, to date, mobile devices have more limited computation resources. Therefore, one question that we may ask ourselves would be: can (potentially large) semantic datasets be consumed natively on mobile devices? Currently, only a few mobile apps (e.g., [1, 9, 2, 8]) make use of semantic data that they store in the mobile devices, while many others access existing SPARQL endpoints or Linked Data directly. Two main reasons can be considered for this fact. On the one hand, in spite of some initial approaches [6, 3], there are no well-established triplestores for mobile devices. This is an important limitation because any po- tential app must assume both RDF storage and SPARQL resolution. On the other hand, the particular features of these devices (little storage space, less computational power or more limited bandwidths) limit the adoption of seman- tic data for different uses and purposes. This paper introduces our HDTourist mobile application prototype. It con- sumes urban data from DBpedia4 to help tourists visiting a foreign city. Although it is a simple app, its functionality allows illustrating how semantic data can be stored and queried with limited resources. Our prototype is implemented for An- droid, but its foundations, explained in Section 2, can be deployed in any other platform. The app is described in Section 3, and Section 4 concludes about our current achievements and devises the future work.

Towards efficient processing of RDF Data Streams

In the last years, there has been an increase in the amount of real-time data generated. Sensors attached to things are transforming how we interact with our environment. Extracting meaningful information from these streams of data is essential for some application areas and requires processing systems that scale to varying conditions in data sources, complex queries, and system failures. This paper describes ongoing research on the development of a scalable RDF streaming engine.

A semantic-based approach to attain reproducibility of computational environments in scientific workflows: a case study

Reproducible research in scientific workflows is often addressed by tracking the provenance of the produced results. While this approach allows inspecting intermediate and final results, improves understanding, and permits replaying a workflow execution, it does not ensure that the computational environment is available for subsequent executions to reproduce the experiment. In this work, we propose describing the resources involved in the execution of an experiment using a set of semantic vocabularies, so as to conserve the computational environment. We define a process for documenting the workflow application, management system, and their dependencies based on 4 domain ontologies. We then conduct an experimental evaluation using a real workflow application on an academic and a public Cloud platform. Results show that our approach can reproduce an equivalent execution environment of a predefined virtual machine image on both computing platforms.

RDSZ: an approach for lossless RDF stream compression

In many applications (like social or sensor networks) the in- formation generated can be represented as a continuous stream of RDF items, where each item describes an application event (social network post, sensor measurement, etc). In this paper we focus on compressing RDF streams. In particular, we propose an approach for lossless RDF stream compression, named RDSZ (RDF Differential Stream compressor based on Zlib). This approach takes advantage of the structural similarities among items in a stream by combining a differential item encoding mechanism with the general purpose stream compressor Zlib. Empirical evaluation using several RDF stream datasets shows that this combi- nation produces gains in compression ratios with respect to using Zlib alone.

Are some brain injury patients improving more than ohers?

Predicting the evolution of individuals is a rather new mining task with applications in medicine. Medical researchers are interested in the progress of a disease and in the evolution of individuals subjected to treatment. We investigate the evolution of patients on the basis of medical tests before and during treatment after brain trauma: we want to understand how similar patients can become to healthy participants. We face two challenges. First, we have less information on healthy participants than on the patients. Second, the values of the medical tests for patients, even after treatment started, remain well-separated from those of healthy people; this is typical for neurodegenerative diseases, but also for further brain impairments. Our approach encompasses methods for modelling patient evolution and for predicting the health improvement of different patient subpopulations, dealing with the above challenges. We test our approach on a cohort of patients treated after brain trauma and a corresponding cohort of controls.

Designer-driven 3D buildings generated using variable neighborhood search

This paper presents a mechanism to generate virtual buildings considering designer constraints and guidelines. This mechanism is implemented as a pipeline of different Variable Neighborhood Search (VNS) optimization processes in which several subproblems are tackled (1) rooms locations, (2) connectivity graph, and (3) element placement. The core VNS algorithm includes some variants to improve its performance, such as, for example constraint handling and biased operator selection. The optimization process uses a toolkit of construction primitives implemented as "smart objects" providing basic elements such as rooms, doors, staircases and other connectors. The paper also shows experimental results of the application of different designer constraints to a wide range of buildings from small houses to a large castle with several underground levels.