Improving Data Integration through Disambiguation Techniques

In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined and an Approximate Word Sense Disambiguation approach (AWSD) is proposed for the automatic lexical annotation of structured and semi-structured data sources

Building an Urban Theft Map by Analyzing Newspaper Crime Reports

One of the main issues in today's cities is related to public safety, which can be improved by implementing a systematic analysis for identifying and analyzing patterns and trends in crime also called crime mapping. Mapping crime allows police analysts to identify crime hot spots, moreover it increases public confidence and citizen engagement and promotes transparency.This paper is focused on analyzing and mapping thefts through on-line newspaper using text mining techniques for an Italian city

High-level visualization over big linked data

The Linked Open Data (LOD) Cloud is continuously expanding and the number of complex and large sources is raising. Understanding at a glance an unknown source is a critical task for LOD users but it can be facilitated by visualization or exploration tools. H-BOLD (High-level visualization over Big Open Linked Data) is a tool that allows users with no a-priori knowledge on the domain nor SPARQL skills to start navigating and exploring Big Linked Data. Users can start from a high-level visualization and then focus on an element of interest to incrementally explore the source, as well as perform a visual query on certain classes of interest. At the moment, 32 Big Linked Data (with more than 500.000 triples) exposing a SPARQL endpoint can be explored by using H-BOLD

Providing effective visualizations over big linked data

The number and the size of Linked Data sources are constantly increasing. In some lucky case, the data source is equipped with a tool that guides and helps the user during the exploration of the data, but in most cases, the data are published as an RDF dump through a SPARQL endpoint that can be accessed only through SPARQL queries. Although the RDF format was designed to be processed by machines, there is a strong need for visualization and exploration tools. Data visualizations make big and small linked data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and outliers in groups of data. For this reason, we developed a tool called H-BOLD (Highlevel Visualization over Big Linked Open Data). H-BOLD aims to help the user exploring the content of a Linked Data by providing a high-level view of the structure of the dataset and an interactive exploration that allows users to focus on the connections and attributes of one or more classes. Moreover, it provides a visual interface for querying the endpoint that automatically generates SPARQL queries

Wearable devices for aging polulation.

Este trabajo de fin de grado es parte de un proyecto del ministerio italiano de salud en el cual se intenta dar a conocer y analizar los diferentes dispostivos de ayuda para personas mayores o personas que puedan padecer alguna enfermedad. Para ello, analizaremos y estudiaremos los datos de diferentes modelos y dispostivos de diferentes sistemas de información y bases de datos intentado proporcionar una visión global sobre estos nuevos instrumentos tecnológicos que nos ayudan en la actualidad. Primeramente, se examinaran los datos recogidos y se realizarán estadísticas para ver su rendimiento en diferentes ámbitos como el análisis de la frecuencia cardiaca, medidor de calorías, detección de caídas... Finalmente, se estudiará el modo de transmisión de datos de cada modelo de dispositivo para dar a entender donde se almacén los datos y que mecanismo de transmisión se utilizan para recolectarlos.<br /

Automatic annotation for mapping discovery in data integration systems (Extended abstract)

In this article we present CWSD (Combined Word Sense Disambiguation) a method and a software tool for enabling automatic lexical annotation of local (structured and semi-structured) data sources in a data integration system. CWSD is based on the exploitation of WordNet Domains and the lexical and structural knowledge of the data sources. The method extends the semi-automatic lexical annotation module of the MOMIS data integration system. The distinguishing feature of the method is its independence or low dependence of a human intervention. CWSD is a valid method to satisfy two important tasks: (1) the source lexical annotation process, i.e. the operation of associating an element of a lexical reference database (WordNet) to all source elements, (2) the discover of mappings among concepts of distributed data sources/ontologies

A Visual Summary for Linked Open Data sources

In this paper we propose LODeX, a tool that produces a representative summary of a Linked open Data (LOD) source starting from scratch, thus supporting users in exploring and understanding the contents of a dataset. The tool takes in input the URL of a SPARQL endpoint and launches a set of predefined SPARQL queries, from the results of the queries it generates a visual summary of the source. The summary reports statistical and structural information of the LOD dataset and it can be browsed to focus on particular classes or to explore their properties and their use. LODeX was tested on the 137 public SPARQL endpoints contained in Data Hub (formerly CKAN), one of the main Open Data catalogues. The statistical and structural information of the 107 well performed extractions are collected and available in the online version of LODeX (http://dbgroup.unimo.it/lodex)

LODeX: A tool for Visual Querying Linked Open Data

Formulating a query on a Linked Open Data (LOD) source is not an easy task; a technical knowledge of the query language, and, the awareness of the structure of the dataset are essential to create a query. We present a revised version of LODeX that provides the user an easy way for building queries in a fast and interactive manner. When a user decides to explore a LOD source, he/she can take advantage of the Schema Summary produced by LODeX (i.e. a synthetic view of the dataset’s structure) and he/she can pick graphical elements from it to create a visual query. The tool also supports the user in browsing the results and, eventually, in refining the query. The prototype has been evaluated on hundreds of public SPARQL endpoints (listed in Data Hub) and it is available online at http://dbgroup.unimo.it/lodex2. A survey conducted on 27 users has demonstrated that our tool can effectively support both unskilled and skilled users in exploring and querying LOD datasets