RDA and Linked Data: A New Way to Look at the Henson Collection

In 2005, the University of Maryland acquired over 70 digital videos spanning 35 years of Jim Henson’s groundbreaking work in television and film. To support in-house discovery and use, the collection was cataloged in detail using AACR2 and MARC21, and a web-based finding aid was also created. In the past year, I created an "r-ball" (a linked data set described using RDA) of these same resources. The presentation will compare and contrast these three ways of accessing the Jim Henson Works collection, with insights gleaned from providing resource discovery using RIMMF (RDA in Many Metadata Formats).

Um modelo de suporte à comunicação de agentes para tratamento de informação imprecisa baseada em sinônimos

Este trabalho propõe o desenvolvimento de um modelo de suporte á comunicação entre agentes e uma Ontologia com informações imprecisas. Os conceitos desta ontologia podem possuir sinônimos possibilitando a interpretação de termos linguísticos imprecisos. Tal problema é relacionado às questões de desenvolvimento da comunicação em Sistemas Multiagentes, possuindo como referência uma base de conhecimento da qual estes agentes possam requisitar informações. Neste estudo, a premissa do modelo é o de ser útil como componente na utilização por desenvolvedores que queiram utilizar de forma simplificada uma conexão com uma Ontologia para dar suporte na comunicação. Para o presente estudo são discutidos os conceitos sobre a comunicação no ambiente multiagentes. Também é realizada uma revisão sobre o desenvolvimento de Ontologias, de forma a criar uma ontologia para os agentes. A lógica nebulosa, baseado em variáveis linguísticas, servirá como modeladora da imprecisão da informação, dando suporte a essa questão com a Ontologia e a comunicação. De forma a validar o modelo proposto, é realizado um estudo de caso no sistema multiagentes das hortas urbanas do Parque San Jerónimo, de Sevilha, Espanha.

Top-K Query Processing in Edge-Labeled Graph Data

Edge-labeled graphs have proliferated rapidly over the last decade due to the increased popularity of social networks and the Semantic Web. In social networks, relationships between people are represented by edges and each edge is labeled with a semantic annotation. Hence, a huge single graph can express many different relationships between entities. The Semantic Web represents each single fragment of knowledge as a triple (subject, predicate, object), which is conceptually identical to an edge from subject to object labeled with predicates. A set of triples constitutes an edge-labeled graph on which knowledge inference is performed. Subgraph matching has been extensively used as a query language for patterns in the context of edge-labeled graphs. For example, in social networks, users can specify a subgraph matching query to find all people that have certain neighborhood relationships. Heavily used fragments of the SPARQL query language for the Semantic Web and graph queries of other graph DBMS can also be viewed as subgraph matching over large graphs. Though subgraph matching has been extensively studied as a query paradigm in the Semantic Web and in social networks, a user can get a large number of answers in response to a query. These answers can be shown to the user in accordance with an importance ranking. In this thesis proposal, we present four different scoring models along with scalable algorithms to find the top-k answers via a suite of intelligent pruning techniques. The suggested models consist of a practically important subset of the SPARQL query language augmented with some additional useful features. The first model called Substitution Importance Query (SIQ) identifies the top-k answers whose scores are calculated from matched vertices' properties in each answer in accordance with a user-specified notion of importance. The second model called Vertex Importance Query (VIQ) identifies important vertices in accordance with a user-defined scoring method that builds on top of various subgraphs articulated by the user. Approximate Importance Query (AIQ), our third model, allows partial and inexact matchings and returns top-k of them with a user-specified approximation terms and scoring functions. In the fourth model called Probabilistic Importance Query (PIQ), a query consists of several sub-blocks: one mandatory block that must be mapped and other blocks that can be opportunistically mapped. The probability is calculated from various aspects of answers such as the number of mapped blocks, vertices' properties in each block and so on and the most top-k probable answers are returned. An important distinguishing feature of our work is that we allow the user a huge amount of freedom in specifying: (i) what pattern and approximation he considers important, (ii) how to score answers - irrespective of whether they are vertices or substitution, and (iii) how to combine and aggregate scores generated by multiple patterns and/or multiple substitutions. Because so much power is given to the user, indexing is more challenging than in situations where additional restrictions are imposed on the queries the user can ask. The proposed algorithms for the first model can also be used for answering SPARQL queries with ORDER BY and LIMIT, and the method for the second model also works for SPARQL queries with GROUP BY, ORDER BY and LIMIT. We test our algorithms on multiple real-world graph databases, showing that our algorithms are far more efficient than popular triple stores.

POWKist: visualising cultural heritage linked datasets.

A collaboration between dot.rural at the University of Aberdeen and the iSchool at Northumbria University, POWkist is a pilot-study exploring potential usages of currently available linked datasets within the cultural heritage domain. Many privately-held family history collections (shoebox archives) remain vulnerable unless a sustainable, affordable and accessible model of citizen-archivist digital preservation can be offered. Citizen-historians have used the web as a platform to preserve cultural heritage, however with no accessible or sustainable model these digital footprints have been ad hoc and rarely connected to broader historical research. Similarly, current approaches to connecting material on the web by exploiting linked datasets do not take into account the data characteristics of the cultural heritage domain. Funded by Semantic Media, the POWKist project is investigating how best to capture, curate, connect and present the contents of citizen-historians’ shoebox archives in an accessible and sustainable online collection. Using the Curios platform - an open-source digital archive - we have digitised a collection relating to a prisoner of war during WWII (1939-1945). Following a series of user group workshops, POWkist is now connecting these ‘made digital’ items with the broader web using a semantic technology model and identifying appropriate linked datasets of relevant content such as DBPedia (an archived linked dataset of Wikipedia) and Ordnance Survey Open Data. We are analysing the characteristics of cultural heritage linked datasets, so that these materials are better visualised, contextualised and presented in an attractive and comprehensive user interface. Our paper will consider the issues we have identified, the solutions we are developing and include a demonstration of our work-in-progress.

Epidemiología y clínica de los pacientes de 1 mes a 5 años ingresados en el HNNBB con enfermedad respiratoria grave de etiología viral. Enero 2012-Diciembre 2013

Introducción: Las Infecciones Respiratorias Agudas Graves (IRAG) son una causa importante de morbilidad y mortalidad infantil a nivel mundial, sobre todo en los niños menores de 5 años. Se estiman alrededor de 146-159 millones nuevos casos al año en los países en vías de desarrollo, causando aproximadamente 4 millones de muertes en la población pediátrica mundial. Objetivo: Describir la incidencia de los virus respiratorios, características clínicas y epidemiológicas en pacientes desde 1 mes a 5 años que ingresan por diagnóstico de enfermedad respiratoria grave de etiología viral al Hospital Nacional de Niños Benjamín Bloom. Material y método: Estudio descriptivo, retrospectivo de corte transversal. Se estudiaron todos los niños de 1 mes a 5 años que ingresaron al Hospital Nacional de Niños Benjamín Bloom, incluidos en la vigilancia centinela con hisopado nasofaríngeo positivo de enero 2012 a diciembre 2013. Resultados: 6 de cada 10 pacientes son menores de 1 año, 51% son del sexo masculino. La sintomatología predominante fue tos (99%), dificultad respiratoria (98%) y fiebre (83%). Un 35% de los pacientes necesitó soporte ventilatorio al ingreso. El 49% no tenían patología previa, un 11% eran prematuros, detectándose en el 100% de ellos el virus sincitial respiratorio. Se reportó positivo a Virus Sincitial Respiratorio (VSR) en el 48% de los casos, seguido de Influenza A 12%, Adenovirus 11% y Parainfluenza 10% aumentándose los casos de todos estos en los meses de invierno. En un 76% de los casos se utilizó uno o más antibióticos, las cefalosporinas de 3ra generación son las más utilizadas. No se detecto patrón radiológico característico de infección viral. Conclusiones: El virus Sincitial respiratorio es el virus que más causa neumonía en menores de 5 años, siendo los prematuros altamente susceptibles.

A multi-method study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the activation pathway

The change in the carbonaceous skeleton of nanoporous carbons during their activation has received limited attention, unlike its counterpart process in the presence of an inert atmosphere. Here we adopt a multi-method approach to elucidate this change in a poly(furfuryl alcohol)-derived carbon activated using cyclic application of oxygen saturation at 250 °C before its removal (with carbon) at 800 °C in argon. The methods used include helium pycnometry, synchrotron-based X-ray diffraction (XRD) and associated radial distribution function (RDF) analysis, transmission electron microscopy (TEM) and, uniquely, electron energy-loss spectroscopy spectrum-imaging (EELS-SI), electron nanodiffraction and fluctuation electron microscopy (FEM). Helium pycnometry indicates the solid skeleton of the carbon densifies during activation from 78% to 93% of graphite. RDF analysis, EELS-SI, and FEM all suggest this densification comes through an in-plane growth of sp2 carbon out to the medium range without commensurate increase in order normal to the plane. This process could be termed ‘graphenization’. The exact way in which this process occurs is not clear, but TEM images of the carbon before and after activation suggest it may come through removal of the more reactive carbon, breaking constraining cross-links and creating space that allows the remaining carbon material to migrate in an annealing-like process.

Enriquecimento semântico de modelos ecológicos baseados em raciocínio qualitativo : um estudo de caso sobre a dinâmica de comunidades de vegetação lenhosa no cerrado brasileiro

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Ecologia, 2015.

RSLT: trasformazione di Open LinkedData in testi in linguaggio naturaletramite template dichiarativi

La diffusione del Semantic Web e di dati semantici in formato RDF, ha creato la necessità di un meccanismo di trasformazione di tali informazioni, semplici da interpretare per una macchina, in un linguaggio naturale, di facile comprensione per l'uomo. Nella dissertazione si discuterà delle soluzioni trovate in letteratura e, nel dettaglio, di RSLT, una libreria JavaScript che cerca di risolvere questo problema, consentendo la creazione di applicazioni web in grado di eseguire queste trasformazioni tramite template dichiarativi. Verranno illustrati, inoltre, tutti i cambiamenti e tutte le modi�che introdotte nella versione 1.1 della libreria, la cui nuova funzionalit�à principale �è il supporto a SPARQL 1.0.

URIs and Intertextuality: Incumbent Philosophical Commitments in the Development of the Semantic Web

Examines two commitments inherent in Resource Description Framework (RDF): intertextuality and rationalism. After introducing how rationalism has been studied in knowledge organization, this paper then introduces the concept of bracketed-rationalism. This paper closes with a discussion of ramifications of intertextuality and bracketed rationalism on evaluation of RDF.

Versioning Concept Schemes for Persistent Retrieval

Things change. Words change, meaning changes and use changes both words and meaning. In information access systems this means concept schemes such as thesauri or clas- sification schemes change. They always have. Concept schemes that have survived have evolved over time, moving from one version, often called an edition, to the next. If we want to manage how words and meanings - and as a conse- quence use - change in an effective manner, and if we want to be able to search across versions of concept schemes, we have to track these changes. This paper explores how we might expand SKOS, a World Wide Web Consortium (W3C) draft recommendation in order to do that kind of tracking.The Simple Knowledge Organization System (SKOS) Core Guide is sponsored by the Semantic Web Best Practices and Deployment Working Group. The second draft, edited by Alistair Miles and Dan Brickley, was issued in November 2005. SKOS is a “model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, other types of controlled vocabulary and also concept schemes embedded in glossaries and terminologies” in RDF. How SKOS handles version in concept schemes is an open issue. The current draft guide suggests using OWL and DCTERMS as mechanisms for concept scheme revision.As it stands an editor of a concept scheme can make notes or declare in OWL that more than one version exists. This paper adds to the SKOS Core by introducing a tracking sys- tem for changes in concept schemes. We call this tracking system vocabulary ontogeny. Ontogeny is a biological term for the development of an organism during its lifetime. Here we use the ontogeny metaphor to describe how vocabularies change over their lifetime. Our purpose here is to create a conceptual mechanism that will track these changes and in so doing enhance information retrieval and prevent document loss through versioning, thereby enabling persistent retrieval.

Gestion de contexte dans un habitat intelligent à base d’ontologie : modélisation, implantation et validation

Le laboratoire DOMUS développe des applications sensibles au contexte dans une perspective d’intelligence ambiante. L’architecture utilisée présentement pour gérer le contexte a atteint ses limites en termes de capacité d’évoluer, d’intégration de nouvelles sources de données et de nouveaux capteurs et actionneurs, de capacité de partage entre les applications et de capacité de raisonnement. Ce projet de recherche a pour objectif de développer un nouveau modèle, un gestionnaire de contexte et de proposer une architecture pour les applications d’assistance installées dans un habitat intelligent. Le modèle doit répondre aux exigences suivantes : commun, abstrait, évolutif, décentralisé, performant et une accessibilité uniforme. Le gestionnaire du contexte doit permettre de gérer les événements et offrir des capacités de raisonnement sur les données et le contexte. La nouvelle architecture doit simplifier le développement d’applications d’assistance et la gestion du contexte. Les applications doivent pouvoir se mettre à jour si le modèle de données évolue dans le temps sans nécessiter de modification dans le code source. Le nouveau modèle de données repose sur une ontologie définie avec le langage OWL 2 DL. L’architecture pour les applications d’assistance utilise le cadre d’applications Apache Jena pour la gestion des requêtes SPARQL et un dépôt RDF pour le stockage des données. Une bibliothèque Java a été développée pour gérer la correspondance entre le modèle de données et le modèle Java. Le serveur d’événements est basé sur le projet OpenIoT et utilise un dépôt RDF. Il fournit une API pour la gestion des capteurs / événements et des actionneurs / actions. Les choix d’implémentation et l’utilisation d’une ontologie comme modèle de données et des technologies du Web sémantique (OWL, SPARQL et dépôt RDF) pour les applications d’assistance dans un habitat intelligent ont été validés par des tests intensifs et l’adaptation d’applications déjà existantes au laboratoire. L’utilisation d’une ontologie a pour avantage une intégration des déductions et du raisonnement directement dans le modèle de données et non au niveau du code des applications.

Connecting works of art within the semantic web of symbolic meanings

My doctoral research is about the modelling of symbolism in the cultural heritage domain, and on connecting artworks based on their symbolism through knowledge extraction and representation techniques. In particular, I participated in the design of two ontologies: one models the relationships between a symbol, its symbolic meaning, and the cultural context in which the symbol symbolizes the symbolic meaning; the second models artistic interpretations of a cultural heritage object from an iconographic and iconological (thus also symbolic) perspective. I also converted several sources of unstructured data, a dictionary of symbols and an encyclopaedia of symbolism, and semi-structured data, DBpedia and WordNet, to create HyperReal, the first knowledge graph dedicated to conventional cultural symbolism. By making use of HyperReal's content, I showed how linked open data about cultural symbolism could be utilized to initiate a series of quantitative studies that analyse (i) similarities between cultural contexts based on their symbologies, (ii) broad symbolic associations, (iii) specific case studies of symbolism such as the relationship between symbols, their colours, and their symbolic meanings. Moreover, I developed a system that can infer symbolic, cultural context-dependent interpretations from artworks according to what they depict, envisioning potential use cases for museum curation. I have then re-engineered the iconographic and iconological statements of Wikidata, a widely used general-domain knowledge base, creating ICONdata: an iconographic and iconological knowledge graph. ICONdata was then enriched with automatic symbolic interpretations. Subsequently, I demonstrated the significance of enhancing artwork information through alignment with linked open data related to symbolism, resulting in the discovery of novel connections between artworks. Finally, I contributed to the creation of a software application. This application leverages established connections, allowing users to investigate the symbolic expression of a concept across different cultural contexts through the generation of a three-dimensional exhibition of artefacts symbolising the chosen concept.

Ethics in the flesh: formalizing moral values in embodied cognition

Values are beliefs or principles that are deemed significant or desirable within a specific society or culture, serving as the fundamental underpinnings for ethical and socio-behavioral norms. The objective of this research is to explore the domain encompassing moral, cultural, and individual values. To achieve this, we employ an ontological approach to formally represent the semantic relations within the value domain. The theoretical framework employed adopts Fillmore’s frame semantics, treating values as semantic frames. A value situation is thus characterized by the co-occurrence of specific semantic roles fulfilled within a given event or circumstance. Given the intricate semantics of values as abstract entities with high social capital, our investigation extends to two interconnected domains. The first domain is embodied cognition, specifically image schemas, which are cognitive patterns derived from sensorimotor experiences that shape our conceptualization of entities in the world. The second domain pertains to emotions, which are inherently intertwined with the realm of values. Consequently, our approach endeavors to formalize the semantics of values within an embodied cognition framework, recognizing values as emotional-laden semantic frames. The primary ontologies proposed in this work are: (i) ValueNet, an ontology network dedicated to the domain of values; (ii) ISAAC, the Image Schema Abstraction And Cognition ontology; and (iii) EmoNet, an ontology for theories of emotions. The knowledge formalization adheres to established modeling practices, including the reuse of semantic web resources such as WordNet, VerbNet, FrameNet, DBpedia, and alignment to foundational ontologies like DOLCE, as well as the utilization of Ontology Design Patterns. These ontological resources are operationalized through the development of a fully explainable frame-based detector capable of identifying values, emotions, and image schemas generating knowledge graphs from from natural language, leveraging the semantic dependencies of a sentence, and allowing non trivial higher layer knowledge inferences.

Studio ed integrazione di Grafana per la visualizzazione di flussi di dati generati dalla piattaforma semantica SEPA

Questo elaborato mostra lo sviluppo di un plugin per la visualizzazione in Grafana di eventi provenienti dalla piattaforma semantica SEPA (SPARQL Event Processing Architecture). La principale funzione svolta dal SEPA è quella di notificare in modo asincrono i propri client rispetto al cambiamento dei risultati di una query che interroga il sottostante grafo RDF. La piattaforma trova il suo utilizzo in quei contesti caratterizzati da dati dinamici, eterogenei e non strutturati e viene impiegata principalmente come strumento per abilitare l’interoperabilità in domini come per esempio l’Internet of Things. Nasce quindi l’esigenza di disporre di strumenti per il monitoraggio e la visualizzazione di dati real-time. Grafana risulta in questo caso lo strumento ideale data la sua flessibilità, che affiancata alla sua natura open source, lo rende particolarmente interessante per lo sviluppo della soluzione proposta da VAIMEE, spinoff dell’Università di Bologna, ospitato presso il CesenaLab, luogo dove è stato svolto questo lavoro di tesi.

Analisi delle nozioni di dibattito e di incertezza in Wikidata

In questo elaborato si analizzano i principali metodi di rappresentazione delle nozioni di incertezza e di dibattito all’interno della Knowledge Base di Wikidata. In particolare, quali sono i metodi per rappresentare tali nozioni, quali tra questi metodi è il più utilizzato, quali offrono un'accuratezza maggiore (ovvero delle informazioni aggiuntive sulla motivazione del perché un determinato statement è in discussione) e infine la presenza di possibili correlazioni tra i vari metodi. Innanzitutto, è stato svolto uno studio preliminare volto a individuare tali metodi in Wikidata. In seguito, sono stati estratti e costruiti quattro dataset rappresentativi del dominio descritto che contenessero le rappresentazioni in esame. Ogni dataset, rappresentativo di un metodo di rappresentazione, è stato prima analizzato singolarmente e in seguito è stata ricercata la presenza degli altri metodi nello stesso. Infine sono stati presentati gli sviluppi futuri, i punti di forza e le debolezze del lavoro svolto.