1,721,174 research outputs found

    Towards a pattern science for the Semantic Web

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    With the web of data, the semantic web can be an empirical science. Two problems have to be dealt with. The knowledge soup problem is about semantic heterogeneity, and can be considered a difficult technical issue, which needs appropriate transformation and inferential pipelines that can help making sense of the different knowledge contexts. The knowledge boundary problem is at the core of empirical investigation over the semantic web: what are the meaningful units that constitute the research objects for the semantic web? This question touches many aspects of semantic web studies: data, schemata, representation and reasoning, interaction, linguistic grounding, etc

    Observing LOD: Its Knowledge Domains and the Varying Behavior of Ontologies Across Them

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    Linked Open Data (LOD) is the largest, collaborative, distributed, and publicly-accessible Knowledge Graph (KG) uniformly encoded in the Resource Description Framework (RDF) and formally represented according to the semantics of the Web Ontology Language (OWL). LOD provides researchers with a unique opportunity to study knowledge engineering as an empirical science: to observe existing modelling practices and possibly understanding how to improve knowledge engineering methodologies and knowledge representation formalisms. Following this perspective, several studies have analysed LOD to identify (mis-)use of OWL constructs or other modelling phenomena e.g. class or property usage, their alignment, the average depth of taxonomies. A question that remains open is whether there is a relation between observed modelling practices and knowledge domains (natural science, linguistics, etc.): do certain practices or phenomena change as the knowledge domain varies? Answering this question requires an assessment of the domains covered by LOD as well as a classification of its datasets. Existing approaches to classify LOD datasets provide partial and unaligned views, posing additional challenges. In this paper, we introduce a classification of knowledge domains, and a method for classifying LOD datasets and ontologies based on it. We classify a large portion of LOD and investigate whether a set of observed phenomena have a domain-specific character

    Amnestic forgery: An ontology of conceptual metaphors

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    This paper presents Amnestic Forgery, an ontology for metaphor semantics, based on MetaNet, which is inspired by the theory of Conceptual Metaphor. Amnestic Forgery reuses and extends the Framester schema, as an ideal ontology design framework to deal with both semiotic and referential aspects of frame and role mappings. The description of the resource is supplied by a discussion of its applications, with examples taken from metaphor generation, and the referential problems of metaphoric mappings. Both schema and data are available from the Framester SPARQL endpoint

    A multi-dimensional comparison of ontology design patterns for representing n-ary relations

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    Within the broad area of knowledge pattern science, an important topic is the discovery, description, and evaluation of modeling patterns for a certain task. One of the most controversial problem is constituted by modeling relations with large or variable (polymorphic) arity. There is indeed a large literature on representing n-ary relations in logical languages with expressivity limited to unary and binary relations, e.g. when time, space, roles and other knowledge should be used as indexes to binary relations. In this paper we provide a comparison of several design patterns, based on their respective (dis)advantages, as well as on their axiomatic complexity. Data on actual processing time for queries and DL reasoning from an in-vitro study is also provided. © 2013 Springer-Verlag Berlin Heidelberg

    Melody: A Platform for Linked Open Data Visualisation and Curated Storytelling

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    Data visualisation and storytelling techniques help experts highlight relations between data and share complex information with a broad audience. However, existing solutions targeted to Linked Open Data visualisation have several restrictions and lack the narrative element. In this article we present MELODY, a web interface for authoring data stories based on Linked Open Data. MELODY has been designed using a novel methodology that harmonises existing Ontology Design and User Experience methodologies (eXtreme Design and Design Thinking), and provides reusable User Interface components to create and publish web-ready article-alike documents based on data retrievable from any SPARQL endpoint. We evaluate the software by comparing it with existing solutions, and we show its potential impact in projects where data dissemination is crucial

    Extending ScholarlyData with Research Impact Indicators

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    ScholarlyData is the reference linked dataset of the Semantic Web community about papers, people, organisations, and events related to its academic conferences. In this paper we present an extension of such a linked dataset and its associated ontology (i.e. the conference ontology) in order to represent research impact indicators. The latter includes both traditional (e.g. citation count) and alternative indicators (e.g. altmetrics)

    Benchmarking robots in smart cities

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    In order for robots to become integrated into society, we need to be able to prove that robots do their jobs reliably. Robot benchmarking competitions in smart cities offer a glimpse into our future

    The practice of self-citations: a longitudinal study

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    In this article, we discuss the outcomes of an experiment where we analysed whether and to what extent the introduction, in 2012, of the new research assessment exercise in Italy (a.k.a. Italian Scientific Habilitation) affected self-citation behaviours in the Italian research community. The Italian Scientific Habilitation attests to the scientific maturity of researchers and in Italy, as in many other countries, is a requirement for accessing to a professorship. To this end, we obtained from ScienceDirect 35,673 articles published from 1957 and 2016 by the participants to the 2012 Italian Scientific Habilitation, that resulted in the extraction of 1,379,050 citations retrieved through Semantic Publishing technologies. Our analysis showed an overall increment in author self-citations (i.e. where the citing article and the cited article share at least one author) in several of the 24 academic disciplines considered. However, we depicted a stronger causal relation between such increment and the rules introduced by the 2012 Italian Scientific Habilitation in 10 out of 24 disciplines analysed
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