... The difference between a published XML schema and a PDV is subtle. On the one hand, even if not
mandatory, a PDV may discard useless nodes in the XML schema, by removing sub-trees or by replacing a
path between two nodes by a single “//” edge. Removing nodes helps improving schema management, storag ...
... Councils, as well as by project funding from the JISC’s Electronic Libraries
Programme and the European Union.
UKOLN also receives support from the University of Bath where it is based.
Relationalizing RDF stores for tools reusability
... blank node scenarios such as single or multi-valued literal blank
nodes, single or multi-valued resource blank nodes, and mixed
(literal/resource) blank nodes using a variety of constructs that are
described in . RDF features such as RDF Containers and RDF
Collections are also supported using the ...
Domain Ontologies: A Database-Oriented Analysis
... 1. Formal. An ontology is a conceptualization based on a formal theory which allows
to check some level of consistency and to perform some level of automatic reasoning over the ontology-defined concepts and individuals. We note that this criterion
excludes most meta-models that do not provide automa ...
... An RDF Data Model with inferencing (RDFS,
OWL and user-defined rules)
Performs SQL-based access to triples and
Combines SQL query of relational data with
RDF graphs and ontologies
Scalable: supports large graphs (billion+ triples)
Support for Special queries
... Materialize the RDF triples from the database using
Use a server to dynamically access the relational
data given a SPARQL query
Use a DBMS that directly supports RDF (e.g.,
Oracle 11g, DB2)
Organizing Committee and Contents
... refusal to any publication (including electronic distribution) arising from this AAAI event.
Please do not make any inquiries or arrangements for hardcopy or electronic publication of all
or part of the papers contained in these working notes without first exploring the options available through AAA ...
slides - Bio-Ontologies 2017
... The BioImage Database aims to provide a searchable database of highquality multidimensional research images of biological specimens, both
‘raw’ and processes, with detailed supporting metadata concerning:
the biological specimen itself
the experimental procedure
details of image formation and ...
... relates to parts of ontologies that have been created in the way that they can be changed
Full paper local copy - Semantic Web and Agent Technologies Lab
... 4) A set of performance metrics including data loading
time, repository size, query response time, and degree
of query completeness and soundness. We have
developed these metrics by borrowing from standard
database benchmarks and at the same time trying to
address the unique properties of the Semant ...
RDF Part II
... these languages allow smarter integration and
connection of data, making it easier to query and use
... authors of the OASIS standards, in particular Topic Maps. In Topic Maps we
have an open world assumption and very little emphasis on computational
inference. Human knowledge is represented in a “shallow form, and
visualization is used to manage this representation.
Computation with topic maps AND OW ...
Computational Complexity of Semantic Web Language
... • Whenever the complexity for a given problem is
described as Open, with a star, (*), it is meant
that its decidability is still an open question; if the
star (*) is omitted, then the problem is known to
be decidable but precise complexity bounds have
not yet been established. If a problem is lab ...
slides - Ontolog
... Web presence – Wiki (www.socop.org)
Ontologies and Databases: myths and challenges
... to the information mediated by the ontology. Good ontologies put their emphasis on the correct and semantically rich
representation of complex properties and relations that may
exist in the data; they should allow for an abstract representation of information which resembles the way they are
Semantic Web Applications in Bioinformatics
... • association of concepts to existing data,
• metadata information describing
information sources and contents,
• search tools able to make the best use of
this additional information.
... answer business questions? And…have the agility to add more
sources in a timely manner?
• How can I retrieve only the information that I need that is
“relevant” to me, versus everything?
• How can I extract value from paper-based forms/documents?
... classes they are a member of (type)
There are vocabularies that define constraints on
Web Ontology Language
The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects. Ontologies resemble class hierarchies in object-oriented programming but there are several critical differences. Class hierarchies are meant to represent structures used in source code that evolve fairly slowly (typically monthly revisions) whereas ontologies are meant to represent information on the Internet and are expected to be evolving almost constantly. Similarly, ontologies are typically far more flexible as they are meant to represent information on the Internet coming from all sorts of heterogeneous data sources. Class hierarchies on the other hand are meant to be fairly static and rely on far less diverse and more structured sources of data such as corporate databases. The OWL languages are characterized by formal semantics. They are built upon a W3C XML standard for objects called the Resource Description Framework (RDF). OWL and RDF have attracted significant academic, medical and commercial interest.In October 2007, a new W3C working group was started to extend OWL with several new features as proposed in the OWL 1.1 member submission. W3C announced the new version of OWL on 27 October 2009. This new version, called OWL 2, soon found its way into semantic editors such as Protégé and semantic reasoners such as Pellet, RacerPro, FaCT++ and HermiT.The OWL family contains many species, serializations, syntaxes and specifications with similar names. OWL and OWL2 are used to refer to the 2004 and 2009 specifications, respectively. Full species names will be used, including specification version (for example, OWL2 EL). When referring more generally, OWL Family will be used.