3,730 research outputs found
XML Matchers: approaches and challenges
Schema Matching, i.e. the process of discovering semantic correspondences
between concepts adopted in different data source schemas, has been a key topic
in Database and Artificial Intelligence research areas for many years. In the
past, it was largely investigated especially for classical database models
(e.g., E/R schemas, relational databases, etc.). However, in the latest years,
the widespread adoption of XML in the most disparate application fields pushed
a growing number of researchers to design XML-specific Schema Matching
approaches, called XML Matchers, aiming at finding semantic matchings between
concepts defined in DTDs and XSDs. XML Matchers do not just take well-known
techniques originally designed for other data models and apply them on
DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical
structure of a DTD/XSD) to improve the performance of the Schema Matching
process. The design of XML Matchers is currently a well-established research
area. The main goal of this paper is to provide a detailed description and
classification of XML Matchers. We first describe to what extent the
specificities of DTDs/XSDs impact on the Schema Matching task. Then we
introduce a template, called XML Matcher Template, that describes the main
components of an XML Matcher, their role and behavior. We illustrate how each
of these components has been implemented in some popular XML Matchers. We
consider our XML Matcher Template as the baseline for objectively comparing
approaches that, at first glance, might appear as unrelated. The introduction
of this template can be useful in the design of future XML Matchers. Finally,
we analyze commercial tools implementing XML Matchers and introduce two
challenging issues strictly related to this topic, namely XML source clustering
and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure
Metamodel Instance Generation: A systematic literature review
Modelling and thus metamodelling have become increasingly important in
Software Engineering through the use of Model Driven Engineering. In this paper
we present a systematic literature review of instance generation techniques for
metamodels, i.e. the process of automatically generating models from a given
metamodel. We start by presenting a set of research questions that our review
is intended to answer. We then identify the main topics that are related to
metamodel instance generation techniques, and use these to initiate our
literature search. This search resulted in the identification of 34 key papers
in the area, and each of these is reviewed here and discussed in detail. The
outcome is that we are able to identify a knowledge gap in this field, and we
offer suggestions as to some potential directions for future research.Comment: 25 page
State-of-the-art on evolution and reactivity
This report starts by, in Chapter 1, outlining aspects of querying and updating resources on
the Web and on the Semantic Web, including the development of query and update languages
to be carried out within the Rewerse project.
From this outline, it becomes clear that several existing research areas and topics are of
interest for this work in Rewerse. In the remainder of this report we further present state of
the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give
an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs;
in Chapter 4 event-condition-action rules, both in the context of active database systems and
in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks
A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases
PhDData stored in individual autonomous databases often needs to be combined and
interrelated. For example, in the Inland Water (IW) environment monitoring domain,
the spatial and temporal variation of measurements of different water quality indicators
stored in different databases are of interest. Data from multiple data sources is more
complex to combine when there is a lack of metadata in a computation forin and when
the syntax and semantics of the stored data models are heterogeneous. The main types
of information retrieval (IR) requirements are query transparency and data
harmonisation for data interoperability and support for multiple user views. A
combined Semantic Web based and Agent based distributed system framework has
been developed to support the above IR requirements. It has been implemented using
the Jena ontology and JADE agent toolkits. The semantic part supports the
interoperability of autonomous data sources by merging their intensional data, using a
Global-As-View or GAV approach, into a global semantic model, represented in
DAML+OIL and in OWL. This is used to mediate between different local database
views. The agent part provides the semantic services to import, align and parse
semantic metadata instances, to support data mediation and to reason about data
mappings during alignment. The framework has applied to support information
retrieval, interoperability and multi-lateral viewpoints for four European environmental
agency databases.
An extended GAV approach has been developed and applied to handle queries that can
be reformulated over multiple user views of the stored data. This allows users to
retrieve data in a conceptualisation that is better suited to them rather than to have to
understand the entire detailed global view conceptualisation. User viewpoints are
derived from the global ontology or existing viewpoints of it. This has the advantage
that it reduces the number of potential conceptualisations and their associated
mappings to be more computationally manageable. Whereas an ad hoc framework
based upon conventional distributed programming language and a rule framework
could be used to support user views and adaptation to user views, a more formal
framework has the benefit in that it can support reasoning about the consistency,
equivalence, containment and conflict resolution when traversing data models. A
preliminary formulation of the formal model has been undertaken and is based upon
extending a Datalog type algebra with hierarchical, attribute and instance value
operators. These operators can be applied to support compositional mapping and
consistency checking of data views. The multiple viewpoint system was implemented
as a Java-based application consisting of two sub-systems, one for viewpoint
adaptation and management, the other for query processing and query result
adjustment
Peer Data Management
Peer Data Management (PDM) deals with the management of structured data in unstructured peer-to-peer (P2P) networks. Each peer can store data locally and define relationships between its data and the data provided by other peers. Queries posed to any of the peers are then answered by also considering the information implied by those mappings.
The overall goal of PDM is to provide semantically well-founded integration and exchange of heterogeneous and distributed data sources. Unlike traditional data integration systems, peer data management systems (PDMSs) thereby allow for full autonomy of each member and need no central coordinator. The promise of such systems is to provide flexible data integration and exchange at low setup and maintenance costs.
However, building such systems raises many challenges. Beside the obvious scalability problem, choosing an appropriate semantics that can deal with arbitrary, even cyclic topologies, data inconsistencies, or updates while at the same time allowing for tractable reasoning has been an area of active research in the last decade. In this survey we provide an overview of the different approaches suggested in the literature to tackle these problems, focusing on appropriate semantics for query answering and data exchange rather than on implementation specific problems
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