2,480 research outputs found
Evaluation of the Impacts of Data Model and Query Language on Query Performance
It is important to understand how users can utilize database systems more effectively to enhance performance. A major research interest is to evaluate and compare user performance across different data models and query languages. So far, experiments have tested combinations of model plus language. An interesting theoretical and practical question is: how much of the performance difference is caused by the data model itself, and how much by the additional query language syntax? A cognitive model of query processing suggests measurement at two stages. The data model has impact at the first stage, and the model with the query language syntax together has the impact at the second stage. An experiment that compares the objected-oriented and relational models and query languages at the two stages provides fresh results
Dwelling on ontology - semantic reasoning over topographic maps
The thesis builds upon the hypothesis that the spatial arrangement of topographic
features, such as buildings, roads and other land cover parcels, indicates how land is
used. The aim is to make this kind of high-level semantic information explicit within
topographic data. There is an increasing need to share and use data for a wider range of
purposes, and to make data more definitive, intelligent and accessible. Unfortunately,
we still encounter a gap between low-level data representations and high-level concepts
that typify human qualitative spatial reasoning. The thesis adopts an ontological
approach to bridge this gap and to derive functional information by using standard
reasoning mechanisms offered by logic-based knowledge representation formalisms. It
formulates a framework for the processes involved in interpreting land use information
from topographic maps. Land use is a high-level abstract concept, but it is also an
observable fact intimately tied to geography. By decomposing this relationship, the
thesis correlates a one-to-one mapping between high-level conceptualisations
established from human knowledge and real world entities represented in the data.
Based on a middle-out approach, it develops a conceptual model that incrementally
links different levels of detail, and thereby derives coarser, more meaningful
descriptions from more detailed ones. The thesis verifies its proposed ideas by
implementing an ontology describing the land use ‘residential area’ in the ontology
editor Protégé. By asserting knowledge about high-level concepts such as types of
dwellings, urban blocks and residential districts as well as individuals that link directly
to topographic features stored in the database, the reasoner successfully infers instances
of the defined classes. Despite current technological limitations, ontologies are a
promising way forward in the manner we handle and integrate geographic data,
especially with respect to how humans conceptualise geographic space
Experiencing OptiqueVQS: A Multi-paradigm and Ontology-based Visual Query System for End Users
This is author's post-print version, published version available on http://link.springer.com/article/10.1007%2Fs10209-015-0404-5Data access in an enterprise setting is a determining factor for value creation processes, such as sense-making, decision-making, and intelligence analysis. Particularly, in an enterprise setting, intuitive data access tools that directly engage domain experts with data could substantially increase competitiveness and profitability. In this respect, the use of ontologies as a natural communication medium between end users and computers has emerged as a prominent approach. To this end, this article introduces a novel ontology-based visual query system, named OptiqueVQS, for end users. OptiqueVQS is built on a powerful and scalable data access platform and has a user-centric design supported by a widget-based flexible and extensible architecture allowing multiple coordinated representation and interaction paradigms to be employed. The results of a usability experiment performed with non-expert users suggest that OptiqueVQS provides a decent level of expressivity and high usability and hence is quite promising
Searching COVID-19 clinical research using graphical abstracts
Objective. Graphical abstracts are small graphs of concepts that visually
summarize the main findings of scientific articles. While graphical abstracts
are customarily used in scientific publications to anticipate and summarize
their main results, we propose them as a means for expressing graph searches
over existing literature. Materials and methods. We consider the COVID-19 Open
Research Dataset (CORD-19), a corpus of more than one million abstracts; each
of them is described as a graph of co-occurring ontological terms, selected
from the Unified Medical Language System (UMLS) and the Ontology of Coronavirus
Infectious Disease (CIDO). Graphical abstracts are also expressed as graphs of
ontological terms, possibly augmented by utility terms describing their
interactions (e.g., "associated with", "increases", "induces"). We build a
co-occurrence network of concepts mentioned in the corpus; we then identify the
best matches of graphical abstracts on the network. We exploit graph database
technology and shortest-path queries. Results. We build a large co-occurrence
network, consisting of 128,249 entities and 47,198,965 relationships. A
well-designed interface allows users to explore the network by formulating or
adapting queries in the form of an abstract; it produces a bibliography of
publications, globally ranked; each publication is further associated with the
specific parts of the abstract that it explains, thereby allowing the user to
understand each aspect of the matching. Discussion and Conclusion. Our approach
supports the process of scientific hypothesis formulation and evidence search;
it can be reapplied to any scientific domain, although our mastering of UMLS
makes it most suited to clinical domains.Comment: 12 pages, 6 figure
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