123,076 research outputs found
Report on the XBase Project
This project addressed the conceptual fundamentals of data storage,
investigating techniques for provision of highly generic storage facilities
that can be tailored to produce various individually customised storage
infrastructures, compliant to the needs of particular applications. This
requires the separation of mechanism and policy wherever possible. Aspirations
include: actors, whether users or individual processes, should be able to bind
to, update and manipulate data and programs transparently with respect to their
respective locations; programs should be expressed independently of the storage
and network technology involved in their execution; storage facilities should
be structure-neutral so that actors can impose multiple interpretations over
information, simultaneously and safely; information should not be discarded so
that arbitrary historical views are supported; raw stored information should be
open to all; where security restrictions on its use are required this should be
achieved using cryptographic techniques. The key advances of the research were:
1) the identification of a candidate set of minimal storage system building
blocks, which are sufficiently simple to avoid encapsulating policy where it
cannot be customised by applications, and composable to build highly flexible
storage architectures 2) insight into the nature of append-only storage
components, and the issues arising from their application to common storage
use-cases
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Geospatial data integration with Semantic Web services: the eMerges approach
Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies
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Methods of conceptual clustering and their relation to numerical taxonomy
Artificial Intelligence (AI) methods for machine learning can be viewed as forms of exploratory data analysis, even though they differ markedly from the statistical methods generally connoted by the term. The distinction between methods of machine learning and statistical data analysis is primarily due to differences in the way techniques of each type represent data and structure within data. That is, methods of machine learning are strongly biased toward symbolic (as opposed to numeric) data representations. We explore this difference within a limited context, devoting the bulk of our paper to the explication of conceptual clustering, an extension to the statistically based methods of numerical taxonomy. In conceptual clustering the formation of object clusters is dependent on the quality of 'higher-level' characterizations, termed concepts, of the clusters. The form of concepts used by existing conceptual clustering systems (sets of necessary and sufficient conditions) is described in some detail. This is followed by descriptions of several conceptual clustering techniques, along with sample output. We conclude with a discussion of how alternative concept representations might enhance the effectiveness of future conceptual clustering systems
Internal representations, external representations and ergonomics: towards a theoretical integration
The MMT API: A Generic MKM System
The MMT language has been developed as a scalable representation and
interchange language for formal mathematical knowledge. It permits natural
representations of the syntax and semantics of virtually all declarative
languages while making MMT-based MKM services easy to implement. It is
foundationally unconstrained and can be instantiated with specific formal
languages.
The MMT API implements the MMT language along with multiple backends for
persistent storage and frontends for machine and user access. Moreover, it
implements a wide variety of MMT-based knowledge management services. The API
and all services are generic and can be applied to any language represented in
MMT. A plugin interface permits injecting syntactic and semantic idiosyncrasies
of individual formal languages.Comment: Conferences on Intelligent Computer Mathematics (CICM) 2013 The final
publication is available at http://link.springer.com
IGUANA Architecture, Framework and Toolkit for Interactive Graphics
IGUANA is a generic interactive visualisation framework based on a C++
component model. It provides powerful user interface and visualisation
primitives in a way that is not tied to any particular physics experiment or
detector design. The article describes interactive visualisation tools built
using IGUANA for the CMS and D0 experiments, as well as generic GEANT4 and
GEANT3 applications. It covers features of the graphical user interfaces, 3D
and 2D graphics, high-quality vector graphics output for print media, various
textual, tabular and hierarchical data views, and integration with the
application through control panels, a command line and different
multi-threading models.Comment: Presented at the 2003 Computing in High Energy and Nuclear Physics
(CHEP03), La Jolla, Ca, USA, March 2003, 6 pages LaTeX, 4 eps figures. PSN
MOLT008 More and higher res figs at
http://iguana.web.cern.ch/iguana/snapshot/main/gallery.htm
Towards a framework for investigating tangible environments for learning
External representations have been shown to play a key role in mediating cognition. Tangible environments offer the opportunity for novel representational formats and combinations, potentially increasing representational power for supporting learning. However, we currently know little about the specific learning benefits of tangible environments, and have no established framework within which to analyse the ways that external representations work in tangible environments to support learning. Taking external representation as the central focus, this paper proposes a framework for investigating the effect of tangible technologies on interaction and cognition. Key artefact-action-representation relationships are identified, and classified to form a structure for investigating the differential cognitive effects of these features. An example scenario from our current research is presented to illustrate how the framework can be used as a method for investigating the effectiveness of differential designs for supporting science learning
Context-adaptive learning designs by using semantic web services
IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources - whether data or services - within the learning design is done manually at design-time on the basis of the subjective appraisals of a learning designer. Since the actual learning context is known at runtime only, IMS-LD applications cannot adapt to a specific context or learner. Therefore, the reusability is limited and high development costs have to be taken into account to support a variety of contexts. To overcome these issues, we propose a highly dynamic approach based on Semantic Web Services (SWS) technology. Our aim is moving from the current data- and metadata-based to a context-adaptive service-orientated paradigm We introduce semantic descriptions of a learning process in terms of user objectives (learning goals) to abstract from any specific metadata standards and used learning resources. At runtime, learning goals are accomplished by automatically selecting and invoking the services that fit the actual user needs and process contexts. As a result, we obtain a dynamic adaptation to different contexts at runtime. Semantic mappings from our standard-independent process models will enable the automatic development of versatile, reusable IMS-LD applications as well as the reusability across multiple metadata standards. To illustrate our approach, we describe a prototype application based on our principles
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