13,717 research outputs found
Conditions, constraints and contracts: on the use of annotations for policy modeling.
Organisational policies express constraints on generation and processing of resources. However, application domains rely on transformation processes, which are in principle orthogonal to policy specifications and domain rules and policies may evolve in a non-synchronised way. In previous papers, we have proposed annotations as a flexible way to model aspects of some policy, and showed how they could be used to impose constraints on domain configurations, how to derive application conditions on transformations, and how to annotate complex patterns. We extend the approach by: allowing domain model elements to be annotated with collections of elements, which can be collectively applied to individual resources or collections thereof; proposing an original construction to solve the problem of annotations remaining orphan , when annotated resources are consumed; introducing a notion of contract, by which a policy imposes additional pre-conditions and post-conditions on rules for deriving new resources. We discuss a concrete case study of linguistic resources, annotated with information on the licenses under which they can be used. The annotation framework allows forms of reasoning such as identifying conflicts among licenses, enforcing the presence of licenses, or ruling out some modifications of a licence configuration
The Research Object Suite of Ontologies: Sharing and Exchanging Research Data and Methods on the Open Web
Research in life sciences is increasingly being conducted in a digital and
online environment. In particular, life scientists have been pioneers in
embracing new computational tools to conduct their investigations. To support
the sharing of digital objects produced during such research investigations, we
have witnessed in the last few years the emergence of specialized repositories,
e.g., DataVerse and FigShare. Such repositories provide users with the means to
share and publish datasets that were used or generated in research
investigations. While these repositories have proven their usefulness,
interpreting and reusing evidence for most research results is a challenging
task. Additional contextual descriptions are needed to understand how those
results were generated and/or the circumstances under which they were
concluded. Because of this, scientists are calling for models that go beyond
the publication of datasets to systematically capture the life cycle of
scientific investigations and provide a single entry point to access the
information about the hypothesis investigated, the datasets used, the
experiments carried out, the results of the experiments, the people involved in
the research, etc. In this paper we present the Research Object (RO) suite of
ontologies, which provide a structured container to encapsulate research data
and methods along with essential metadata descriptions. Research Objects are
portable units that enable the sharing, preservation, interpretation and reuse
of research investigation results. The ontologies we present have been designed
in the light of requirements that we gathered from life scientists. They have
been built upon existing popular vocabularies to facilitate interoperability.
Furthermore, we have developed tools to support the creation and sharing of
Research Objects, thereby promoting and facilitating their adoption.Comment: 20 page
EGO: a personalised multimedia management tool
The problems of Content-Based Image Retrieval (CBIR) sys- tems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces, and introduce our view on how to solve some of the problems of the studied interfaces. To address the semantic gap and long-term multifaceted information needs, we propose a "retrieval in context" system. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user's personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is detailed, which is based on relevance feedback techniques
Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach
Goals are first-class entities in a self-adaptive system (SAS) as they guide
the self-adaptation. A SAS often operates in dynamic and partially unknown
environments, which cause uncertainty that the SAS has to address to achieve
its goals. Moreover, besides the environment, other classes of uncertainty have
been identified. However, these various classes and their sources are not
systematically addressed by current approaches throughout the life cycle of the
SAS. In general, uncertainty typically makes the assurance provision of SAS
goals exclusively at design time not viable. This calls for an assurance
process that spans the whole life cycle of the SAS. In this work, we propose a
goal-oriented assurance process that supports taming different sources (within
different classes) of uncertainty from defining the goals at design time to
performing self-adaptation at runtime. Based on a goal model augmented with
uncertainty annotations, we automatically generate parametric symbolic formulae
with parameterized uncertainties at design time using symbolic model checking.
These formulae and the goal model guide the synthesis of adaptation policies by
engineers. At runtime, the generated formulae are evaluated to resolve the
uncertainty and to steer the self-adaptation using the policies. In this paper,
we focus on reliability and cost properties, for which we evaluate our approach
on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the
validation are promising and show that our approach is able to systematically
tame multiple classes of uncertainty, and that it is effective and efficient in
providing assurances for the goals of self-adaptive systems
A lightweight web video model with content and context descriptions for integration with linked data
The rapid increase of video data on the Web has warranted an urgent need for effective representation, management and retrieval of web videos. Recently, many studies have been carried out for ontological representation of videos, either using domain dependent or generic schemas such as MPEG-7, MPEG-4, and COMM. In spite of their extensive coverage and sound theoretical grounding, they are yet to be widely used by users. Two main possible reasons are the complexities involved and a lack of tool support. We propose a lightweight video content model for content-context description and integration. The uniqueness of the model is that it tries to model the emerging social context to describe and interpret the video. Our approach is grounded on exploiting easily extractable evolving contextual metadata and on the availability of existing data on the Web. This enables representational homogeneity and a firm basis for information integration among semantically-enabled data sources. The model uses many existing schemas to describe various ontology classes and shows the scope of interlinking with the Linked Data cloud
Valuing Knowledge Management Impact on Engineering Design Activities
Knowledge Management Systems (KMS) have been developed in Engineering Designactivities in order to improve the productivity of these activities. Nevertheless it is still verydifficult to identify the impact of such Systems on the Engineering Design Performance.In this paper our goal is to present why valuing Knowledge Management Impact onEngineering Design is today a challenge. In a first part we aim at presenting how and whyKnowledge Management has been introduced in Engineering Design Activities. By a reviewof the literature from a span of disciplines we will next focus on the different ways to valuethe impact of Knowledge Management Systems on firm activities. At least we will propose amethod to monitor the impact of Knowledge Management Systems on Engineering DesignActivities.Knowledge Management, research organisations, quality management
Living with the Semantic Gap: Experiences and remedies in the context of medical imaging
Semantic annotation of images is a key concern for the newly emerged applications of semantic multimedia. Machine processable descriptions of images make it possible to automate a variety of tasks from search and discovery to composition and collage of image data bases. However, the ever occurring problem of the semantic gap between the low level descriptors and the high level interpretation of an image poses new challenges and needs to be addressed before the full potential of semantic multimedia can be realised. We explore the possibilities and lessons learnt with applied semantic multimedia from our engagement with medical imaging where we deployed ontologies and a novel distributed architecture to provide semantic annotation, decision support and methods for tackling the semantic gap problem
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