26,597 research outputs found
Leveraging Semantic Web Service Descriptions for Validation by Automated Functional Testing
Recent years have seen the utilisation of Semantic Web Service descriptions for automating a wide range of service-related activities, with a primary focus on service discovery, composition, execution and mediation. An important area which so far has received less attention is service validation, whereby advertised services are proven to conform to required behavioural specifications. This paper proposes a method for validation of service-oriented systems through automated functional testing. The method leverages ontology-based and rule-based descriptions of service inputs, outputs, preconditions and effects (IOPE) for constructing a stateful EFSM specification. The specification is subsequently utilised for functional testing and validation using the proven Stream X-machine (SXM) testing methodology. Complete functional test sets are generated automatically at an abstract level and are then applied to concrete Web services, using test drivers created from the Web service descriptions. The testing method comes with completeness guarantees and provides a strong method for validating the behaviour of Web services
An experiment with ontology mapping using concept similarity
This paper describes a system for automatically mapping between concepts in different ontologies. The motivation for the research stems from the Diogene project, in which the project's own ontology covering the ICT domain is mapped to external ontologies, in order that their associated content can automatically be included in the Diogene system. An approach involving measuring the similarity of concepts is introduced, in which standard Information Retrieval indexing techniques are applied to concept descriptions. A matrix representing the similarity of concepts in two ontologies is generated, and a mapping is performed based on two parameters: the domain coverage of the ontologies, and their levels of granularity. Finally, some initial experimentation is presented which suggests that our approach meets the project's unique set of requirements
Interoperability in the OpenDreamKit Project: The Math-in-the-Middle Approach
OpenDreamKit --- "Open Digital Research Environment Toolkit for the
Advancement of Mathematics" --- is an H2020 EU Research Infrastructure project
that aims at supporting, over the period 2015--2019, the ecosystem of
open-source mathematical software systems. From that, OpenDreamKit will deliver
a flexible toolkit enabling research groups to set up Virtual Research
Environments, customised to meet the varied needs of research projects in pure
mathematics and applications.
An important step in the OpenDreamKit endeavor is to foster the
interoperability between a variety of systems, ranging from computer algebra
systems over mathematical databases to front-ends. This is the mission of the
integration work package (WP6). We report on experiments and future plans with
the \emph{Math-in-the-Middle} approach. This information architecture consists
in a central mathematical ontology that documents the domain and fixes a joint
vocabulary, combined with specifications of the functionalities of the various
systems. Interaction between systems can then be enriched by pivoting off this
information architecture.Comment: 15 pages, 7 figure
An ontology of agile aspect oriented software development
Both agile methods and aspect oriented programming (AOP) have emerged in recent years as new paradigms in software development. Both promise to free the process of building software systems from some of the constraints of more traditional approaches. As a software engineering approach on the one hand, and a software development tool on the other, there is the potential for them to be used in conjunction. However, thus far, there has been little interplay between the two. Nevertheless, there is some evidence that there may be untapped synergies that may be exploited, if the appropriate approach is taken to integrating AOP with agile methods. This paper takes an ontological approach to supporting this integration, proposing ontology enabled development based on an analysis of existing ontologies of aspect oriented programming, a proposed ontology of agile methods, and a derived ontology of agile aspect oriented development
Implementing feedback in creative systems : a workshop approach
One particular challenge in AI is the computational modelling and simulation of creativity. Feedback and learning from experience are key aspects of the creative process. Here we investigate how we could implement feedback in creative systems using a social model. From the field of creative writing we borrow the concept of a Writers Workshop as a model for learning through feedback. The Writers Workshop encourages examination, discussion and debates of a piece of creative work using a prescribed format of activities. We propose a computational model of the Writers Workshop as a roadmap for incorporation of feedback in artificial creativity systems. We argue that the Writers Workshop setting describes the anatomy of the creative process. We support our claim with a case study that describes how to implement the Writers Workshop model in a computational creativity system. We present this work using patterns other people can follow to implement similar designs in their own systems. We conclude by discussing the broader relevance of this model to other aspects of AI
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
Towards an Interaction-based Integration of MKM Services into End-User Applications
The Semantic Alliance (SAlly) Framework, first presented at MKM 2012, allows
integration of Mathematical Knowledge Management services into typical
applications and end-user workflows. From an architecture allowing invasion of
spreadsheet programs, it grew into a middle-ware connecting spreadsheet, CAD,
text and image processing environments with MKM services. The architecture
presented in the original paper proved to be quite resilient as it is still
used today with only minor changes.
This paper explores extensibility challenges we have encountered in the
process of developing new services and maintaining the plugins invading
end-user applications. After an analysis of the underlying problems, I present
an augmented version of the SAlly architecture that addresses these issues and
opens new opportunities for document type agnostic MKM services.Comment: 14 pages, 7 figure
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