11,773 research outputs found
Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains
Biomedical taxonomies, thesauri and ontologies in the form of the
International Classification of Diseases (ICD) as a taxonomy or the National
Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in
acquiring, representing and processing information about human health. With
increasing adoption and relevance, biomedical ontologies have also
significantly increased in size. For example, the 11th revision of the ICD,
which is currently under active development by the WHO contains nearly 50,000
classes representing a vast variety of different diseases and causes of death.
This evolution in terms of size was accompanied by an evolution in the way
ontologies are engineered. Because no single individual has the expertise to
develop such large-scale ontologies, ontology-engineering projects have evolved
from small-scale efforts involving just a few domain experts to large-scale
projects that require effective collaboration between dozens or even hundreds
of experts, practitioners and other stakeholders. Understanding how these
stakeholders collaborate will enable us to improve editing environments that
support such collaborations. We uncover how large ontology-engineering
projects, such as the ICD in its 11th revision, unfold by analyzing usage logs
of five different biomedical ontology-engineering projects of varying sizes and
scopes using Markov chains. We discover intriguing interaction patterns (e.g.,
which properties users subsequently change) that suggest that large
collaborative ontology-engineering projects are governed by a few general
principles that determine and drive development. From our analysis, we identify
commonalities and differences between different projects that have implications
for project managers, ontology editors, developers and contributors working on
collaborative ontology-engineering projects and tools in the biomedical domain.Comment: Published in the Journal of Biomedical Informatic
Graph-based discovery of ontology change patterns
Ontologies can support a variety of purposes, ranging from capturing conceptual knowledge to the organisation of digital content and information. However, information systems are always subject to change and ontology change management can pose challenges. We investigate ontology change representation and discovery of change patterns.
Ontology changes are formalised as graph-based change logs. We use attributed graphs, which are typed over a generic graph with node and edge attribution.We analyse ontology change logs, represented as graphs, and identify frequent change sequences. Such sequences are applied as a reference in order to discover reusable, often domain-specific and usagedriven change patterns. We describe the pattern discovery algorithms and measure their performance using experimental result
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Models for Learning (Mod4L) Final Report: Representing Learning Designs
The Mod4L Models of Practice project is part of the JISC-funded Design for Learning Programme. It ran from 1 May – 31 December 2006. The philosophy underlying the project was that a general split is evident in the e-learning community between development of e-learning tools, services and standards, and research into how teachers can use these most effectively, and is impeding uptake of new tools and methods by teachers. To help overcome this barrier and bridge the gap, a need is felt for practitioner-focused resources which describe a range of learning designs and offer guidance on how these may be chosen and applied, how they can support effective practice in design for learning, and how they can support the development of effective tools, standards and systems with a learning design capability (see, for example, Griffiths and Blat 2005, JISC 2006). Practice models, it was suggested, were such a resource.
The aim of the project was to: develop a range of practice models that could be used by practitioners in real life contexts and have a high impact on improving teaching and learning practice.
We worked with two definitions of practice models. Practice models are:
1. generic approaches to the structuring and orchestration of learning activities. They express elements of pedagogic principle and allow practitioners to make informed choices (JISC 2006)
However, however effective a learning design may be, it can only be shared with others through a representation. The issue of representation of learning designs is, then, central to the concept of sharing and reuse at the heart of JISC’s Design for Learning programme. Thus practice models should be both representations of effective practice, and effective representations of practice. Hence we arrived at the project working definition of practice models as:
2. Common, but decontextualised, learning designs that are represented in a way that is usable by practitioners (teachers, managers, etc).(Mod4L working definition, Falconer & Littlejohn 2006).
A learning design is defined as the outcome of the process of designing, planning and orchestrating learning activities as part of a learning session or programme (JISC 2006).
Practice models have many potential uses: they describe a range of learning designs that are found to be effective, and offer guidance on their use; they support sharing, reuse and adaptation of learning designs by teachers, and also the development of tools, standards and systems for planning, editing and running the designs.
The project took a practitioner-centred approach, working in close collaboration with a focus group of 12 teachers recruited across a range of disciplines and from both FE and HE. Focus group members are listed in Appendix 1. Information was gathered from the focus group through two face to face workshops, and through their contributions to discussions on the project wiki. This was supplemented by an activity at a JISC pedagogy experts meeting in October 2006, and a part workshop at ALT-C in September 2006. The project interim report of August 2006 contained the outcomes of the first workshop (Falconer and Littlejohn, 2006).
The current report refines the discussion of issues of representing learning designs for sharing and reuse evidenced in the interim report and highlights problems with the concept of practice models (section 2), characterises the requirements teachers have of effective representations (section 3), evaluates a number of types of representation against these requirements (section 4), explores the more technically focused role of sequencing representations and controlled vocabularies (sections 5 & 6), documents some generic learning designs (section 8.2) and suggests ways forward for bridging the gap between teachers and developers (section 2.6).
All quotations are taken from the Mod4L wiki unless otherwise stated
A new technique for intelligent web personal recommendation
Personal recommendation systems nowadays are very important in web applications
because of the available huge volume of information on the World Wide Web, and the
necessity to save users’ time, and provide appropriate desired information, knowledge,
items, etc. The most popular recommendation systems are collaborative filtering systems,
which suffer from certain problems such as cold-start, privacy, user identification, and
scalability. In this thesis, we suggest a new method to solve the cold start problem taking
into consideration the privacy issue. The method is shown to perform very well in
comparison with alternative methods, while having better properties regarding user privacy.
The cold start problem covers the situation when recommendation systems have not
sufficient information about a new user’s preferences (the user cold start problem), as well
as the case of newly added items to the system (the item cold start problem), in which case
the system will not be able to provide recommendations. Some systems use users’
demographical data as a basis for generating recommendations in such cases (e.g. the
Triadic Aspect method), but this solves only the user cold start problem and enforces user’s
privacy. Some systems use users’ ’stereotypes’ to generate recommendations, but
stereotypes often do not reflect the actual preferences of individual users. While some other
systems use user’s ’filterbots’ by injecting pseudo users or bots into the system and consider
these as existing ones, but this leads to poor accuracy.
We propose the active node method, that uses previous and recent users’ browsing targets
and browsing patterns to infer preferences and generate recommendations (node
recommendations, in which a single suggestion is given, and batch recommendations, in
which a set of possible target nodes are shown to the user at once). We compare the active
node method with three alternative methods (Triadic Aspect Method, Naïve Filterbots
Method, and MediaScout Stereotype Method), and we used a dataset collected from online
web news to generate recommendations based on our method and based on the three
alternative methods. We calculated the levels of novelty, coverage, and precision in these
experiments, and we found that our method achieves higher levels of novelty in batch
recommendation while achieving higher levels of coverage and precision in node
recommendations comparing to these alternative methods. Further, we develop a variant of
the active node method that incorporates semantic structure elements. A further
experimental evaluation with real data and users showed that semantic node
recommendation with the active node method achieved higher levels of novelty than nonsemantic
node recommendation, and semantic-batch recommendation achieved higher levels
of coverage and precision than non-semantic batch recommendation
Implementing 5D BIM on construction projects: Contractor perspectives from the UK construction sector
This is an accepted manuscript of an article published by Emerald in Journal of Engineering, Design and Technology on 09/05/2020: https://doi.org/10.1108/JEDT-01-2020-0007
The accepted version of the publication may differ from the final published version.Purpose
The purpose of this paper is to report on primary research findings that sought to investigate and analyse salient issues on the implementation of 5D building information modelling (BIM) from the UK contractors’ perspective. Previous research and efforts have predominantly focussed on the use of technologies for cost estimation and quantity takeoff within a more traditional-led procurement, with a paucity of research focussing on how 5D BIM could facilitate costing within contractor-led procurement. This study fills this current knowledge gap and enhances the understanding of the specific costing challenges faced by contractors in contractor-led projects, leading to the development of 5D framework for use in future projects.
Design/methodology/approach
To develop a fully detailed understanding of the challenges and issues being faced in this regard, a phenomenological, qualitative-based study was undertaken through interviews involving 21 participants from UK-wide construction organisations. A thematic data analytical process was applied to the data to derive key issues, and this was then used to inform the development of a 5D-BIM costing framework.
Findings
Multi-disciplinary findings reveal a range of issues faced by contractors when implementing 5D BIM. These exist at strategic, operational and technological levels which require addressing successful implementation of 5D BIM on contractor-led projects adhering to Level 2 BIM standards. These findings cut across the range of stakeholders on contractor-led projects. Ultimately, the findings suggest strong commitment and leadership from organisational management are required to facilitate cost savings and generate accurate cost information.
Practical implications
This study highlights key issues for any party seeking to effectively deploy 5D BIM on a contractor-led construction project. A considerable cultural shift towards automating and digitising cost functions virtually, stronger collaborative working relationship relative to costing in design development, construction practice, maintenance and operation is required.
Originality/value
By analysing findings from primary research data, the work concludes with the development of a 5D BIM costing framework to support contractor-led projects which can be implemented to ensure that 5D BIM is successfully implemented
Knowledge Representation with Ontologies: The Present and Future
Recently, we have seen an explosion of interest in ontologies as
artifacts to represent human knowledge and as critical components in
knowledge management, the semantic Web, business-to-business
applications, and several other application areas. Various research
communities commonly assume that ontologies are the appropriate modeling
structure for representing knowledge. However, little discussion has
occurred regarding the actual range of knowledge an ontology can
successfully represent
The future of technology enhanced active learning – a roadmap
The notion of active learning refers to the active involvement of learner in the learning process,
capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap,
the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a
best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap
Learning and Activity Patterns in OSS Communities and their Impact on Software Quality
This paper presents a framework to identify and analyse learning and activity patterns that characterise participation and collaboration of individuals in Open Source Software (OSS) communities. It first describes how participants’ activities enable and drive a learning process that occurs in individual participants as well as in the OSS project community as a whole. It then explores how to identify and analyse learning patterns at both individual level and community level. The objective of such analysis is to determine the impact of these patterns on the quality of the OSS product and define a descriptive approach to quality that is concerned less with standards than with the facts of OSS peer-review and peer-production
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