43,671 research outputs found
A Machine Learning Based Analytical Framework for Semantic Annotation Requirements
The Semantic Web is an extension of the current web in which information is
given well-defined meaning. The perspective of Semantic Web is to promote the
quality and intelligence of the current web by changing its contents into
machine understandable form. Therefore, semantic level information is one of
the cornerstones of the Semantic Web. The process of adding semantic metadata
to web resources is called Semantic Annotation. There are many obstacles
against the Semantic Annotation, such as multilinguality, scalability, and
issues which are related to diversity and inconsistency in content of different
web pages. Due to the wide range of domains and the dynamic environments that
the Semantic Annotation systems must be performed on, the problem of automating
annotation process is one of the significant challenges in this domain. To
overcome this problem, different machine learning approaches such as supervised
learning, unsupervised learning and more recent ones like, semi-supervised
learning and active learning have been utilized. In this paper we present an
inclusive layered classification of Semantic Annotation challenges and discuss
the most important issues in this field. Also, we review and analyze machine
learning applications for solving semantic annotation problems. For this goal,
the article tries to closely study and categorize related researches for better
understanding and to reach a framework that can map machine learning techniques
into the Semantic Annotation challenges and requirements
Semantic web learning technology design: addressing pedagogical challenges and precarious futures
Semantic web technologies have the potential to extend and transform teaching and learning, particularly in those educational settings in which learners are encouraged to engage with âauthenticâ data from multiple sources. In the course of the âEnsembleâ project, teachers and learners in different disciplinary contexts in UK Higher Education worked with educational researchers and technologists to explore the potential of such technologies through participatory design and rapid prototyping. These activities exposed some of the barriers to the development and adoption of emergent learning technologies, but also highlighted the wide range of factors, not all of them technological or pedagogical, that might contribute to enthusiasm for and adoption of such technologies. This suggests that the scope and purpose of research and design activities may need to be broadened and the paper concludes with a discussion of how the tradition of operaismo or âworkersâ enquiryâ may help to frame such activities. This is particularly relevant in a period when the both educational institutions and the working environments for which learners are being prepared are becoming increasingly fractured, and some measure of âprecarityâ is increasingly the norm
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STELLAR (Semantic Technologies Enhancing the Lifecycle of Learning Resources): Jisc Final Report
[Project Summary]
As one of the earliest distance learning providers The Open University (OU) has a rich heritage of archived learning materials. An ever increasing amount of that is in digital form and is being deposited with the University Archive. This growth has been driven by digitisation activity from projects such as AVA (Access to Video Assets) and the Fedora-based Open University Digital Library âa place to discover digital and digitised archival content from the OU Library, from videos and images to digitised documentsâ. Other digital content is being captured from web archiving activities, such as work to preserve Moodle Virtual Learning Environment course websites. An evidence based understanding is required to inform digital preservation policies, curation strategy and investment in digital library development.
Following the Pre-enhancement, Enhancement and Post-enhancement methodology set out by Jisc, STELLAR adopted the model of a balanced scorecard to ascertain the value ascribed to the non-current learning materials. Four aspects were considered: Personal and professional perspectives of value; Value to the Higher Educational and academic communities; Value to internal processes and cultures; Financial perspectives of value. The outcomes of the survey indicated that stakeholders place a high value on the materials, and that they perceived them to have value in all areas evaluated.
Three OU courses were chosen from the digital library for the transformation stage. These materials were enhanced and transformed into RDF, a process that required more extensive metadata expertise and effort than was expected. Following enhancement the RDF was accessed through a tool called DiscOU, created by a member of the project team from the OUâs Knowledge Media Institute. DiscOU uses both linked data and a semantic meaning engine to analyse the meaning of the text in a search query. This is matched against the meaning of the content derived from an index of the full-text of the digital library content.
In the final stage stakeholders were asked through a survey and series of workshops to use the DiscOU proof-of-concept tool to assess their perception of the value of this transformation. This has revealed that overall, academics and other stakeholders in the university do believe that the value of the selected materials was positively impacted by the application of semantic technologies
LODE: Linking Digital Humanities Content to the Web of Data
Numerous digital humanities projects maintain their data collections in the
form of text, images, and metadata. While data may be stored in many formats,
from plain text to XML to relational databases, the use of the resource
description framework (RDF) as a standardized representation has gained
considerable traction during the last five years. Almost every digital
humanities meeting has at least one session concerned with the topic of digital
humanities, RDF, and linked data. While most existing work in linked data has
focused on improving algorithms for entity matching, the aim of the
LinkedHumanities project is to build digital humanities tools that work "out of
the box," enabling their use by humanities scholars, computer scientists,
librarians, and information scientists alike. With this paper, we report on the
Linked Open Data Enhancer (LODE) framework developed as part of the
LinkedHumanities project. With LODE we support non-technical users to enrich a
local RDF repository with high-quality data from the Linked Open Data cloud.
LODE links and enhances the local RDF repository without compromising the
quality of the data. In particular, LODE supports the user in the enhancement
and linking process by providing intuitive user-interfaces and by suggesting
high-quality linking candidates using tailored matching algorithms. We hope
that the LODE framework will be useful to digital humanities scholars
complementing other digital humanities tools
Knowledge web: realising the semantic web... all the way to knowledge-enhanced multimedia documents
The semantic web and semantic web services are major efforts in order to spread and to integrate knowledge technology to the whole web. The Knowledge Web network of excellence aims at supporting their developments at the best and largest European level and supporting industry in adopting them. It especially investigates the solution of scalability, heterogeneity and dynamics obstacles to the full development of the semantic web. We explain how Knowledge Web results should benefit knowledge-enhanced multimedia applications
Metadata enrichment for digital heritage: users as co-creators
This paper espouses the concept of metadata enrichment through an expert and user-focused approach to metadata creation and management. To this end, it is argued the Web 2.0 paradigm enables users to be proactive metadata creators. As Shirky (2008, p.47) argues Web 2.0âs social tools enable âaction by loosely structured groups, operating without managerial direction and outside the profit motiveâ. Lagoze (2010, p. 37) advises, âthe participatory nature of Web 2.0 should not be dismissed as just a popular phenomenon [or fad]â. Carletti (2016) proposes a participatory digital cultural heritage approach where Web 2.0 approaches such as crowdsourcing can be sued to enrich digital cultural objects. It is argued that âheritage crowdsourcing, community-centred projects or other forms of public participationâ. On the other hand, the new collaborative approaches of Web 2.0 neither negate nor replace contemporary standards-based metadata approaches. Hence, this paper proposes a mixed metadata approach where user created metadata augments expert-created metadata and vice versa. The metadata creation process no longer remains to be the sole prerogative of the metadata expert. The Web 2.0 collaborative environment would now allow users to participate in both adding and re-using metadata. The case of expert-created (standards-based, top-down) and user-generated metadata (socially-constructed, bottom-up) approach to metadata are complementary rather than mutually-exclusive. The two approaches are often mistakenly considered as dichotomies, albeit incorrectly (Gruber, 2007; Wright, 2007) .
This paper espouses the importance of enriching digital information objects with descriptions pertaining the about-ness of information objects. Such richness and diversity of description, it is argued, could chiefly be achieved by involving users in the metadata creation process. This paper presents the importance of the paradigm of metadata enriching and metadata filtering for the cultural heritage domain. Metadata enriching states that a priori metadata that is instantiated and granularly structured by metadata experts is continually enriched through socially-constructed (post-hoc) metadata, whereby users are pro-actively engaged in co-creating metadata. The principle also states that metadata that is enriched is also contextually and semantically linked and openly accessible. In addition, metadata filtering states that metadata resulting from implementing the principle of enriching should be displayed for users in line with their needs and convenience. In both enriching and filtering, users should be considered as prosumers, resulting in what is called collective metadata intelligence
Taxonomies for Development
{Excerpt} Organizations spend millions of dollars on management systems without commensurate investments in the categorization needed to organize the information they rest on. Taxonomy work is strategic work: it enables efficient and interoperable retrieval and sharing of data, information, and knowledge by building needs and natural workflows in intuitive structures.
Bible readers think that taxonomy is the worldâs oldest profession. Whatever the case, the word is now synonymous with any hierarchical system of classification that orders domains of inquiry into groups and signifies natural relationships among these. (A taxonomic scheme is often depicted as a âtreeâ and individual taxonomic units as âbranchesâ in the tree.) Almost anything can be classified according to some taxonomic scheme. Resulting catalogs provide conceptual frameworks for miscellaneous purposes including knowledge identification, creation, storage, sharing, and use, including related decision making
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