919 research outputs found
Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review
Since the Simple Knowledge Organization System (SKOS) specification and its
SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a
significant number of conventional knowledge organization systems (KOS)
(including thesauri, classification schemes, name authorities, and lists of
codes and terms, produced before the arrival of the ontology-wave) have made
their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS"
as an umbrella term to refer to all of the value vocabularies and lightweight
ontologies within the Semantic Web framework. The paper provides an overview of
what the LOD KOS movement has brought to various communities and users. These
are not limited to the colonies of the value vocabulary constructors and
providers, nor the catalogers and indexers who have a long history of applying
the vocabularies to their products. The LOD dataset producers and LOD service
providers, the information architects and interface designers, and researchers
in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper
examines a set of the collected cases (experimental or in real applications)
and aims to find the usages of LOD KOS in order to share the practices and
ideas among communities and users. Through the viewpoints of a number of
different user groups, the functions of LOD KOS are examined from multiple
dimensions. This paper focuses on the LOD dataset producers, vocabulary
producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on
Digital Librarie
GI Systems for public health with an ontology based approach
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Health is an indispensable attribute of human life. In modern age,
utilizing technologies for health is one of the emergent concepts in
several applied fields. Computer science, (geographic) information
systems are some of the interdisciplinary fields which motivates this
thesis.
Inspiring idea of the study is originated from a rhetorical disease
DbHd: Database Hugging Disorder, defined by Hans Rosling at
World Bank Open Data speech in May 2010. The cure of this disease
can be offered as linked open data, which contains ontologies for
health science, diseases, genes, drugs, GEO species etc. LOD-Linked
Open Data provides the systematic application of information by
publishing and connecting structured data on the Web.
In the context of this study we aimed to reduce boundaries
between semantic web and geo web. For this reason a use case data is
studied from Valencia CSISP- Research Center of Public Health in
which the mortality rates for particular diseases are represented
spatio-temporally. Use case data is divided into three conceptual
domains (health, spatial, statistical), enhanced with semantic relations
and descriptions by following Linked Data Principles. Finally in order
to convey complex health-related information, we offer an
infrastructure integrating geo web and semantic web. Based on the
established outcome, user access methods are introduced and future
researches/studies are outlined
A Survey on Linked Data and the Social Web as facilitators for TEL recommender systems
Personalisation, adaptation and recommendation are central features
of TEL environments. In this context, information retrieval techniques are applied
as part of TEL recommender systems to filter and recommend learning resources
or peer learners according to user preferences and requirements. However,
the suitability and scope of possible recommendations is fundamentally
dependent on the quality and quantity of available data, for instance, metadata
about TEL resources as well as users. On the other hand, throughout the last
years, the Linked Data (LD) movement has succeeded to provide a vast body of
well-interlinked and publicly accessible Web data. This in particular includes
Linked Data of explicit or implicit educational nature. The potential of LD to
facilitate TEL recommender systems research and practice is discussed in this
paper. In particular, an overview of most relevant LD sources and techniques is
provided, together with a discussion of their potential for the TEL domain in
general and TEL recommender systems in particular. Results from highly related
European projects are presented and discussed together with an analysis of
prevailing challenges and preliminary solutions.LinkedU
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A linked data-driven & service-oriented architecture for sharing educational resources
The two fundamental aims of managing educational resources are to enable resources to be reusable and interoperable and to enable Web-scale sharing of resources across learning communities. Currently, a variety of approaches have been proposed to expose and manage educational resources and their metadata on the Web. These are usually based on heterogeneous metadata standards and schemas, such as IEEE LOM or ADL SCORM, and diverse repository interfaces such as OAI-PMH or SQI. Also, there is still a lack of usage of controlled vocabularies and available data sets that could replace the widespread use of unstructured text for describing resources. On the other hand, the Linked Data approach has proven that it offers a set of successful principles that have the potential to alleviate the aforementioned issues. In this paper, we introduce an architecture and prototype which is fundamentally based on (a) Linked Data principles and (b) Service-orientation to resolve the integration issues for sharing educational resources
Ontologies as bridges between data sources and user queries: the KNOWMAK project experience
This paper describes ongoing work in the KNOWMAK project, which aims to develop a webbased
tool providing interactive visualisations and state-of-the-art indicators on knowledge cocreation
in the European research area. One of the main novel developments in this work is the
use of ontologies to act as a bridge between the data sources (research projects, patents and
publications) and user queries, in order to address the problems of mapping between
heterogenous data sources with different vocabularies while still maintaining a level of
standardization necessary for summarising the information required to provide informative
views about the highly dynamic S&T landscape
Interlinking educational data to web of data
With the proliferation of educational data on the Web, publishing and interlinking eLearning resources have become an important issue nowadays. Educational resources are exposed under heterogeneous Intellectual Property Rights (IPRs) in different times and formats. Some resources are implicitly related to each other or to the interest, cultural and technical environment of learners. Linking educational resources to useful knowledge on the Web improves resource seeking. This becomes crucial for moving from current isolated eLearning repositories towards an open discovery space, including distributed resources irrespective of their geographic and system boundaries. Linking resources is also useful for enriching educational content, as it provides a richer context and other related information to both educators and learners. On the other hand, the emergence of the so-called "Linked Data" brings new opportunities for interconnecting different kinds of resources on the Web of Data. Using the Linked Data approach, data providers can publish structured data and establish typed links between them from various sources. To this aim, many tools, approaches and frameworks have been built to first expose the data as Linked Data formats and to second discover the similarities between entities in the datasets. The research carried out for this PhD thesis assesses the possibilities of applying the Linked Open Data paradigm to the enrichment of educational resources. Generally speaking, we discuss the interlinking educational objects and eLearning resources on the Web of Data focusing on existing schemas and tools. The main goals of this thesis are thus to cover the following aspects: -- Exposing the educational (meta)data schemas and particularly IEEE LOM as Linked Data -- Evaluating currently available interlinking tools in the Linked Data context -- Analyzing datasets in the Linked Open Data cloud, to discover appropriate datasets for interlinking -- Discussing the benefits of interlinking educational (meta)data in practice
Linked Data based Health Information Representation, Visualization and Retrieval System on the Semantic Web
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.To better facilitate health information dissemination, using flexible ways to
represent, query and visualize health data becomes increasingly important.
Semantic Web technologies, which provide a common framework by
allowing data to be shared and reused between applications, can be applied
to the management of health data. Linked open data - a new semantic web
standard to publish and link heterogonous data- allows not only human,
but also machine to brows data in unlimited way.
Through a use case of world health organization HIV data of sub Saharan
Africa - which is severely affected by HIV epidemic, this thesis built a
linked data based health information representation, querying and
visualization system. All the data was represented with RDF, by
interlinking it with other related datasets, which are already on the cloud.
Over all, the system have more than 21,000 triples with a SPARQL
endpoint; where users can download and use the data and – a SPARQL
query interface where users can put different type of query and retrieve the
result. Additionally, It has also a visualization interface where users can
visualize the SPARQL result with a tool of their preference. For users who
are not familiar with SPARQL queries, they can use the linked data search
engine interface to search and browse the data.
From this system we can depict that current linked open data technologies
have a big potential to represent heterogonous health data in a flexible and
reusable manner and they can serve in intelligent queries, which can
support decision-making. However, in order to get the best from these
technologies, improvements are needed both at the level of triple stores
performance and domain-specific ontological vocabularies
Using linked data for integrating educational medical web databases based on bioMedical ontologies
Open data are playing a vital role in different communities, including governments, businesses, and education. This revolution has had a high impact on the education field. Recently, Linked Data are being adopted for publishing and connecting data on the web by exposing and connecting data which were not previously linked.
In the context of education, applying Linked Data to the growing amount of open data used for learning is potentially highly beneficial. This paper proposes a system that tackles the challenges of data acquisition and integration from distributed web data sources into one linked dataset. The application domain of this work is medical education, and the focus is on integrating educational
content in the form of articles published in online educational libraries and Web 2.0 content that can be used for education. The process of integrating a collection of heterogeneous resources is to create links that connect the resources collected from distributed web data sources based on their semantics. The proposed system harvests metadata from distributed web sources and enriches it with concepts from
biomedical ontologies, such as SNOMED CT, that enable its linking. The final result of building this system is a linked dataset of more than 10,000 resources collected from PubMed Library, YouTube channels, and Blogging platforms. The final linked dataset is evaluated by developing information retrieval methods that exploit the SNOMED CT hierarchical relations for accessing and querying the dataset. Ontology-based browsing method has been developed for exploring the
dataset, and the browsing results have been clustered to evaluate its linkages. Furthermore, ontology-based query searching method has been developed and tested to enhance the discoverability of the data. The results were promising and had shown that using SNOMED CT for integrating distributed resources on the web is beneficial
Ontologies in the Time of Linked Data
This paper discusses some of the methodological issues one encounters when creating and using ontologies in the rapidly expanding Linked Open Data (LOD) landscape. Over the years the notion of applied ontologies has transitioned from that of a logically formalized knowledge system with varying degrees of inferencing power to that of a lightweight knowledge representation tool. This shift is reflected in the current lexicon where different actors in the LOD community use the term ontology interchangeably with more generic terms like vocabulary or even namespace or data schema. Applied ontologies have been a key area of research in the context of Semantic Web initiative since the late 1990s. The Semantic Web has recently found a new stream of development in the Linked Data initiative, which is considered its natural evolution (Allemang and Hendler, 2011). While a good deal of literature has been devoted to investigating ontology engineering for the Semantic Web, not enough attention has yet been paid to understanding the nature and role that ontologies play in the linked data context, especially from the lens of knowledge organization research. Based on our ongoing work creating Linked Open Data applications and services for digital resources in the domain of the performing arts, we describe methodological steps and lessons learned in line with the spirit of the linked data initiative, where an agile and pragmatic approach to development is combined with the practice of learning from one another
Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article
With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest in the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web
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