scholarly journals Knowledge Representation and Management: a Linked Data Perspective

2016 ◽  
Vol 25 (01) ◽  
pp. 178-183 ◽  
Author(s):  
M. Barros ◽  
F.M. Couto
Keyword(s):  
Knowledge Representation ◽  
Linked Data ◽  
Health Sciences ◽  
Current Status ◽  
Strong Impact ◽  
Biomedical Data ◽  
Biomedical Ontologies ◽  
Semantic Web Technologies ◽  
Data Intensive ◽  
Data Elements

Summary Introduction: Biomedical research is increasingly becoming a data-intensive science in several areas, where prodigious amounts of data is being generated that has to be stored, integrated, shared and analyzed. In an effort to improve the accessibility of data and knowledge, the Linked Data initiative proposed a well-defined set of recommendations for exposing, sharing and integrating data, information and knowledge, using semantic web technologies. Objective: The main goal of this paper is to identify the current status and future trends of knowledge representation and management in Life and Health Sciences, mostly with regard to linked data technologies. Methods: We selected three prominent linked data studies, namely Bio2RDF, Open PHACTS and EBI RDF platform, and selected 14 studies published after 2014 (inclusive) that cited any of the three studies. We manually analyzed these 14 papers in relation to how they use linked data techniques. Results: The analyses show a tendency to use linked data techniques in Life and Health Sciences, and even if some studies do not follow all of the recommendations, many of them already represent and manage their knowledge using RDF and biomedical ontologies. Conclusion: These insights from RDF and biomedical ontologies are having a strong impact on how knowledge is generated from biomedical data, by making data elements increasingly connected and by providing a better description of their semantics. As health institutes become more data centric, we believe that the adoption of linked data techniques will continue to grow and be an effective solution to knowledge representation and management.

scholarly journals Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective

2019 ◽  
Vol 28 (01) ◽  
pp. 140-151 ◽  
Author(s):  
Jonathan P. Bona ◽  
Fred W. Prior ◽  
Meredith N. Zozus ◽  
Mathias Brochhausen
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Clinical Research ◽  
Data Management ◽  
Clinical Data ◽  
Research Data ◽  
Biomedical Ontologies ◽  
One To One ◽  
Data Elements ◽  
Clinical Research Data

Objectives: There exists a communication gap between the biomedical informatics community on one side and the computer science/artificial intelligence community on the other side regarding the meaning of the terms “semantic integration" and “knowledge representation“. This gap leads to approaches that attempt to provide one-to-one mappings between data elements and biomedical ontologies. Our aim is to clarify the representational differences between traditional data management and semantic-web-based data management by providing use cases of clinical data and clinical research data re-representation. We discuss how and why one-to-one mappings limit the advantages of using Semantic Web Technologies (SWTs). Methods: We employ commonly used SWTs, such as Resource Description Framework (RDF) and Ontology Web Language (OWL). We reuse pre-existing ontologies and ensure shared ontological commitment by selecting ontologies from a framework that fosters community-driven collaborative ontology development for biomedicine following the same set of principles. Results: We demonstrate the results of providing SWT-compliant re-representation of data elements from two independent projects managing clinical data and clinical research data. Our results show how one-to-one mappings would hinder the exploitation of the advantages provided by using SWT. Conclusions: We conclude that SWT-compliant re-representation is an indispensable step, if using the full potential of SWT is the goal. Rather than providing one-to-one mappings, developers should provide documentation that links data elements to graph structures to specify the re-representation.

Enabling the Matchmaking of Organizations and Public Procurement Notices by Means of Linked Open Data

2013 ◽  
pp. 105-131 ◽  
Author(s):  
Jose María Alvarez Rodríguez ◽  
José Emilio Labra Gayo ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Public Procurement ◽  
Open Data ◽  
Specific Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Domain Specific ◽  
The Status ◽  
Financial Transactions

The aim of this chapter is to present a proposal and a case study to describe the information about organizations in a standard way using the Linked Data approach. Several models and ontologies have been provided in order to formalize the data, structure and behaviour of organizations. Nevertheless, these tries have not been fully accepted due to some factors: (1) missing pieces to define the status of the organization; (2) tangled parts to specify the structure (concepts and relations) between the elements of the organization; 3) lack of text properties, and other factors. These divergences imply a set of incomplete approaches to formalize data and information about organizations. Taking into account the current trends of applying semantic web technologies and linked data to formalize, aggregate, and share domain specific information, a new model for organizations taking advantage of these initiatives is required in order to overcome existing barriers and exploit the corporate information in a standard way. This work is especially relevant in some senses to: (1) unify existing models to provide a common specification; (2) apply semantic web technologies and the Linked Data approach; (3) provide access to the information via standard protocols, and (4) offer new services that can exploit this information to trace the evolution and behaviour of the organization over time. Finally, this work is interesting to improve the clarity and transparency of some scenarios in which organizations play a key role, like e-procurement, e-health, or financial transactions.

Customer Relationship Management as an Imperative for Academic Libraries

2015 ◽  
pp. 44-77
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Web Data Quality

2014 ◽  
Vol 10 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Amrapali Zaveri ◽  
Andrea Maurino ◽  
Laure-Berti Equille
Keyword(s):  
Semantic Web ◽  
Data Quality ◽  
Linked Data ◽  
Web Data ◽  
Semantic Web Technologies ◽  
Future Directions ◽  
Web Technologies ◽  
Current State ◽  
Web Of Data ◽  
The Web

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.

Linked Data as Integrating Technology for Industrial Data

2012 ◽  
Vol 3 (3) ◽  
pp. 40-52 ◽  
Author(s):  
Markus Graube ◽  
Johannes Pfeffer ◽  
Jens Ziegler ◽  
Leon Urbas
Keyword(s):  
Linked Data ◽  
Small And Medium Enterprises ◽  
Collaborative Work ◽  
Semantic Web Technologies ◽  
Industrial Data ◽  
Distributed Information ◽  
Web Technologies ◽  
Share Data ◽  
First Results ◽  
Medium Enterprises

In a globalised world the process industry faces challenges regarding data management. Rising demands for agility and rapid shortening of innovation cycles have lead to project-based collaborations. Highly specialised small and medium enterprises are forming “virtual companies” for their mutual benefit. However, today’s industrial data structures are very heterogeneous, complicating collaborative work and hindering the flow of data between stakeholders from different domains. Existing solutions are too rigid and potentially cumbersome. A broad gap still exists between the need of virtual companies to share data from mixed sources in a controlled way and the technologies available. The authors’ approach uses semantic web technologies to represent industrial data in a generic way. Major advantages in comparison to traditional approaches arise from the inherent merging abilities and the extensibility of Linked Data. Distributed information spaces from different domains can be condensed into an interlinked cloud. Existing data can be integrated either on-the-fly using appropriate adapters or by complete migration. Furthermore, operations from graph theory can be performed on the Linked Data networks to generate aggregated views. This article discusses a set of proven web technologies for cloud-driven industrial data sharing in virtual companies and presents first results.

scholarly journals Linking Educational Resources on Data Science

2019 ◽  
Vol 33 ◽  
pp. 9404-9409
Author(s):  
José Luis Ambite ◽  
Jonathan Gordon ◽  
Lily Fierro ◽  
Gully Burns ◽  
Joel Mathew
Keyword(s):  
Big Data ◽  
Linked Data ◽  
Data Science ◽  
Resource Discovery ◽  
Educational Resources ◽  
Machine Learning Techniques ◽  
Biomedical Data ◽  
Centers Of Excellence ◽  
Training Resources ◽  
The Web

The availability of massive datasets in genetics, neuroimaging, mobile health, and other subfields of biology and medicine promises new insights but also poses significant challenges. To realize the potential of big data in biomedicine, the National Institutes of Health launched the Big Data to Knowledge (BD2K) initiative, funding several centers of excellence in biomedical data analysis and a Training Coordinating Center (TCC) tasked with facilitating online and inperson training of biomedical researchers in data science. A major initiative of the BD2K TCC is to automatically identify, describe, and organize data science training resources available on the Web and provide personalized training paths for users. In this paper, we describe the construction of ERuDIte, the Educational Resource Discovery Index for Data Science, and its release as linked data. ERuDIte contains over 11,000 training resources including courses, video tutorials, conference talks, and other materials. The metadata for these resources is described uniformly using Schema.org. We use machine learning techniques to tag each resource with concepts from the Data Science Education Ontology, which we developed to further describe resource content. Finally, we map references to people and organizations in learning resources to entities in DBpedia, DBLP, and ORCID, embedding our collection in the web of linked data. We hope that ERuDIte will provide a framework to foster open linked educational resources on the Web.

Extraction, analysis and publication of bibliographical references within an institutional repository

2016 ◽  
Vol 34 (2) ◽  
pp. 259-267 ◽  
Author(s):  
Götz Hatop
Keyword(s):  
Semantic Web ◽  
Citation Analysis ◽  
Open Source Software ◽  
Linked Data ◽  
Software Components ◽  
Institutional Repository ◽  
Semantic Web Technologies ◽  
Content Type ◽  
Web Technologies ◽  
Reference Information

Purpose – The academic tradition of adding a reference section with references to cited and otherwise related academic material to an article provides a natural starting point for finding links to other publications. These links can then be published as linked data. Natural language processing technologies are available today that can perform the task of bibliographical reference extraction from text. Publishing references by the means of semantic web technologies is a prerequisite for a broader study and analysis of citations and thus can help to improve academic communication in a general sense. The paper aims to discuss these issues. Design/methodology/approach – This paper examines the overall workflow required to extract, analyze and semantically publish bibliographical references within an Institutional Repository with the help of open source software components. Findings – A publication infrastructure where references are available for software agents would enable additional benefits like citation analysis, e.g. the collection of citations of a known paper and the investigation of citation sentiment.The publication of reference information as demonstrated in this article is possible with existing semantic web technologies based on established ontologies and open source software components. Research limitations/implications – Only a limited number of metadata extraction programs have been considered for performance evaluation and reference extraction was tested for journal articles only, whereas Institutional Repositories usually do contain a large number of other material like monographs. Also, citation analysis is in an experimental state and citation sentiment is currently not published at all. For future work, the problem of distributing reference information between repositories is an important problem that needs to be tackled. Originality/value – Publishing reference information as linked data are new within the academic publishing domain.

scholarly journals Six Challenges for Embodiment Research

2019 ◽  
Vol 28 (6) ◽  
pp. 593-599 ◽  
Author(s):  
Markus Ostarek ◽  
Falk Huettig
Keyword(s):  
Embodied Cognition ◽  
Language Comprehension ◽  
Current Status ◽  
Strong Impact ◽  
Affective States ◽  
Cognitive Sciences ◽  
Perceptual Symbols ◽  
Sensory Motor ◽  
Cognitive Revolution ◽  
Key Questions

Twenty years after Barsalou’s seminal perceptual-symbols article, embodied cognition, the notion that cognition involves simulations of sensory, motor, or affective states, has moved from an outlandish proposal to a mainstream position adopted by many researchers in the psychological and cognitive sciences (and neurosciences). Though it has generated productive work in the cognitive sciences as a whole, it has had a particularly strong impact on research into language comprehension. The view of a mental lexicon based on symbolic word representations, which are arbitrarily linked to sensory aspects of their referents, was generally accepted since the cognitive revolution in the 1950s. This has radically changed. Given the current status of embodiment as a main theory of cognition, it is somewhat surprising that a close look at the literature reveals that the debate about the nature of the processes involved in language comprehension is far from settled, and key questions remain unanswered. We present several suggestions for a productive way forward.

scholarly journals Thedlvhexsystem for knowledge representation: recent advances (system description)

2016 ◽  
Vol 16 (5-6) ◽  
pp. 866-883 ◽  
Author(s):  
CHRISTOPH REDL
Keyword(s):  
Knowledge Representation ◽  
Real World ◽  
Answer Set Programming ◽  
Current Status ◽  
System Description ◽  
Recent Advances ◽  
Real World Applications ◽  
External Sources ◽  
Answer Set

AbstractThedlvhexsystem implements thehex-semantics, which integrates answer set programming (ASP) with arbitrary external sources. Since its first release ten years ago, significant advancements were achieved. Most importantly, the exploitation of properties of external sources led to efficiency improvements and flexibility enhancements of the language, and technical improvements on the system side increased user's convenience. In this paper, we present the current status of the system and point out the most important recent enhancements over early versions. While existing literature focuses on theoretical aspects and specific components, a bird's eye view of the overall system is missing. In order to promote the system for real-world applications, we further present applications which were already successfully realized on top ofdlvhex.

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