Linked data-driven geographic mobile learning application

2015 ◽  
Author(s):  
Hendrik ◽  
Ade Rickyano Tri Hendratmo
Keyword(s):  
Mobile Learning ◽  
Linked Data ◽  
Data Driven

Linked Data-Driven Smart Spaces

2014 ◽  
pp. 3-15
Author(s):  
Oscar Rodríguez Rocha ◽  
Cristhian Figueroa ◽  
Iacopo Vagliano ◽  
Boris Moltchanov
Keyword(s):  
Linked Data ◽  
Data Driven ◽  
Smart Spaces

scholarly journals The roles of data management and analytics in industry 4.0 ecosystems

2020 ◽  
Author(s):  
Hendro Wicaksono
Keyword(s):  
Artificial Intelligence ◽  
Industry 4.0 ◽  
Linked Data ◽  
Data Analytics ◽  
Industrial Revolution ◽  
Data Driven ◽  
Knowledge Graph ◽  
Fourth Industrial Revolution ◽  
Global Access ◽  
Integration Data

The presentation introduces the technologies associated with the fourth industrial revolution which rely on the concept of artificial intelligence. Data is the basis of functioning artificial intelligence technologies. The presentation also explains how data can revolutionize the business by providing global access to physical products through an industry 4.0 ecosystem. The ecosystem contains four pillars: smart product, smart process, smart resources (smart PPR), and data-driven services. Through these four pillars, the industry 4.0 can be implemented in different sectors. The presentation also provides some insights on the roles of linked data (knowledge graph) for data integration, data analytics, and machine learning in industry 4.0 ecosystem. Project examples in smart city, healthcare, and agriculture sectors are also described. Finally, the presentation discusses the implications of the introduced concepts on the Indonesian context.

(Re)using resources for historical languages

2017 ◽  
Author(s):  
Gard B. Jenset ◽  
Barbara McGillivray
Keyword(s):  
Linked Data ◽  
Historical Linguistics ◽  
Research Process ◽  
Data Driven ◽  
Language Resources ◽  
Linguistic Resources ◽  
Worked Example ◽  
Basic Concepts ◽  
The Relationship

Chapter 5 covers the topic of language resources in historical linguistics. It explains the relationship between historical corpora and language resources in a data-driven framework, and refers to valency lexicons as an example. The chapter also points to resources external to the linguistics community, and shows how these can enrich the research process in historical linguistics. We explain the basic concepts of linked data, and argue for a more extensive linking of linguistic resources with other types of resources, including gazetteers and prosopographical data. We provide a worked example from the LexInfo ontology.

scholarly journals Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies

2022 ◽  
Vol 19 (2) ◽  
pp. 794
Author(s):  
Akeem Pedro ◽  
Anh-Tuan Pham-Hang ◽  
Phong Thanh Nguyen ◽  
Hai Chien Pham
Keyword(s):  
Information Sharing ◽  
Industry 4.0 ◽  
Linked Data ◽  
Data Science ◽  
Safety Information ◽  
Construction Safety ◽  
Lessons Learned ◽  
Data Driven ◽  
Knowledge Graph ◽  
Ontological Approach

Accident, injury, and fatality rates remain disproportionately high in the construction industry. Information from past mishaps provides an opportunity to acquire insights, gather lessons learned, and systematically improve safety outcomes. Advances in data science and industry 4.0 present new unprecedented opportunities for the industry to leverage, share, and reuse safety information more efficiently. However, potential benefits of information sharing are missed due to accident data being inconsistently formatted, non-machine-readable, and inaccessible. Hence, learning opportunities and insights cannot be captured and disseminated to proactively prevent accidents. To address these issues, a novel information sharing system is proposed utilizing linked data, ontologies, and knowledge graph technologies. An ontological approach is developed to semantically model safety information and formalize knowledge pertaining to accident cases. A multi-algorithmic approach is developed for automatically processing and converting accident case data to a resource description framework (RDF), and the SPARQL protocol is deployed to enable query functionalities. Trials and test scenarios utilizing a dataset of 200 real accident cases confirm the effectiveness and efficiency of the system in improving information access, retrieval, and reusability. The proposed development facilitates a new “open” information sharing paradigm with major implications for industry 4.0 and data-driven applications in construction safety management.

scholarly journals Centre for Health Record Linkage

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Katie Irvine ◽  
Rick Hall ◽  
Lee Taylor
Keyword(s):  
Record Linkage ◽  
Linked Data ◽  
Best Practice ◽  
Data Linkage ◽  
New South ◽  
Data Driven ◽  
Health Record ◽  
Data Governance ◽  
South Wales ◽  
Data Informed

ContextThe Centre for Health Record Linkage (CHeReL) was established in 2006 as a dedicated health and human services data linkage facility for two Australian jurisdictions, New South Wales and the geographically-nested Australian Capital Territory. The two jurisdictions have their own Governments and separate Health and Human Service systems. Purpose and OperationsThe primary purpose of the CHeReL is to make linked administrative and routinely collected healthdata available to researchers and government within relevant regulatory and governance frameworks.The CHeReL’s data governance and technical operations draw on international best practice andhave been refined by learnings from other data linkage centres. OutcomesOver twelve years of operation, more than 2,320 unique investigators from 140 institutions haveused the CHeReL, producing 615 publications in peer-reviewed literature. A robust pipeline of newdevelopment is expected to further amplify the use of linked data for cutting edge medical researchand support a vision of data-informed policy and data-driven government services.

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