Towards linked open government data in Canada

Rajabi, Enayat

doi:10.1504/ijmso.2020.112802

Cited by 3 publications

(5 citation statements)

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“…The data dictionary or metadata of each NSOD dataset consists of information about that dataset, such as name, publisher, publication date, category, department, etc. which can be transformed to RDF using VoiD [13], DCMI [5] , DCAT [6] , and RDFS vocabularies. The observation of an NSOD dataset includes a collection of dimensions, measures and attributes.…”

Section: Data Modelmentioning

confidence: 99%

“…To the best of our knowledge, there are no existing ontologies to be re-used based on the nature of the NSOD dataset. However, we re-use a current data model for [5] https://dublincore.org [6] https://www.w3.org/TR/vocab-dcat-2/ [7] https://www.w3.org/TR/vocab-data-cube/…”

Section: Ontologymentioning

confidence: 99%

“…This study constructs a knowledge graph to connect various diseaserelated datasets in Nova Scotia Open Data (NSOD), a Canadian regional Open Data portal. There are 11 provinces and territories in Canada with approximately 11,771 published datasets in different domains ranging from "Business and Economy" to "Health and Wellness" in various formats (e.g., CSV, JSON, and Excel) [5]. Most open datasets do not allow users to export data in RDF format and are isolated while conceptually linked.…”

Section: Introductionmentioning

confidence: 99%

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Constructing a Knowledge Graph from OpenStatistical Data: The Case of Nova ScotiaDisease Datasets

Rajabi

Midha

Souza

2022

Preprint

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The majority of available datasets in open government dataare statistical. They are widely published by various governments to beused by the public and data consumers. However, most open data por-tals do not provide the five-star Linked Data standard datasets. Thepublished datasets are isolated from one another while conceptually con-nected. Through this paper, a knowledge graph is constructed for thedisease-related datasets of a Canadian government data portal, NovaScotia Open Data. We leverage the Semantic Web technologies to trans-form the disease-related datasets into the Resource Description Frame-work (RDF) standard and enrich them with semantic rules. An RDFdata model using the RDF Cube vocabulary is designed in this work todevelop the graph that adheres to best practices and standards, allowingfor expansion, modification and flexible re-use 3. The study also discussesthe lessons learned during the cross-dimensional knowledge graph con-struction and integrating open statistical datasets from multiple sources.

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Section: Data Modelmentioning

confidence: 99%

Section: Ontologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Constructing a Knowledge Graph from OpenStatistical Data: The Case of Nova ScotiaDisease Datasets

Rajabi

Midha

Souza

2022

Preprint

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“…At time of this research, there are 11 provinces and territories in Canada with approximately 11,771 published datasets in different domains ranging from “Business and Economy” to “Health and Wellness” in various formats (e.g., CSV, JSON, and Excel) [ 4 ]. Most open datasets do not allow users to export data in RDF; the data are isolated while semantically linked.…”

Section: Introductionmentioning

confidence: 99%

Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets

2023

Self Cite

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The majority of available datasets in open government data are statistical. They are widely published by various governments to be used by the public and data consumers. However, most open government data portals do not provide the five-star Linked Data standard datasets. The published datasets are isolated from one another while conceptually connected. This paper constructs a knowledge graph for the disease-related datasets of a Canadian government data portal, Nova Scotia Open Data. We leveraged the Semantic Web technologies to transform the disease-related datasets into Resource Description Framework (RDF) and enriched them with semantic rules. An RDF data model using the RDF Cube vocabulary was designed in this work to develop a graph that adheres to best practices and standards, allowing for expansion, modification and flexible re-use. The study also discusses the lessons learned during the cross-dimensional knowledge graph construction and integration of open statistical datasets from multiple sources.

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“…Linked data are defined a set of best practices for expressing, publishing, and connecting structured data by using semantic web technologies, and ontologies are complementary tools which serve as a foundation for linked data by allowing the modeling of concepts with semantic relationships [ 16 ]. Noteworthy applications of linked data can be found in governance, where the concept of linked open government data has been considered to support information transparency and innovative service development in various countries [ 17 , 18 , 19 ]. Similarly, the healthcare domain has also leveraged and benefited from linked data.…”

Section: Introductionmentioning

confidence: 99%

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

Pedro

Pham-Hang

Nguyen

et al. 2022

IJERPH

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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.

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Towards linked open government data in Canada

Cited by 3 publications

References 0 publications

Constructing a Knowledge Graph from OpenStatistical Data: The Case of Nova ScotiaDisease Datasets

Constructing a Knowledge Graph from OpenStatistical Data: The Case of Nova ScotiaDisease Datasets

Constructing a knowledge graph for open government data: the case of Nova Scotia disease datasets

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

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