ILastic: Linked Data Generation Workflow and User Interface for iMinds Scholarly Data

This article is a proof-of-concept case study to evaluate the functionality of a block metaphor–based linked data generator. In this work, we chose to produce linked data repository of recipes, which provide a medium for people to share their regional and healthy recipes with the masses. However, the same approach can also be adapted easily to other domains. Therefore, the applicability of our approach extends well beyond the food domain that we are considering in this article. As a medium for information sharing and understanding between heterogeneous systems, ontologies will play an important role in the realisation of the Internet of things (IoT) vision. Therefore, an ontology-based recipe repository would also be one of the basic blocks of a smart kitchen environment. However, building ontologies is a challenging task, especially for users who are not conversant in the ontology building languages. This article proposes an approach that can be used even by non-experts and facilitates the sharing and searching of recipe data. In our case, we exploit the features of the block paradigm to publish recipes in Linked Data format. In this way, users do not have to know the OWL (Web Ontology Language) syntax and the text input is kept minimal. As far as we know, this article is the first study that produces linked data using Blockly in the literature. We also conducted a user-based evaluation of the proposed approach using the System Usability Scale (SUS) questionnaire.

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Designing a Step-by-Step User Interface for Finding Provenance Information over Linked Data

Lecture Notes in Computer Science - Web Engineering ◽

10.1007/978-3-642-22233-7_36 ◽

2011 ◽

pp. 403-406 ◽

Cited By ~ 1

Author(s):

Enayat Rajabi ◽

Mohsen Kahani

Keyword(s):

User Interface ◽

Linked Data ◽

Provenance Information

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Linked Data Generation for the University Data From Legacy Database

International journal of Web & Semantic Technology ◽

10.5121/ijwest.2011.2302 ◽

2011 ◽

Vol 2 (3) ◽

pp. 21-31 ◽

Cited By ~ 5

Author(s):

Arup Sarkar ◽

Ujjal Marjit ◽

Utpal Biswas

Keyword(s):

Linked Data ◽

Data Generation ◽

The University

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Intelligent navigation of linked data with a graphical interface based on semantic similarity

the 5th International Conference on Virtual and Augmented Reality in Education ◽

10.46354/i3m.2019.vare.009 ◽

2019 ◽

Author(s):

Pedro Fonseca-Ortiz ◽

Hector G. Ceballos

Keyword(s):

User Interface ◽

Semantic Web ◽

Semantic Similarity ◽

Linked Data ◽

Recommendation System ◽

Web Applications ◽

Graphical Interface ◽

User Interest ◽

Specialized Knowledge ◽

Semantic Web Technology

"Semantic Web Technology proposes the use of linked data and ontologies as a mean for providing meaning to information. Even though several tools for the analysis and visualization of linked data exist, these tools require a lot of specialized knowledge to fulfill a purpose. Additionally, this complexity hardens its use for nonexperienced users therefore limiting semantic web applications. This paper describes a tool that combines the use of a recommendation system and an intuitive dynamic user interface for navigating linked data. The tool guides the user to find resources of interest by highlighting those related to his search intention. This is, the platform learns on the fly the user interest and makes recommendations based on the connections between resources."

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Sustainable Linked Data Generation: The Case of DBpedia

Lecture Notes in Computer Science - The Semantic Web – ISWC 2017 ◽

10.1007/978-3-319-68204-4_28 ◽

2017 ◽

pp. 297-313

Author(s):

Wouter Maroy ◽

Anastasia Dimou ◽

Dimitris Kontokostas ◽

Ben De Meester ◽

Ruben Verborgh ◽

...

Keyword(s):

Linked Data ◽

Data Generation

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A Linked Data Generation Method for Academic Conference Websites

Communications in Computer and Information Science - Natural Language Processing and Chinese Computing ◽

10.1007/978-3-642-34456-5_27 ◽

2012 ◽

pp. 296-307

Author(s):

Peng Wang ◽

Mingqi Zhou ◽

Xiang Zhang ◽

Fengbo Zhou

Keyword(s):

Linked Data ◽

Data Generation ◽

Academic Conference

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Polysemy and Synonymy Detection in Ontology Engineering

WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS ◽

10.37394/23209.2020.17.14 ◽

2020 ◽

Vol 17 ◽

Keyword(s):

Linked Data ◽

Semantic Analysis ◽

Ontology Engineering ◽

Data Generation ◽

Knowledge Domain ◽

Knowledge Resources ◽

Knowledge Domains ◽

Single Term ◽

Semantic Associations ◽

Value Decomposition

Polysemy, when a single term has multiple meanings, and synonymy, when multiple terms have the same meaning, are common phenomena in linguistics as well as in scientific knowledge. In ontology engineering, it is vital to detect the synonyms annotations and the multiple inheritances because of polysemy. The persistence of these issues in the semantic description of a knowledge domain causes problematic interoperability and data processing. The disambiguation of the entities, properties and relationships sense in a semantic web ontology significantly improves linked data generation and information retrieval. We explore the synonymy and polysemy in the setting of a cardiology terminology generated from textbooks on the basis of field coverage, professionals’ associations’ recommendations and bibliometrics, for the building of a cardiologic ontology. From 56,134 terms collected we found that 67.7% were unique. The indexed terms included single words, compound words and multi-word expressions. The frequency of their appearances in the combined master index was calculated and used as a marker of their significance. To cope with the linguistic polysemy and synonymy of terms, we examined them in WordNet, MeSH and BioPortal, as well as by latent semantic analysis (LSA) through singular value decomposition (SVD). Through these approaches we managed to identify and decipher semantic associations and relationships between the terms. We proposed a roadmap for ontology building from scratch by utilizing intrinsic and extrinsic knowledge resources and reuse of metadata. We anticipate that this approach is applicable in ontology engineering of different knowledge domains for relationships setting and linked data contextualization

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Guidelines for Linked Data generation and publication: An example in building energy consumption

Automation in Construction ◽

10.1016/j.autcon.2015.04.002 ◽

2015 ◽

Vol 57 ◽

pp. 178-187 ◽

Cited By ~ 28

Author(s):

Filip Radulovic ◽

María Poveda-Villalón ◽

Daniel Vila-Suero ◽

Víctor Rodríguez-Doncel ◽

Raúl García-Castro ◽

...

Keyword(s):

Energy Consumption ◽

Linked Data ◽

Building Energy ◽

Data Generation ◽

Building Energy Consumption

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BIM-linked data integration for asset management

Built Environment Project and Asset Management ◽

10.1108/bepam-11-2018-0136 ◽

2019 ◽

Vol 9 (4) ◽

pp. 489-502 ◽

Cited By ~ 3

Author(s):

Karim Farghaly ◽

F.H. Abanda ◽

Christos Vidalakis ◽

Graham Wood

Keyword(s):

Data Integration ◽

Asset Management ◽

Linked Data ◽

Data Generation ◽

Participatory Action ◽

Content Type ◽

Building Information ◽

Management Context ◽

Transfer Of Information ◽

Methodological Guidelines

Purpose The purpose of this paper is to investigate the transfer of information from the building information modelling (BIM) models to either conventional or advanced asset management platforms using Linked Data. To achieve this aim, a process for generating Linked Data in the asset management context and its integration with BIM data is presented. Design/methodology/approach The research design employs a participatory action research (PAR) approach. The PAR approach utilized two qualitative data collection methods, namely; focus group and interviews to identify and evaluate the required standards for the mapping of different domains. Also prototyping which is an approach of Software Development Methodology is utilized to develop the ontologies and Linked Data. Findings The proposed process offers a comprehensive description of the required standards and classifications in construction domain, related vocabularies and object-oriented links to ensure the effective data integration between different domains. Also the proposed process demonstrates the different stages, tools, best practices and guidelines to develop Linked Data, armed with a comprehensive use case Linked Data generation about building assets that consume energy. Originality/value The Linked Data generation and publications in the domain of AECO is still in its infancy and it also needs methodological guidelines to support its evolution towards maturity in its processes and applications. This research concentrates on the Linked Data applications with BIM to link across domains where few studies have been conducted.

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