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The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area.

An ontology for recommending learning material was integrated in the organizational learning environment based on ontology. An experiment was performed with 15 experts and 84 learners. Experts and learners were asked to classify 30 learning material related to Software Engineering area. The results obtained from experts and learners were compared with the ontology results.

Among 30 learning materials evaluated, 24 learning materials got closer to the expert classification using the ontology than using the learners’ manual classification. The learners had difficulties in correctly classifying the learning materials according to the knowledge area applied.

In an autonomous collaborative environment without a tutor responsible for organizing the learning materials shared by collaborators, an ontology may be an auxiliary mechanism to support automatic learning material classification. The proposed ontology uses recommendations given by the collaborators to get the correct knowledge area classification. The correct classification may support retrieval of appropriate learning materials according to the learners’ needs.

The purpose of this paper is to present a framework for integrating construction supply chain in order to resolve the data heterogeneity and data sharing problems in the construction industry.

Standardized web service technology is used in the proposed framework for data specification, transfer, and integration. Open standard SAWSDL is used to annotate web service descriptions with pointers to concepts defined in ontologies. NoSQL database Cassandra is used for distributed data storage among construction supply chain stakeholders.

Ontology can be used to support heterogeneous data transfer and integration through web services. Distributed data storage facilitates data sharing and enhances data control.

This paper presents examples of two ontologies for expressing construction supply chain information – ontology for material and ontology for purchase order. An example scenario is presented to demonstrate the proposed web service framework for material procurement process involving three parties, namely, project manager, contractor, and material supplier.

The use of web services is not new to construction supply chains (CSCs). However, it still faces problems in channelizing information along CSCs due to data heterogeneity. Trust issue is also a barrier to information sharing for integrating supply chains in a centralized collaboration system. In this paper, the authors present a web service framework, which facilitates storage and sharing of information on a distributed manner mediated through ontology-based web services. Security is enhanced with access control. A data model for the distributed databases is also presented for data storage and retrieval.

Matter is an important topic of science as a discipline since its inception. Nevertheless, along with the evolution of semantic web, matter has got equal importance among the ontology developers. The current work describes an ontology of matter that the authors developed in the lab. The purpose of this paper is to come up with an exhaustive list of concepts and relations to cover matter domain under one umbrella, after identifying the gaps in the present ontologies.

Ontology was developed following faceted analytico-synthetic approach of knowledge organization. The authors followed hybrid developmental approach which includes top-down as well as bottom-up development strategy, for creating classes and subclasses. The authors modelled matter domain comprehensively considering different aspects of matter. The theories behind the modelling approach helps to maintain the consistency of further extensions.

Final ontology has around 280 concepts and as many as 60 properties which include both object property and datatype property.

There exists very vague definition of concepts in different subject areas, as matter is a domain of study in physics, chemistry, material science, metallurgy, etc. Same material has been adopted differently depending upon purpose of its study/use in that field. For example aspirin is simply a chemical compound in chemistry, whereas in medicine it is also an agent.

Present work claims to influence the ontology engineers to develop more extension to this core ontology of matter (COMAT). Also this will find its use in information retrieval, semantic annotations and in several other semantic knowledge-based systems.

COMAT is the most recent work of the domain. Originality lies in the way matter domain has been looked up, from a very wide perspective, as well as in the approach of modelling the domain.

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science.

The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach.

The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies.

To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.

With the increasing spread of ontologies in various domains, units have gradually become an essential part of ontologies and units ontologies have been developed to offer a better expression ability for the practical usage. From the perspectives of architecture, comparison and reuse, the purpose of this paper is to provide a comprehensive survey on four mainstream units ontologies: quantity-unit-dimension-type, quantities, units, dimensions and values, ontology of units of measure and units ontology (UO) of the open biomedical ontologies, in order to address well the state of the art and the reuse strategies of the UO.

An architecture of units ontologies is presented, in which the relations between key factors (i.e. units of measure, quantity and dimension) are discussed. The criteria for comparing units ontologies are developed from the perspectives of organizational structure, pattern design and application scenario. Then, the authors compare four typical units ontologies based on the proposed comparison criteria. Furthermore, how to reuse these units ontologies is discussed in materials science domain by utilizing two reuse strategies of partial reference and complete reference.

Units ontologies have attracted high attention in the scientific domain. Based on the comparison of four popular units ontologies, this paper finds that different units ontologies have different design features from the perspectives of basis structure, units conversion and axioms design; a UO is better to be applied to the application areas that satisfy its design features; and many challenges remain to be done in the future research of the UO.

This paper makes an extensive review on units ontologies, by defining the comparison criteria and discussing the reuse strategies in the materials domain. Based on this investigation, guidelines are summarized for the selection and reuse of units ontologies.

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

The integration and retrieval of the vast data have attracted sufficient attention, thus the W3C workgroup releases R2RML to standardize the transformation from relational data to semantic-aware data. However, it only provides a data transform mechanism to resource description framework (RDF). The generation of mapping alignments still needs manual work or other algorithms. Therefore, the purpose of this paper is to propose a domain-oriented automatic mapping method and an application of the R2RML standard.

In this paper, materials science is focussed to show an example of domain-oriented mapping. source field concept and M3B2 (Metal Materials Mapping Background Base) knowledge bases are established to support the auto-recommending algorithm. As for the generation of RDF files, the idea is to generate the triples and the links, respectively. The links of the triples follow the object-subject relationship, and the links of the object properties can be achieved by the range individuals and the trail path.

Consequently based on the previous work, the authors proposed Engine for Metal Materials Mapping Background Base (EM3B2), a semantic integration engine for materials science. EM3B2 not only offers friendly graphical interfaces, but also provides auto-recommending mapping based on materials knowledge to enable users to avoid vast manually work. The experimental result indicates that EM3B2 supplies accurate mapping. Moreover, the running time of E3MB2 is also competitive as classical methods.

This paper proposed EM3B2 semantic integration engine, which contributes to the relational database-to-RDF mapping by the application of W3C R2RML standard and the domain-oriented mapping.

On Justification: Economies of Worth (Boltanski & Thévenot, 1991/2006) was a synthetic and comprehensive parsing of common goods, goods that could and had to be justified in public. In response to Bourdieu’s critical sociology, they rather provided a robust and disciplined sociology of critique, the situated requirements of justification. They refused power and violence as integral to the operability of justification. They emphasized the ways in which conventions of worth afforded coordination, not their constitution of or by domination. They refused to make either capitalism, or the state, into primary motors of social order. Indeed, they refused social sphere, structure, or group as the ground of the good. They emphasized the cognitive capacities of agents. There was no passion, no desire, no bodily affect in these justified worlds. There wasn’t even any account of production of value, of children, or of money. And while they recognized the metaphysical aspect of the good and even used Christianity as a template for one of their cités, they rigorously excluded religion. The theory was designed to analyze moments of controversy, not quiescence or quietude. In his subsequent work, Boltanski aimed to address these absences. In this essay, we examine how Boltanski sought to restore love, violence, religion, production, and institution across five texts: Love and Justice as Competences (1990/2012), The New Spirit of Capitalism, co-authored with Eve Chiapello (1999/2007), The Foetal Condition: A Sociology of Engendering and Abortion (2004/2013), On Critique: A Sociology of Emancipation (2009/2011), and La «Collection», Une Forme Neuve du Capitalisme – La Mise en Valeur Economique du Passé et ses Effets (2014) co-authored with Arnaud Esquerre.

Online encyclopedia has facilitated users to easily access interesting knowledge and find solutions for daily problems. However, for the staff in specific domains, especially in secret-related domains, a domain-micropedia is still necessary for work.

In this paper, the authors propose an approach to extract entities from DBpedia and construct the SDPedia in space debris mitigation domain. First, the authors select the root categories about space debris mitigation domain by manual methods. Subsequently, the authors propose Distance of Electrical Resistance, Pages Common Words and AVDP algorithms to implement the extraction. The authors also achieve the data visualization by generating swf files and embedding them into web pages.

In the experiments, the precision, recall and F1-measure are used to evaluate the proposed algorithms. The authors set a series of thresholds to pursue the highest F1-measure. The experimental data indicate that the AVDP algorithm gets the highest F1-measure and is statistically effective for the entities extraction from DBpedia.

The authors propose an approach of deriving linked data from DBpedia and construct their own SDPedia, which has been applied in the space debris mitigation domain currently. Compared with DBpedia, the authors also add the linked data visualization. Moreover, the methodology can be used in many other domains in the future.

This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.

The ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-making

(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.

It cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.

As portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.

By counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.

The goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.