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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.

The purpose of this paper is to construct diverse granules and coverings derived from a semi‐equivalence class and then to reveal the relationships between granules and coverings and even relations, and to help one to study pansystems relations in a trans‐cross view.

Forms regarding semi‐equivalence classes as primitives, blocks or granules such as tolerance class, join class, meet class, optimist/pessimist selected compatible class, and tolerantly kernel class in an incomplete information system are defined and compared. Different approximations are also introduced. Furthermore, diverse coverings are also suggested.

A tolerance class of an object is proved to be the join of semi‐equivalence classes containing it, i.e. a result of acting union operation on some primitive classes. A compatibly kernel class of an object is a meet of semi‐equivalence classes including it, i.e. a result of acting intersection operation on some primitive classes. Related coverings can also be regarded as coverings derived from the covering consisting of primitive granules. Several necessary and/or sufficient conditions for a general covering to become a semi‐equivalence or complete covering are obtained. Meaningful property and relationship results are also exploited.

Constructing diverse granules naturally from an incomplete information system to form a different knowledge expression system looks promising for data mining in the information society. It widens the approach and schema.

The paper shows that the formation process of granules is natural, newly defined, and not similar and theoretic to those existing in a neighborhood system. The relationship between diverse granules and coverings is described by mathematical theorems in sufficient or necessary condition form.

The huge volume of biomedical literature provides a nice opportunity and challenge to induce novel knowledge by finding some connections among logical‐related medical concepts This paper aims to propose a semantic‐based knowledge discovery system for mining novel connections from large online digital libraries.

The method takes advantages of the biomedical ontologies, MeSH and UMLS, as the source of semantic knowledge. A prototype system, Biomedical Semantic‐based Knowledge Discovery System (Bio‐SbKDS), is designed to uncover novel hypothesis/connections hidden in the biomedical literature. Using only the starting concept and the initial semantic relation derived from UMLS, Bio‐SbKDS can automatically generate the semantic types as category restrictions for concepts. Using the semantic types and semantic relations of the biomedical concepts, Bio‐SbKDS can identify the relevant concepts collected from Medline in terms of the semantic type and generate the novel hypothesis between these concepts based on the semantic relations.

The system successfully replicates Dr Swanson's famous discoveries: Raynaud disease/fish oil automatically, and generates much less intermediate concepts and spurious connections.

The method takes full advantage of the semantic knowledge of the biomedical concepts, compared with previous approaches, our methods generate much less but more relevant novel hypotheses. Another significant advantage over other traditional approaches is that our method requires much less human intervention in the discovery procedure.

The aim of this paper is to introduce the special issue on the Semantic Web. Intensive research has been undertaken worldwide in research centres and several achievements have been accomplished towards the ultimate objective: the expression and the exploitation of humanity's collective knowledge.

A multi‐fold strategy for the preparation of this special issue was deployed. Given the special characteristics, a balanced mix of introductory papers to the topic, and also advanced research papers at the leading edge of Semantic Web evolution, were selected.

The paper summarizes the articles of the issue and also provides help in understanding the Semantic Web Roadmap of Digital Libraries.

Introduces the papers in the special issue.

In this paper, the properties of the warp knitted spacer fabrics for pressure reduction are experimentally investigated and compared to other materials. The influences of the different parameters such as thickness, spacer yarn diameter and connecting form are also analyzed and discussed. The results have shown that the spacer knitted fabrics have very good properties for pressure reduction when they are used as mattress or cushions.

Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may limit the positive effects of these systems. The purpose of this paper is to systematically evaluate the degree of domain specificity of the AGROVOC controlled vocabulary terms as a representative of a large terminology in the agricultural domain and discuss the generic/specific boundaries across its hierarchy.

A user-oriented study with domain-experts in conjunction with quantitative and systematic analysis. First an in-depth analysis of AGROVOC was carried out to make a proper selection of terms for the experiment. Then domain-experts were asked to classify the terms according to their domain specificity. An evaluation was conducted to analyse the domain-experts’ results. Finally, the resulting data set was automatically compared with the terms in SUMO, an upper ontology and MILO, a mid-level ontology; to analyse the coincidences.

Results show the existence of a high number of generic terms. The motivation for several of the unclear cases is also depicted. The automatic evaluation showed that there is not a direct way to assess the specificity degree of a term by using SUMO and MILO ontologies, however, it provided additional validation of the results gathered from the domain-experts.

The “domain-analysis” concept has long been discussed and it could be addressed from different perspectives. A resume of these perspectives and an explanation of the approach followed in this experiment is included in the background section.

The authors propose an approach to identify the domain specificity of terms in large domain-specific terminologies and a criterion to measure the overall domain specificity of a knowledge organisation system, based on domain-experts analysis. The authors also provide a first insight about using automated measures to determine the degree to which a given term can be considered domain specific. The resulting data set from the domain-experts’ evaluation can be reused as a gold standard for further research about these automatic measures.

Despite the fact that user participation (UP) has been highlighted as an important aspect in innovation, previous findings on its relationship with service innovation performance (SIP) are inconsistent. This study aims to investigate the relationships among UP, knowledge management capability (KMC) and SIP, especially in the digital age, inspired by the theories of knowledge-based and absorptive capacity.

Based on a sample of 252 Chinese e-commerce enterprises, this study adopts a hierarchical regression analysis and bootstrap method to test the theoretical framework and research hypotheses.

UP and KMC have positive effects on SIP, respectively. KMC plays a mediating role in the effect of UP on SIP. Furthermore, the intermediary role of KMC varies in different sub-paths between UP and SIP.

First, this study provides some explanations for inconsistent arguments on the relationship between UP and service innovation. Second, with the consideration of specific dimensions of UP and SIP, the mediation role of KMC varies in different sub-paths has been recognized, which provides a deeper understanding of the relationship between UP and SIP. Third, this study opens the discussion about how to realize SIP more effectively in the digital age, advancing theoretical and practical developments on service innovation.

This study aims to apply legitimacy theory and self-identity theory to the online food delivery (OFD) app service and then to investigate the impact of green brand legitimacy and biospheric value orientation perceived by customers on eco-friendly behavior.

This study focuses on the mediating role of trust in green brands and its perceived benefits (including psychological and environmental benefits). This study involved an online survey of 445 customers who had experienced using OFD services in the past six months.

The platform's green brand legitimacy and consumer perceived biospheric value orientation positively impact trust in green brands. Trust in green products and services significantly affects customers' perceived benefits and has a positive impact on eco-friendly service using behavior. Mediating effect analysis indicated that brand legitimacy and biospheric value have a positive indirect influence on the psychological benefits of supporting green activities and utilitarian environmental benefits.

The convenience sampling method is used, and its purely quantitative nature may limit the generalization of the research results.

The OFD platform should encourage online catering retailers to use more eco-friendly packages for packaging food and minimize the provision of disposable tableware. The platform manager can provide consumers with knowledge and information on lowering related environmental pollution sources when ordering food.

This study innovatively introduces brand legitimacy into the green consumption literature. This is an essential expansion of the content of brand legitimacy and a supplement for the research field of eco-friendly behavior.

The purpose of this paper is to investigate Chinese farmers’ adaptation behavior in the context of the rising cost of labor in agriculture. As the cost of labor increases, farmers will either reallocate their budget to different inputs or change the structure of agricultural production to maximize profit.

The Rural Fixed Point Observation data set between 2004 and 2010 is employed in the empirical analysis of this study. Both the compensated and uncompensated demand elasticities with respect to wages are estimated by adopting the translog cost function and the profit function.

The results show that labor input will drop down significantly as a response to rising wages. Land, fertilizer and intermediate inputs are net complements of labor, whereas machinery appears to be net substitute for labor. In addition, the authors also separate the expansion effect from the substitution effect and find that farmers will shift to grain production with intensive use of fertilizer and from wheat and corn to rice as a response to the rising cost of labor.

This study adopts the classical household model to incorporate various adaptation behaviors of farmers into one framework and decomposes the total effect of the rising cost of labor on input demand into an expansion effect and a substitution effect, which provides a better understanding of farmers’ adaptation behavior.