Configuration knowledge modeling of customizable products based on semantic web technologies

In order to solve the problem of modeling product configuration knowledge at the semantic level to successfully implement the mass customization strategy, an approach of ontology-based configuration knowledge modeling, combining semantic web technologies, was proposed. A general configuration ontology was developed to provide a common concept structure for modeling configuration knowledge and rules of specific product domains. The OWL web ontology language and semantic web rule language （SWRL） were used to formally represent the configuration ontology, domain configuration knowledge and rules to enhance the consistency, maintainability and reusability of all the configuration knowledge. The configuration knowledge modeling of a customizable personal computer family shows that the approach can provide explicit, computerunderstandable knowledge semantics for specific product configuration domains and can efficiently support automatic configuration tasks of complex products.

World-Wide Semantic Web of Agriculture Knowledge

The rapid increase in the publication of knowledge bases as linked open data （LOD） warrants serious consideration from all concerned, as this phenomenon will potentially scale exponentially. This paper will briefly describe the evolution of the LOD, the emerging world-wide semantic web （WWSW）, and explore the scalability and performance features Of the service oriented architecture that forms the foundation of the semantic technology platform developed at MIMOS Bhd., for addressing the challenges posed by the intelligent future internet. This paper＂ concludes with a review of the current status of the agriculture linked open data.

A survey of semantic web technology for agriculture

Semantic web technologies have become a popular technique to apply meaning to unstructured data.They have been infrequently applied to problems within the agricultural domain when compared to complementary domains.Despite this lack of application,agriculture has a large number of semantic resources that have been developed by large NGOs such as the Food and Agriculture Organization(FAO).This survey is intended to motivate further research in the application of semantic web technologies for agricultural problems,by making available a self contained reference that provides:a comprehensive review of preexisting semantic resources and their construction methods,data interchange standards,as well as a survey of the current applications of semantic web technologies.

Semantic Representation of Evidence-Based Medical Guidelines and Its Use Cases

Semantic representation of evidence-based medical guidelines provides the support for the data inter-operability and has been found many applications in the medical domain. In this paper, we describe a semantic representation approach of evidence-based medical guidelines, which is based on the Semantic Web Technology standards. We discuss several use cases of that semantic representation of evidence-based medical guideline, and show that they are potentially useful for medical applications.

A knowledge graph and service for regional geologic time standards

Geologic time is an important dimension in geological research.Geologic time data are commonly collected from multiple sources in data-intensive studies of Earth’s history and raise an issue of data cleansing and integration.A knowledge graph of the international geological time scale has been established to harmonize heterogeneous data to facilitate effective and efficient data-driven discovery.Although many regional geologic time standards are also used in various databases and literature,there is limited discussion or development of knowledge graph for them.In this research,we construct a knowledge graph for the geologic time standards in 17 regions at the Epoch and Age levels.This regional geologic time knowledge graph is integrated with the international geologic time knowledge graph as a comprehensive deep-time knowledge base.A SPARQL endpoint has been established to provide open and free online service to the knowledge base.Several use cases are presented here to demonstrate the functionality of the knowledge graph we built as well as its application in open data exploration.Our work addresses the shortage of machine-readable knowledge graphs for regional geologic time standards and will help accelerate geologic data integration from multiple sources in data-intensive studies.All data and code in this paper are made open source and are accessible on GitHub and Zenodo.

Ontology-based Access Control for FAIR Data

This paper focuses on fine-grained,secure access to FAIR data,for which we propose ontology-based data access policies.These policies take into account both the FAIR aspects of the data relevant to access(such as provenance and licence),expressed as metadata,and additional metadata describing users.With this tripartite approach(data,associated metadata expressing FAIR information,and additional metadata about users),secure and controlled access to object data can be obtained.This yields a security dimension to the“A”(accessible)in FAIR,which is clearly needed in domains like security and intelligence.These domains need data to be shared under tight controls,with widely varying individual access rights.In this paper,we propose an approach called Ontology-Based Access Control(OBAC),which utilizes concepts and relations from a data set's domain ontology.We argue that ontology-based access policies contribute to data reusability and can be reconciled with privacy-aware data access policies.We illustrate our OBAC approach through a proof-of-concept and propose that OBAC to be adopted as a best practice for access management of FAIR data.

Hastily formed knowledge networks and distributed situation awareness for collaborative robotics

In the context of collaborative robotics,distributed situation awareness is essential for supporting collective intelligence in teams of robots and human agents where it can be used for both individual and collective decision support.This is particularly important in applications pertaining to emergency rescue and crisis management.During operational missions,data and knowledge are gathered incrementally and in different ways by heterogeneous robots and humans.We describe this as the creation of Hastily Formed Knowledge Networks(HFKNs).The focus of this paper is the specification and prototyping of a general distributed system architecture that supports the creation of HFKNs by teams of robots and humans.The information collected ranges from low-level sensor data to high-level semantic knowledge,the latter represented in part as RDF Graphs.The framework includes a synchronization protocol and associated algorithms that allow for the automatic distribution and sharing of data and knowledge between agents.This is done through the distributed synchronization of RDF Graphs shared between agents.High-level semantic queries specified in SPARQL can be used by robots and humans alike to acquire both knowledge and data content from team members.The system is empirically validated and complexity results of the proposed algorithms are provided.Additionally,a field robotics case study is described,where a 3D mapping mission has been executed using several UAVs in a collaborative emergency rescue scenario while using the full HFKN Framework.