Position paper on realizing smart products: challenges for Semantic Web technologies

In the rapidly developing space of novel technologies that combine sensing and semantic technologies, research on smart products has the potential of establishing a research field in itself. In this paper, we synthesize existing work in this area in order to define and characterize smart products. We then reflect on a set of challenges that semantic technologies are likely to face in this domain. Finally, in order to initiate discussion in the workshop, we sketch an initial comparison of smart products and semantic sensor networks from the perspective of knowledge technologies

Towards Knowledge in the Cloud

Knowledge in the form of semantic data is becoming more and more ubiquitous, and the need for scalable, dynamic systems to support collaborative work with such distributed, heterogeneous knowledge arises. We extend the “data in the cloud” approach that is emerging today to “knowledge in the cloud”, with support for handling semantic information, organizing and finding it efficiently and providing reasoning and quality support. Both the life sciences and emergency response fields are identified as strong potential beneficiaries of having ”knowledge in the cloud”

Research and Development Workstation Environment: the new class of Current Research Information Systems

Against the backdrop of the development of modern technologies in the field of scientific research the new class of Current Research Information Systems (CRIS) and related intelligent information technologies has arisen. It was called - Research and Development Workstation Environment (RDWE) - the comprehensive problem-oriented information systems for scientific research and development lifecycle support. The given paper describes design and development fundamentals of the RDWE class systems. The RDWE class system's generalized information model is represented in the article as a three-tuple composite web service that include: a set of atomic web services, each of them can be designed and developed as a microservice or a desktop application, that allows them to be used as an independent software separately; a set of functions, the functional filling-up of the Research and Development Workstation Environment; a subset of atomic web services that are required to implement function of composite web service. In accordance with the fundamental information model of the RDWE class the system for supporting research in the field of ontology engineering - the automated building of applied ontology in an arbitrary domain area, scientific and technical creativity - the automated preparation of application documents for patenting inventions in Ukraine was developed. It was called - Personal Research Information System. A distinctive feature of such systems is the possibility of their problematic orientation to various types of scientific activities by combining on a variety of functional services and adding new ones within the cloud integrated environment. The main results of our work are focused on enhancing the effectiveness of the scientist's research and development lifecycle in the arbitrary domain area.Comment: In English, 13 pages, 1 figure, 1 table, added references in Russian. Published. Prepared for special issue (UkrPROG 2018 conference) of the scientific journal "Problems of programming" (Founder: National Academy of Sciences of Ukraine, Institute of Software Systems of NAS Ukraine

WHAT IS INFORMATION SUCH THAT THERE CAN BE INFORMATION SYSTEMS?

Information systems, as a discipline, is concerned with the generation, storage and transmission of information, generally by technological means. As such, it would seem to be fundamental that it has a clear and agreed conceptualization of its core subject matter – namely “information”. Yet, we would claim, this is clearly not the case. As McKinney and Yoos point out, in a recent survey of the term information within information systems: “This is the IS predicament – using information as a ubiquitous label whose meaning is almost never specified. Virtually all the extant IS literature fails to explicitly specify meaning for the very label that identifies it.” We live in an information age and the vast majority of information (whatever it may be) is made available through a wide range of computer systems and one would expect therefore that information systems would in fact be one of the leading disciplines of the times rather than one that appears to hide itself in the shadows. Governments nowadays routinely utilize many academic experts to advise them in a whole range of areas but how many IS professors ever get asked? So, the primary purpose of this paper is to stimulate a debate within IS to discuss, and try to establish, a secure foundation for the discipline in terms of its fundamental concept – information. The structure of the paper is that we will firstly review the theories of information used (generally implicitly) within IS. Then we will widen the picture to consider the range of theories available more broadly within other disciplines. We will then suggest a particular approach that we consider most fruitful and discuss some of the major contentious issues. We will illustrate the theories with examples from IS

A Semantic Collaboration Method Based on Uniform Knowledge Graph

The Semantic Internet of Things is the extension of the Internet of Things and the Semantic Web, which aims to build an interoperable collaborative system to solve the heterogeneous problems in the Internet of Things. However, the Semantic Internet of Things has the characteristics of both the Internet of Things and the Semantic Web environment, and the corresponding semantic data presents many new data features. In this study, we analyze the characteristics of semantic data and propose the concept of a uniform knowledge graph, allowing us to be applied to the environment of the Semantic Internet of Things better. Here, we design a semantic collaboration method based on a uniform knowledge graph. It can take the uniform knowledge graph as the form of knowledge organization and representation, and provide a useful data basis for semantic collaboration by constructing semantic links to complete semantic relation between different data sets, to achieve the semantic collaboration in the Semantic Internet of Things. Our experiments show that the proposed method can analyze and understand the semantics of user requirements better and provide more satisfactory outcomes