Semantic technologies for open interaction systems

Open interaction systems play a crucial role in agreement technologies because they are software devised for enabling autonomous agents (software or human) to interact, negotiate, collaborate, and coordinate their activities in order to establish agreements and manage their execution. Following the approach proposed by the recent literature on agent environments those open distributed systems can be efficiently and effectively modeled as a set of correlated physical and institutional spaces of interaction where objects and agents are situated. In our view in distributed open systems, spaces are fundamental for modeling the fact that events, actions, and social concepts (like norms and institutional objects) should be perceivable only by the agents situated in the spaces where they happen or where they are situated. Institutional spaces are also crucial for their active functional role of keeping track of the state of the interaction, and for monitoring and enforcing norms. Given that in an open distributed and dynamic system it is fundamental to be able to create and destroy spaces of interaction at run-time, in this paper we propose to create them using Artificial Institutions (AIs) specified at design time. This dynamic creation is a complex task that deserves to be studied in all details. For doing that, in this paper, we will first define the various components of AIs and spaces using Semantic Web Technologies, then we will describe the mechanisms for using AIs specification for realizing spaces of interaction. We will exemplify this process by formalizing the components of the auction Artificial Institution and of the spaces created for running concrete auction

A Survey on User Interaction with Linked Data

Since the beginning of the Semantic Web and the coining of the term Linked Data in 2006, more than one thousand datasets with over sixteen thousand links have been published to the Linked Open Data Cloud. This rising interest is fuelled by the benefits that semantically annotated and machine-readable information can have in many systems. Alongside this growth we also observe a rise in humans creating and consuming Linked Data, and the opportunity to study and develop guidelines for tackling the new user interaction problems that arise with it. To gather information on the current solutions for modelling user interaction for these applications, we conducted a study surveying the interaction techniques provided in the state of the art of Linked Data tools and applications developed for users with no experience with Semantic Web technologies. The 18 tools reviewed are described and compared according to the interaction features provided, techniques used for visualising one instance and a set of instances, search solutions implemented, and the evaluation methods used to evaluate the proposed interaction solutions. From this review, we can conclude that researchers have started to deviate from more traditional visualisation techniques, like graph visualisations, when developing for lay users. This shows a current effort in developing Semantic Web tools to be used by lay users and motivates the documentation and formalisation of the solutions encountered in the studied tools. Copyright (c) 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun

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

The Cognitive Atlas: Employing Interaction Design Processes to Facilitate Collaborative Ontology Creation

The Cognitive Atlas is a collaborative knowledge-building project that aims to develop an ontology that characterizes the current conceptual framework among researchers in cognitive science and neuroscience. The project objectives from the beginning focused on usability, simplicity, and utility for end users. Support for Semantic Web technologies was also a priority in order to support interoperability with other neuroscience projects and knowledge bases. Current off-the-shelf semantic web or semantic wiki technologies, however, do not often lend themselves to simple user interaction designs for non-technical researchers and practitioners; the abstract nature and complexity of these systems acts as point of friction for user interaction, inhibiting usability and utility. Instead, we take an alternate interaction design approach driven by user centered design processes rather than a base set of semantic technologies. This paper reviews the initial two rounds of design and development of the Cognitive Atlas system, including interactive design decisions and their implementation as guided by current industry practices for the development of complex interactive systems

Emergent Capabilities for Collaborative Teams in the Evolving Web Environment

This paper reports on our investigation of the latest advances for the Social Web, Web 2.0 and the Linked Data Web. These advances are discussed in terms of the latest capabilities that are available (or being made available) on the Web at the time of writing this paper. Such capabilities can be of significant benefit to teams, especially those comprised of multinational, geographically-dispersed team members. The specific context of coalition members in a rapidly formed diverse military context such as disaster relief or humanitarian aid is considered, where close working between non-government organisations and non-military teams will help to achieve results as quickly and efficiently as possible. The heterogeneity one finds in such teams, coupled with a lack of dedicated private network infrastructure, poses a number of challenges for collaboration, and the current paper represents an attempt to assess whether nascent Web-based capabilities can support such teams in terms of both their collaborative activities and their access to (and sharing of) information resources

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations