The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

A customized semantic service retrieval methodology for the digital ecosystems environment

With the emergence of the Web and its pervasive intrusion on individuals, organizations, businesses etc., people now realize that they are living in a digital environment analogous to the ecological ecosystem. Consequently, no individual or organization can ignore the huge impact of the Web on social well-being, growth and prosperity, or the changes that it has brought about to the world economy, transforming it from a self-contained, isolated, and static environment to an open, connected, dynamic environment. Recently, the European Union initiated a research vision in relation to this ubiquitous digital environment, known as Digital (Business) Ecosystems. In the Digital Ecosystems environment, there exist ubiquitous and heterogeneous species, and ubiquitous, heterogeneous, context-dependent and dynamic services provided or requested by species. Nevertheless, existing commercial search engines lack sufficient semantic supports, which cannot be employed to disambiguate user queries and cannot provide trustworthy and reliable service retrieval. Furthermore, current semantic service retrieval research focuses on service retrieval in the Web service field, which cannot provide requested service retrieval functions that take into account the features of Digital Ecosystem services. Hence, in this thesis, we propose a customized semantic service retrieval methodology, enabling trustworthy and reliable service retrieval in the Digital Ecosystems environment, by considering the heterogeneous, context-dependent and dynamic nature of services and the heterogeneous and dynamic nature of service providers and service requesters in Digital Ecosystems.The customized semantic service retrieval methodology comprises: 1) a service information discovery, annotation and classification methodology; 2) a service retrieval methodology; 3) a service concept recommendation methodology; 4) a quality of service (QoS) evaluation and service ranking methodology; and 5) a service domain knowledge updating, and service-provider-based Service Description Entity (SDE) metadata publishing, maintenance and classification methodology.The service information discovery, annotation and classification methodology is designed for discovering ubiquitous service information from the Web, annotating the discovered service information with ontology mark-up languages, and classifying the annotated service information by means of specific service domain knowledge, taking into account the heterogeneous and context-dependent nature of Digital Ecosystem services and the heterogeneous nature of service providers. The methodology is realized by the prototype of a Semantic Crawler, the aim of which is to discover service advertisements and service provider profiles from webpages, and annotating the information with service domain ontologies.The service retrieval methodology enables service requesters to precisely retrieve the annotated service information, taking into account the heterogeneous nature of Digital Ecosystem service requesters. The methodology is presented by the prototype of a Service Search Engine. Since service requesters can be divided according to the group which has relevant knowledge with regard to their service requests, and the group which does not have relevant knowledge with regard to their service requests, we respectively provide two different service retrieval modules. The module for the first group enables service requesters to directly retrieve service information by querying its attributes. The module for the second group enables service requesters to interact with the search engine to denote their queries by means of service domain knowledge, and then retrieve service information based on the denoted queries.The service concept recommendation methodology concerns the issue of incomplete or incorrect queries. The methodology enables the search engine to recommend relevant concepts to service requesters, once they find that the service concepts eventually selected cannot be used to denote their service requests. We premise that there is some extent of overlap between the selected concepts and the concepts denoting service requests, as a result of the impact of service requesters’ understandings of service requests on the selected concepts by a series of human-computer interactions. Therefore, a semantic similarity model is designed that seeks semantically similar concepts based on selected concepts.The QoS evaluation and service ranking methodology is proposed to allow service requesters to evaluate the trustworthiness of a service advertisement and rank retrieved service advertisements based on their QoS values, taking into account the contextdependent nature of services in Digital Ecosystems. The core of this methodology is an extended CCCI (Correlation of Interaction, Correlation of Criterion, Clarity of Criterion, and Importance of Criterion) metrics, which allows a service requester to evaluate the performance of a service provider in a service transaction based on QoS evaluation criteria in a specific service domain. The evaluation result is then incorporated with the previous results to produce the eventual QoS value of the service advertisement in a service domain. Service requesters can rank service advertisements by considering their QoS values under each criterion in a service domain.The methodology for service domain knowledge updating, service-provider-based SDE metadata publishing, maintenance, and classification is initiated to allow: 1) knowledge users to update service domain ontologies employed in the service retrieval methodology, taking into account the dynamic nature of services in Digital Ecosystems; and 2) service providers to update their service profiles and manually annotate their published service advertisements by means of service domain knowledge, taking into account the dynamic nature of service providers in Digital Ecosystems. The methodology for service domain knowledge updating is realized by a voting system for any proposals for changes in service domain knowledge, and by assigning different weights to the votes of domain experts and normal users.In order to validate the customized semantic service retrieval methodology, we build a prototype – a Customized Semantic Service Search Engine. Based on the prototype, we test the mathematical algorithms involved in the methodology by a simulation approach and validate the proposed functions of the methodology by a functional testing approach

Modeling the dynamics of web-based service and resource-oriented digital ecosystems

The notion of digital species is broadened to include services and resources, special issues arise in modeling the dynamics and workflows with representations associated with these services and resources. To address these issues, this paper explores two different yet related approaches: the traditional BPEL-based workflow modeling approach and the Mashupbased Web approach. In this paper, we first demonstrate two examples of service-oriented and resource-oriented digital ecosystems on the Web. We then identify key issues pertinent to both types of DES. We discuss formal definition, specifications and issues of BPEL-based approach and Mashup-based modeling techniques with computational formalisms. Finally, we propose a hybrid approach to deal with modeling the dynamicsin processes associated with such Digital Ecosystems

Activity-Centric Computing Systems

• Activity-Centric Computing (ACC) addresses deep-rooted information management problems in traditional application centric computing by providing a unifying computational model for human goal-oriented ‘activity,’ cutting across system boundaries. • We provide a historical review of the motivation for and development of ACC systems, and highlight the need for broadening up this research topic to also include low-level system research and development. • ACC concepts and technology relate to many facets of computing; they are relevant for researchers working on new computing models and operating systems, as well as for application designers seeking to incorporate these technologies in domain-specific applications

Product Information Quality : A sustainability challenge in design and construction

The adverse consequences of building product performance pose sustainability problems for the built environment. Effective approaches to these problems require a clear understanding of building product information and its provision by manufacturers. This is an essential need for sustainable growth in industrialized construction, a system characterized by the expanded role of the manufacturing sector. Furthermore, a sustainable transition to digitalization in the construction industry needs digital interfaces capable of providing the information required for sustainable design and construction. The aim of this research is to contribute to an increased understanding of how building product information can support sustainability in the built environment. To this end, two fundamental aspects have been examined: the quality of information on the sustainability performance of building products and the usability of the digital interfaces providing such information. This research relies on critical realism and adopts a qualitative methodology to analyze and explain the mechanisms of creating and providing product information in four sequential case studies. Systems thinking and process tracing method have been applied to analyze the flow of product information in the construction industry, the operative processes that can support sustainability, and the stakeholders involved. In the first three case studies, the operative process is the diffusion of innovative ventilation products with superior indoor environmental performance. The first case study identifies the problems affecting this process. The second and third case studies, respectively, explore how product information and information exchange on building information modeling (BIM) library platforms can support the process. Influenced by the Grenfell Tower fire in London in 2017, the fourth case identifies the product information problems that can contribute to harmful facade fires threatening sustainability in the built environment. The study examines the capabilities for avoiding the identified problems and explores how an operative process of design, manufacturing, and construction of fire-safe facades can be supported. The findings reveal problems concerning the quality of information on the sustainability performance of products and the methods used by manufacturers for presenting such information. These problems have limited the availability and usability of the information in product databases and BIM object libraries. This defective flow of information affects the design process and can lead to unacceptable consequences such as facade fires. In addition, the inefficient methods of supplying product information have impeded the adoption of innovative products with improved sustainability performance. To address these issues, this research proposes the standardization of product information in collaboration with effective legislation and establishes a framework for evaluating the provision of information on the sustainability performance of building products. The theoretical contributions of this work include five tools: (1) a model for applied critical realism towards sustainability, (2) a matrix for the qualitative analysis of BIM object library platforms, (3) a matrix for evaluating the quality of information and digital interfaces, (4) a model of the functions of the standards on product information, and (5) a conceptual model of product information for sustainable design and construction

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Human system interaction with confident computing

This keynote will give an overview of the last 30 years of human system interaction and the key elements of Human Computer Interaction (HCI) and its transition from traditional HCI into the frontier of Human System Interaction (HSI). This leads to the discussion as to why HSI is about Digital Ecosystems and about the world we live in rather than just ICT. We explain the 5 Mega Trends, and the emergence of Confident Computing and how that is leading to the revolution of the next generation of Human System Interaction version 2.0 and Usability version 2.0. This is followed by the challenges and research issues within Human System Interaction (HSI)

A Reference System Architecture with Data Sovereignty for Human-Centric Data Ecosystems

Since the European information economy faces insufficient access to and joint utilization of data, data ecosystems increasingly emerge as economical solutions in B2B environments. Contrarily, in B2C ambits, concepts for sharing and monetizing personal data have not yet prevailed, impeding growth and innovation. Their major pitfall is European data protection law that merely ascribes human data subjects a need for data privacy while widely neglecting their economic participatory claims to data. The study reports on a design science research (DSR) approach addressing this gap and proposes an abstract reference system architecture for an ecosystem centered on humans with personal data. In this DSR approach, multiple methods are embedded to iteratively build and evaluate the artifact, i.e., structured literature reviews, design recovery, prototyping, and expert interviews. Managerial contributions embody novel design knowledge about the conceptual development of human-centric B2C data ecosystems, considering their legal, ethical, economic, and technical constraints