The Interoperability of Things: Interoperable solutions as an enabler for IoT and Web 3.0

This paper presents an overview of the interoperability concepts along with the challenges for the IoT domain and the upcoming Web 3.0. We identify four levels of interoperability and the relevant solutions for accomplishing vertical and horizontal compatibility between the various layers of a modern IoT ecosystem, referred to as: technological, syntactic, semantic, and organizational interoperability. The goal is to achieve cross-domain interaction and facilitate the proper usage and management of the provided IoT services and applications. An interoperability framework is also proposed where the involved system components can cooperate and offer the seamless operation from the device to the backend framework. This by-design end-to-end interoperation enables the interplay of several complex service composition settings and the management of the system via patterns. The overall proposal is adopted by the EU funded project SEMIoTICS as an enabler towards the IoT and Web 3.0, even when products from different vendors are utilized

We are ready for faunistic surveys of bdelloid rotifers through DNA barcoding: the example of <i>Sphagnum</i> bogs of the Swiss Jura Mountains

The identification of biological diversity through DNA barcoding and metabarcoding of the organisms living in the field has the potential to revolutionise the way biological surveys and monitoring are performed. Yet, we still do not know if the current representativeness of the reference database of DNA sequence data is sufficient to allow such approaches. Here, we show that, at least for bdelloid rotifers (Metazoa; Rotifera; Bdelloidea) in Europe, current knowledge is ripe to perform such surveys. We show the results of an exercise performed on bdelloid rotifers in Sphagnum bogs of the Swiss Jura Mountain. The results of DNA-based identifications were rather consistent with the morphology-based identifications, and the few cases of mismatch could be used as a cautionary tale to avoid potential misinterpretations of results. The mismatches were due to cases of the closest match not being genetically very close, and to the occurrence of cryptic species.La identificación de la diversidad biológica a través de DNA barcoding y metabarcoding de los organismos en el medio ambiente tiene el potencial de revolucionar la forma en que se realizan los inventarios biológicos y el monitoreo. Sin embargo, todavía no se sabe si las bases de datos genéticos de referencia a disposición hoy en día son lo suficientemente representativas como para permitir tales enfoques. Aquí, mostramos que, al menos para los rotíferos bdelloideos (Metazoa; Rotifera; Bdelloidea) de Europa, el nivel de conocimiento es suficiente para realizar tales estudios. Mostramos los resultados de un ejercicio realizado sobre rotíferos bdelloideos en turberas de Sphagnum del Jura suizo. Los resultados de las identificaciones basadas en el ADN fueron bastante consistentes con las identificaciones basadas en la morfología, y los pocos casos de desajuste podrían utilizarse como una advertencia para evitar posibles interpretaciones erróneas de los resultados. Estos desajustes se debieron a que las secuencias más cercanas seguían alejadas de los organismos realmente encontrados y a la presencia de especies crípticas

Agent-based autonomous systems and abstraction engines: Theory meets practice

We report on experiences in the development of hybrid autonomous systems where high-level decisions are made by a rational agent. This rational agent interacts with other sub-systems via an abstraction engine. We describe three systems we have developed using the EASS BDI agent programming language and framework which supports this architecture. As a result of these experiences we recommend changes to the theoretical operational semantics that underpins the EASS framework and present a fourth implementation using the new semantics

Routes to sustainability in public food procurement: An investigation of different models in primary school catering

Increasingly, policymakers are setting ambitious goals for sustainability in public procurement, integrated across different pillars. Such ambitions are apparent in public catering services, where procurement models have been shifting towards greater localisation of supply chains and purchasing of more organically grown food. To date however, few studies have examined empirically what the impacts of different procurement models are across these multiple pillars of sustainability. This research aimed to fill the gap, by measuring and comparing the environmental, economic and nutritional outcomes of different models of school meals procurement. Case studies were undertaken of ten primary school meals services in five European countries, capturing different procurement model types. Results showed carbon emissions ranged from 0.95 kgs CO2e per meal in the lowest case to 2.41 kgs CO2e in the highest case, with adoption of low carbon food waste disposal methods and reduction of the amount of ruminant meat in the menus being the most important actions for lowering emissions. In terms of economic impact, local economic multiplier ratios ranged from 1.59 to 2.46, and although the level of local food sourcing contributed to these ratios, the effect was eclipsed, in some cases, by investment in local catering staff. Meanwhile, implementation of a robust standards regime and improving canteen environment and supervision were the most important actions for nutritional quality and intake. The paper discusses the implications of the findings for integrated, sustainable models of food procurement

An event abstraction layer for the integration of geosensor data

Time series of observations reflect the status of environmental properties. Variations in these properties can be considered as events when they potentially affect the stability of the monitored environment. Organisations dedicated to analyse environmental change use institutionalised descriptions of events to define the observable conditions under which events happen. This also applies to the methods used to classify and model changes in environmental monitoring. The heterogeneity of representations often causes interoperability problems when such communities exchange geospatial information. To enhance interoperability among diverse communities, it is required to develop models that do not restrict the representation of events, but allow integrating different perspectives on changes in the environment. The goal of the Event Abstraction Layer is to facilitate the analysis and integration of geosensor data by inferring events from time series of observations. For the analysis of geosensor data, we use event processing to detect event patterns in time series of observations. Spatio-temporal properties of the event are inferred from the geosensor location and the observation timestamps. For the data integration, we represent event-related information extracted from multiples sources under a common event model. Additionally, domain knowledge is modelled in a multilevel ontology structure. © 2014 Taylor &amp; Francis

Utilising stream reasoning techniques to underpin an autonomous framework for cloud application platforms

As cloud application platforms (CAPs) are reaching the stage where the human effort required to maintain them at an operational level is unsupportable, one of the major challenges faced by the cloud providers is to develop appropriate mechanisms for run-time monitoring and adaptation, to prevent cloud application platforms from quickly dissolving into a non-reliable environment. In this context, the application of intelligent approaches to Autonomic Clouds may offer promising opportunities. In this paper we present an approach to providing cloud platforms with autonomic capabilities, utilising techniques from the Semantic Web and Stream Reasoning research fields. The main idea of this approach is to encode values, monitored within cloud application platforms, using Semantic Web languages, which then allows us to integrate semantically-enriched observation streams with static ontological knowledge and apply intelligent reasoning. Using such run-time reasoning capabilities, we have developed a conceptual architecture for an autonomous framework and describe a prototype solution we have constructed which implements this architecture. Our prototype is able to perform analysis and failure diagnosis, and suggest further adaptation actions. We report our experience in utilising the Stream Reasoning technique in this context as well as further challenges that arise out of our work