A Mobile Query Service for Integrated Access to Large Numbers of Online Semantic Web Data Sources

From the Semantic Web’s inception, a number of concurrent initiatives have given rise to multiple segments: large semantic datasets, exposed by query endpoints; online Semantic Web documents, in the form of RDF files; and semantically annotated web content (e.g., using RDFa), semantic sources in their own right. In various mobile application scenarios, online semantic data has proven to be useful. While query endpoints are most commonly exploited, they are mainly useful to expose large semantic datasets. Alternatively, mobile RDF stores are utilized to query local semantic data, but this requires the design-time identification and replication of relevant data. Instead, we present a mobile query service that supports on-the-fly and integrated querying of semantic data, originating from a largely unused portion of the Semantic Web, comprising online RDF files and semantics embedded in annotated webpages. To that end, our solution performs dynamic identification, retrieval and caching of query-relevant semantic data. We explore several data identification and caching alternatives, and investigate the utility of source metadata in optimizing these tasks. Further, we introduce a novel cache replacement strategy, fine- tuned to the described query dataset, and include explicit support for the Open World Assumption. An extensive experimental validation evaluates the query service and its alternative components

Hypnos: a Hardware and Software Toolkit for Energy-Aware Sensing in Low-Cost IoT Nodes

Through the Internet of Things, autonomous sensing devices can be deployed to regularly capture environmental and other sensor measurements for a variety of usage scenarios. However, for the market segment of stand-alone, self-sustaining small IoT nodes, long term deployment remains problematic due to the energy-constrained nature of these devices, requiring frequent maintenance. This article introduces Hypnos, an open hardware and software toolkit that aims to balance energy intake and usage through adaptive sensing rate for low-cost Internetconnected IoT nodes. We describe the hardware architecture of the IoT node, an open hardware board based on the Arduino Uno form-factor packing the energy measurement circuitry, and the associated open source software library, that interfaces with the sensing node’s microcontroller and provides access to the low-level energy measurements. Hypnos comes equipped with a built-in, configurable, modified sigmoid function to regulate duty cycle frequency based on energy intake and usage, yet developers may also plug in their custom duty/sleep balancing function. An experiment was set up, whereby two identical boards ran for two months: one with the Hypnos software framework and built-in energy balancing function to regulate sensing rate and the other with fixed sensing rate. The experiment showed that Hypnos is able to successfully balance energy usage and sensing frequency within configurable energy ranges. Hereby, it increases reliability by avoiding complete shutdown, while at the same time optimizing performance in terms of average amount of sensor measurements

Enterprise-specific ontology-driven process modelling

Different process models are created within an enterprise by different modelers who use different enterprise terms. This hinders model interoperability and integration. A possible solution is formalizing the vocabulary used within the enterprise in an ontology and put this ontology as bases for constructing process models. Given that an enterprise is an evolving entity, the ontology needs to evolve to properly reflect the domain of the enterprise. This paper proposes an enterprise-specific ontology-driven process modelling method which tackles the two aforementioned issues by assisting the modeller in creating process models using terminology from the ontology and simultaneously supporting ontology enrichment with feedback from those models. When the modeller creates a model, matching mechanisms incorporated in the method are working together to suggest a list of ontological concepts that have a high potential to be useful for a particular modelling element. When the model is created, its quality is first evaluated from different perspectives to make sure that it can be used within the enterprise, and second to discover whether its feedback can be useful for the ontology. When the feedback is extracted, the proposed method incorporates guidelines on how to use this feedback

Understanding the sharing economy and its implication on sustainability in smart cities

Akande, A., Cabral, P., & Casteleyn, S. (2020). Understanding the sharing economy and its implication on sustainability in smart cities. Journal of Cleaner Production, 277, 1-11. [124077]. https://doi.org/10.1016/j.jclepro.2020.124077The purpose of this article is to evaluate the main drivers of the sharing economy through an exhaustive weighting and meta-analysis of previous relevant quantitative research articles, obtained using a systematic literature review methodology. The authors analysed 22 quantitative studies from 2008 through. Out of the 249 extracted relationships (independent – dependent variable), the paper identifies the “best” predictors used in theoretical models to study the sharing economy. These include: attitude on intention to share, perceived behavioural control on intention to share, subjective norm on intention to share, economic benefit on attitude, and perceived risk on attitude. Geographically, Germany and the United States of America were found to be the nations with the highest number of respondents. Temporally, an increasing trend in the number of articles on the sharing economy and respondents was observed. The consolidation of the drivers of the sharing economy provides a solid theoretical foundation for the research community to explore existing hypotheses further and test new hypotheses in emerging contexts of the sharing economy. Given the different conceptual theories that have been used to study the sharing economy and their application to different contexts, this study presents the first attempt at advancing knowledge by quantitatively synthesizing findings presented in previous literature.publishersversionpublishe

A GIS-based methodological framework to identify superficial water sources and their corresponding conduction paths for gravity-driven irrigation systems in developing countries

The limited availability of fresh water is a major constraint to agricultural productivity and livelihood security in many developing countries. Within the coming decades, smallholder farmers in drought-prone areas are expected to be increasingly confronted with local water scarcity problems, but their access to technological knowledge and financial resources to cope with these problems is often limited. In this article, we present a methodological framework that allows for identifying, in a short period of time, suitable and superficial water sources, and cost-effective water transportation routes for the provisioning of gravity-driven irrigation systems. As an implementation of the framework, we present the automated and extensible geospatial toolset named “AGRI’’, and elaborate a case study in Western Honduras, where the methodology and toolset were applied to provide assistance to field technicians in the process of identifying water intake sites and transportation routes. The case study results show that 28 % of the water intake sites previously identified by technicians (without the support of AGRI) were found to be not feasible for gravity-driven irrigation. On the other hand, for the feasible water intake sites, AGRI was able to provide viable and shorter water transportation routes to farms in 70 % of the cases. Furthermore, AGRI was able to provide alternative feasible water intake sites for all considered farms, with correspondingly viable water transportation routes for 74 % of them. These results demonstrate AGRI’s potential to reduce time, costs and risk of failure associated with the development of low-cost irrigation systems, which becomes increasingly needed to support the livelihoods of some of the world’s most vulnerable populations

On Metrics for Location-Aware Games

Metrics are important and well-known tools to measure users’ behavior in games, and gameplay in general. Particularities of location-aware games—a class of games where the player’s location plays a central role-demand specific support in metrics to adequately address the spatio-temporal features such games exhibit. In this article, we analyse and discuss how existing game analytics platforms address the spatio-temporal features of location-aware games. Our analysis reveals that little support is available. Next, based on the analysis, we propose a classification of spatial metrics, embedded in existing literature, and discuss three types of spatial metrics-point-, trajectory- and area-based metrics-, and elaborate examples and difficulties. Finally, we discuss how spatial metrics may be deployed to improve gameplay in location-aware games

Citizens’ intention to use and recommend e-participation: Drawing upon UTAUT and citizen empowerment

Purpose The purpose of this paper is to investigate how citizens’ perception of empowerment can influence the intention to use and intention to recommend e-participation. Design/methodology/approach A research model is evaluated using structural equation modelling. An online survey questionnaire was used to collect data from 210 users of e-participation. Findings The results show that psychological empowerment influences the intention to use and recommend e-participation. Performance expectancy and facilitating conditions were the strongest predictors of intention to use; effort expectancy and social influence had no significant effect on the prediction of intention to use e-participation. Research limitations/implications The use of psychological empowerment as a higher-order multidimensional construct is still insufficiently researched. Future research may explore the effect of each dimension of psychological empowerment in different scenarios of e-participation adoption. Caution is needed when generalising our findings towards the adoption of e-participation in different locations or with different participants. Practical implications The findings can help the local governments to design strategies for the promotion and diffusion of e-participation amongst the citizenry. Those strategies should focus on citizens’ perception of empowerment, thereby creating a positive attitude towards intention to use and recommend e-participation. Originality/value An innovative research model integrates the unified theory of acceptance, use of technology and psychological empowerment; the last as a higher-order construct

Recommendation-Based Conceptual Modeling and Ontology Evolution Framework (CMOE+)

Within an enterprise, various stakeholders create different conceptual models, such as process, data, and requirements models. These models are fundamentally based on similar underlying enterprise (domain) concepts, but they differ in focus, use different modeling languages, take different viewpoints, utilize different terminology, and are used to develop different enterprise artifacts; as such, they typically lack consistency and interoperability. This issue can be solved by enterprise-specific ontologies, which serve as a reference during the conceptual model creation. Using such a shared semantic repository makes conceptual models interoperable and facilitates model integration. The challenge to accomplish this is twofold: on the one hand, an up-to-date enterprise-specific ontology needs to be created and maintained, and on the other hand, different modelers also need to be supported in their use of the enterprise-specific ontology. The authors propose to tackle these challenges by means of a recommendation-based conceptual modeling and an ontology evolution framework, and we focus in particular on ontology-based modeling support. To this end, the authors present a framework for Business Process Modeling Notation (BPMN) as a conceptual modeling language, and focus on how modelers can be assisted during the modeling process and how this impacts the semantic quality of the resulting models. Subsequently, a first, large-scale explorative experiment is presented involving 140 business students to evaluate the BPMN instantiation of our framework. The experiments show promising results with regard to incurred overheads, intention of use and model interoperability

An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

In large-scale context-aware applications, a central design concern is capturing, managing and acting upon location and context data. The ability to understand the collected data and define meaningful contextual events, based on one or more incoming (contextual) data streams, both for a single and multiple users, is hereby critical for applications to exhibit location- and context-aware behaviour. In this article, we describe a context-aware, data-intensive metrics platform —focusing primarily on its geospatial support—that allows exactly this: to define and execute metrics, which capture meaningful spatio-temporal and contextual events relevant for the application realm. The platform (1) supports metrics definition and execution; (2) provides facilities for real-time, in-application actions upon metrics execution results; (3) allows post-hoc analysis and visualisation of collected data and results. It hereby offers contextual and geospatial data management and analytics as a service, and allow context-aware application developers to focus on their core application logic. We explain the core platform and its ecosystem of supporting applications and tools, elaborate the most important conceptual features, and discuss implementation realised through a distributed, micro-service based cloud architecture. Finally, we highlight possible application fields, and present a real-world case study in the realm of psychological health

Ten Years of Rich Internet Applications: A Systematic Mapping Study, and Beyond

BACKGROUND: The term Rich Internet Applications (RIAs) is generally associated with Web appli- cations that provide the features and functionality of traditional desktop applications. Ten years after the introduction of the term, an ample amount of research has been carried out to study various aspects of RIAs. It has thus become essential to summarize this research and provide an adequate overview. OBJECTIVE: The objective of our study is to assemble, classify and analyze all RIA research performed in the scienti c community, thus providing a consolidated overview thereof, and to identify well-established topics, trends and open research issues. Additionally, we provide a qualitative discussion of the most inter- esting ndings. This work therefore serves as a reference work for beginning and established RIA researchers alike, as well as for industrial actors that need an introduction in the eld, or seek pointers to (a speci c subset of) the state-of-the-art. METHOD: A systematic mapping study is performed in order to identify all RIA-related publications, de ne a classi cation scheme, and categorize, analyze, and discuss the identi ed research according to it. RESULTS: Our source identi cation phase resulted in 133 relevant, peer-reviewed publications, published between 2002 and 2011 in a wide variety of venues. They were subsequently classi ed according to four facets: development activity, research topic, contribution type and research type. Pie, stacked bar and bubble charts were used to visualize and analyze the results. A deeper analysis is provided for the most interesting and/or remarkable results. CONCLUSION: Analysis of the results shows that, although the RIA term was coined in 2002, the rst RIA-related research appeared in 2004. From 2007 there was a signi cant increase in research activity, peaking in 2009 and decreasing to pre-2009 levels afterwards. All development phases are covered in the identi ed research, with emphasis on \design" (33%) and \implementation" (29%). The majority of research proposes a \method" (44%), followed by \model" (22%), \methodology" (18%) and \tools" (16%); no publications in the category \metrics" were found. The preponderant research topic is \models, methods and methodologies" (23%) and to a lesser extent, \usability & accessibility" and \user interface" (11% each). On the other hand, the topic \localization, internationalization & multi-linguality" received no attention at all, and topics such as \deep web" (under 1%), \business processing", \usage analysis", \data management", \quality & metrics", (all under 2%), \semantics" and \performance" (slightly above 2%) received very few attention. Finally, there is a large majority of \solution proposals" (66%), few \evaluation research" (14%) and even fewer \validation" (6%), although the latter are increasing in recent years