Search, Filter, Fork, and Link Open Data - The ADEQUATe platform: data- and community-driven quality improvements.

The present work describes the ADEQUATe platform: a framework to monitor the quality of (Governmental) Open Data catalogs, to re-publish improved and linked versions of the datasets and their respective metadata descriptions, and to include the community in the quality improvement process. The information acquired by the linking and (meta)data improvement steps is then integrated in a semantic search engine. In the paper, we first describe the requirements of the platform, which are based on focus group interviews and a web-based survey. Second, we use these requirements to formulate the goals and show the architecture of the overall platform, and third, we showcase the potential and relevance of the platform to resolve the requirements by describing exemplary user journeys exploring the system. The platform is available at: https://www.adequate.at/

Smart Cities and Digital Twins in Lower Austria

Smart city solutions require innovative governance approaches together with the smart use of technology, such as digital twins, by city managers and policymakers to manage the big societal challenges. The project Smart Cities aNd Digital Twins in Lower Austria (SCiNDTiLA) extends the state of the art of research in several contributing disciplines and uses the foundations of complexity theory and computational social science methods to develop a digital-twin-based smart city model. The project will also apply a novel transdisciplinary process to conceptualise sustainable smart cities and validate the smart city generic model. The outcomes will be translated into a roadmap highlighting methodologies, guidelines and policy recommendations for tackling societal challenges in smart cities with a focus on rescaling the entire framework to be transferred to regions, smaller towns and non-urban environments, such as rural areas and smart villages, in ways that fit the respective local governance, ethical and operational capacity context.Comment: 2 page

Thermodynamic Dissipative Systems and Information Theory to Study the Social Component of a Smart City

In this article, we discuss the application of information theory and the theory of thermodynamic dissipative systems to smart cities. Specifically, we study how to model the interaction between a society and a smart city, under an information-theoretic approach. Because the smart city comprises both a social and a technological component, it then becomes possible to use information theory to study them both. In this paper, we discuss a model that applies the constraints from thermodynamic dissipative systems theory in order to study smart cities, and their associated social system, in their information processing capacity and in their evolution over time. Within the context of our model, we are allowed to study under what conditions a smart city would expand or contract, or to state that the smart city shrinks if its output greatly exceeds its input.Facultad de Informátic

Improving the Computational Performance of Ontology-Based Classification Using Graph Databases

The increasing availability of very high-resolution remote sensing imagery (i.e., from satellites, airborne laser scanning, or aerial photography) represents both a blessing and a curse for researchers. The manual classification of these images, or other similar geo-sensor data, is time-consuming and leads to subjective and non-deterministic results. Due to this fact, (semi-) automated classification approaches are in high demand in affected research areas. Ontologies provide a proper way of automated classification for various kinds of sensor data, including remotely sensed data. However, the processing of data entities—so-called individuals—is one of the most cost-intensive computational operations within ontology reasoning. Therefore, an approach based on graph databases is proposed to overcome the issue of a high time consumption regarding the classification task. The introduced approach shifts the classification task from the classical Protégé environment and its common reasoners to the proposed graph-based approaches. For the validation, the authors tested the approach on a simulation scenario based on a real-world example. The results demonstrate a quite promising improvement of classification speed—up to 80,000 times faster than the Protégé-based approach

Natural Language Processing in Geographic Information Systems - Some Trends and Open Issues -

The increasing ubiquity of information technology motivates situative interaction mechanisms for the benefit of standard and power users. Classical interaction paradigms in geographic information systems are currently subject to amendment or even to substitution by context-aware and technology-agnostic natural-language-based interfaces. This work compiles a recent selection of radically innovative concepts found in three selected domains of the open GIS literature including related research demands. The added value herein lies in the coherence of future options and challenges in that field

Affective Effect: Issue Engagement on a Youth E-Participation Platform

While E-participation promotes citizen participation in democratic decision-making processes, and often takes place through deliberation, citizens are expected to be cool-headed individuals equipped with reason and logic, insulating their actions from the impulse of emotion. However, research in neuroscience and cognitive science has found that emotion plays a vital part in cognitive processing and is instrumental in decision-making. This study thus fills this research gap by examining the effect of emotions in eliciting participation on a youth E-participation platform. Following affective intelligence theory and appraisal theory, the authors specifically examined three types of emotions; namely, anger, anxiety, and sadness. By applying methods in the field of text and statistical analysis, the authors found that anxiety, although the least common type of emotion expressed on the E-participation platform, was associated with an increased level of engagement. On the contrary, anger dominated issue discussion across topics, and sadness prevailed in the discourse on system-level economic issues

ICT System Design & Implementation Using Wireless Sensors to Support Elderly In-home Assistance

Around the globe the number of older people in relation to the rest is constantly growing. As a result, medical and care facilities cannot handle the growing number of patients. Therefore, elderly in-home assistance gets more attention an importance. Due to issues regarding memory, physical strength and reduced self-assessment, old people face a lot of challenges in accomplishing their activities of daily living. This thesis is meant to address these problems by analysing the required infrastructure of a home-care facility as well as the arising issues regarding used components, especially wireless sensors. After the analysis, a prototype of a home-care system is designed and implemented. Furthermore, the issue of energy consumption of the used wireless sensor node is addressed by modifying the intelligence of the used sensor. After that, the design and components of the prototype used for the energy consumption analysis is explained, together with the programming structure of the sensor nodes used in this thesis. Thereupon, the results are of the simulations are discussed and compared with the authors ‘expectations. Finally the overall outcomes of the thesis are analysed and summed up, followed by a short outlook of further possible improvements and developments

openlaws.eu: Big data user activity and metadata report

An important part of the openlaws.eu project is to include user-generated content and to combine it with open data. For this purpose, the community needs to be engaged and awareness for the project has to be increased. Social media dissemination is a key element for this task

Improving the Computational Performance of Ontology-Based Classification Using Graph Databases

The increasing availability of very high-resolution remote sensing imagery (i.e., from satellites, airborne laser scanning, or aerial photography) represents both a blessing and a curse for researchers. The manual classification of these images, or other similar geo-sensor data, is time-consuming and leads to subjective and non-deterministic results. Due to this fact, (semi-) automated classification approaches are in high demand in affected research areas. Ontologies provide a proper way of automated classification for various kinds of sensor data, including remotely sensed data. However, the processing of data entities—so-called individuals—is one of the most cost-intensive computational operations within ontology reasoning. Therefore, an approach based on graph databases is proposed to overcome the issue of a high time consumption regarding the classification task. The introduced approach shifts the classification task from the classical Protégé environment and its common reasoners to the proposed graph-based approaches. For the validation, the authors tested the approach on a simulation scenario based on a real-world example. The results demonstrate a quite promising improvement of classification speed—up to 80,000 times faster than the Protégé-based approach