A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure

Toward a service-based workflow for automated information extraction from herbarium specimens

Over the past years, herbarium collections worldwide have started to digitize millions of specimens on an industrial scale. Although the imaging costs are steadily falling, capturing the accompanying label information is still predominantly done manually and develops into the principal cost factor. In order to streamline the process of capturing herbarium specimen metadata, we specified a formal extensible workflow integrating a wide range of automated specimen image analysis services. We implemented the workflow on the basis of OpenRefine together with a plugin for handling service calls and responses. The evolving system presently covers the generation of optical character recognition (OCR) from specimen images, the identification of regions of interest in images and the extraction of meaningful information items from OCR. These implementations were developed as part of the Deutsche Forschungsgemeinschaft-funded a standardised and optimised process for data acquisition from digital images of herbarium specimens (StanDAP-Herb) Project

The OrgTrace project: Content, Bioavailability and Health Effects of Trace Elements and Bioactive Components of Food Products Cultivated in Organic and Conventional Agricultural Systems

Trace elements, bioactive secondary metabolites and vitamins are among the most important quality parameters in plants. Yet, very little information is available on their content, bioavailability and health effects in organically grown plant food products. The main objective of OrgTrace is to study the impact of different agricultural management practices relevant for organic farming on the ability of cereal and vegetable crops to absorb trace elements from the soil and to synthesize bioactive compounds (secondary metabolites, antioxidant vitamins and phytates) with health promoting effects. Based on different plant products produced in OrgTrace, diets were composed and the bioavailabilities of health promoting substances were analyzed in a human intervention study. Moreover, various health effects such as immune system responses were studied using rats as model organisms. OrgTrace is the first study, which follows selected elements and bioactive compounds all the way from the plant and soil system to absorption in the human body. All experimental studies have now been finalized and we are able to draw final conclusions

Semantics in environmental search systems

In this article we sketch three different and complementary, semantics-enabled approaches to search for structured and unstructured environmental data and information. The SUI system is a search broker using ontology-based metadata and background knowledge for query interpretation, query dispatching, and mapping between different systems. The HIPPOLYTOS system also employs ontology-based metadata over query templates for accessing structured relational data in a data warehouse, and ontological background knowledge for query relaxation. The KOIOS system also addresses relational data, but realizes a schema-agnostic search approach that derives distributional semantics from database content in order to better interpret user queries

Use of environmental data for GIS-based risk assessment of biogas plants in Baden-Württemberg

This paper illustrates how environmental risks potentially emerging in conjunction with an observed growing number of biogas plants can properly be estimated, integrated and visualized in an overarching risk management application. On the one hand, due to safety flaws observed in the past, biogas plants have direct environmental risks as they can cause environmental pollution (e.g. groundwater contamination or emissions of methane). On the other hand, environmental hazards such as floodwater or storms are a threat especially to unsafe biogas plants and an enhancement factor of these risks. Moreover, the growing number of plants causes indirect risks for economy - e.g. dependency on dependable operation of or impact on smart grids - and society, e.g. transition to monocultures, over-fertilization or threatened species. This contribution describes how and which environmental data can support the assessment and visualization of these risks up to the calculation of corresponding risk indicators. The idea is to provide thematic layers for the iNTeg-Risk atlas offered by means of the Web Map Service (WMS) as defined by the Open Geospatial Consortium (OGC). Such a biogas plant layer may comprise information about the geographic position, power and/or gas output, used substrates, security concepts, approvals and observation. It may be combined with further environmental layers describing environmental objects (e.g. nature protection areas), objects at risk (e.g. schools, plants) or traffic flows. Finally, by means of geospatial data analysis, such an integrated geospatial view allows risk managers to evaluate emerging risks caused by biogas plants. As a prototype implementation based on a few scenarios we provide an interface to the Environmental Information System of the German federal state of Baden-Württemberg, from which the base data used for these evaluations will be drawn. As a next step, this application may be enhanced towards a planning instrument for environmental administrations as well as a communication and information means for the citizenship concerned

Towards a Universal Search in Environmental Information Systems

Part 3: Environmental Information Systems and Services – Infrastructures and PlatformsInternational audienceFull-text search functions in environmental portals make a large amount of environmental data accessible. Many data sources, however, are not suited for indexing by search machines or the data themselves are not suited for access by full-text search. A possibility to make such data of the “dark web” accessible consists in addressing the data sources in the environmental portal directly. The procedure presented here starts with a formal description of data sources (e.g. from the point of view of the portal, these are the target systems). Based on this description, a special component of full-text search, the so-called search broker, can extend and detail a search query, such that all necessary parameters (if possible) are compiled to address these systems and to guide the user directly to the data desired. The presentation component of the environmental portal is responsible for the adequate compilation and display of these data, the so-called result mash-up

SUI für Umweltportale. Entwurf und prototypische Implementierung einer Architektur für die semantische Suche im Portal Umwelt-BW

Im Projekt SUI (Semantische Suche nach Umweltinformationen) wurden in der Projektphase I Konzepte für die Verbesserung der Suche nach Informationen in Umweltportalen, insbesondere im Umweltportal Baden-Württemberg (Portal Umwelt-BW), auf Basis von Technologien des Semantic Web erarbeitet und prototypisch umgesetzt /1/. In Projektphase II wurde das SUI-Konzept vervollständigt durch Ausarbeitung einer generischen Schnittstellenspezifikation gemäß dem OpenSearch-Standard /2/. Über diese Schnittstelle (eine ausführliche Beschreibung findet sich in /3/) werden an das Portal gerichtete Suchanfragen an ausgewählte Zielsysteme - unter notwendiger Transformation der Suchparameter - weitergeleitet. In Phase II wurde auch ein neues Konzept für die Gesamt-Architektur definiert. Es basiert auf einer Broker-Architektur für die semantische Vorverarbeitung der Such-Anfragen und wurde in einem neuen Prototyp implementiert. Der vorliegende Beitrag beschreibt die neue Architektur und fokussiert dabei auf Aspekte der Vorverarbeitung und Ergebnispräsentation. Einen Schwerpunkt bildet dabei die thematische Aufbereitung der Suchanfragen durch das Ontologie-System sowie Aspekte des Einsatzes und der Verwaltung von Ontologien. Abschließend werden aktuell laufende Entwicklungen in der Projektphase III skizziert

Personalized environmental service configuration and delivery orchestration: The PESCaDO demonstrator

Citizens are increasingly aware of the influence of environmental and meteorological conditions on the quality of their life. This results in an increasing demand for personalized environmental information, i.e., information that is tailored to citizens’ specific context and background. In this demonstration, we present an environmental information system that addresses this demand in its full complexity in the context of the PESCaDO EU project. Specifically, we will show a system that supports submission of user generated queries related to environmental conditions. From the technical point of view, the system is tuned to discover reliable data in the web and to process these data in order to convert them into knowledge, which is stored in a dedicated repository. At run time, this information is transferred into an ontology-based knowledge base, from which then information relevant to the specific user is deduced and communicated in the language of their preference