The growing popularity of Web applications and the Internet of Things cause an urgent need for modern scalable data management to cope with large amounts of data. In the environmental domain these problems also need a solution because of big data coming from a large amount of sensors or users (e.g. crowdsourcing applications). This paper presents an architecture that uses a microservice approach to create a data management backend for the mentioned applications. The main concept shows that microservices can be used to define separate services for different data types and management tasks. This separation leads to many advantages such as better scalability and low coupling between different features. Two prototypes, which are already implemented, are evaluated in this paper.

Abstract. This paper describes a universal approach to the development of a cross-platform and multi-functional environmental mobile application. According to the Pareto principle [1] only common use cases are implemented and can be described in a lightweight description format instead of being explicitly programmed. These use cases include information about the environment ("my environment"), reporting of environmental data ("crowd sourcing"), and environmental experience ("electronic nature guide"). IntroductionEvery month users of mobile devices are facing many new applications. Those can be used to access information of their interest in almost any place and situation using context information such as current position and time. People use apps for localized weather forecasts, travel information (including delays), news, stock quotes, etc., and maybe even provide information by themselves, implicitly by allowing apps to send location and speed (traffic flow) information back to service providers or explicitly by reporting their own observations via a crowdsourcing application. At least in Europe authorities are committed to actively provide environmental information to the public [2]. For that reason many environmental information systems (EIS) do implement web frontends, web services, or even service oriented architectures and it is relatively easy to use these for the implementation of mobile frontends, e.g. mobile apps.The range of environmental information provided varies from unstructured data, like text documents and media files, up to structured and semi-structured information, like tabular data, spatial data, metadata, time series, charts, and also includes specialized information for specific applications. Nevertheless, although data is very diverse some recurring usage patterns can be observed.In [3] and [4] a descriptive approach of a universal mobile application accessing EIS based on extended OpenSearch descriptions, outlined in section 2, was presented.

Abstract. The provision of accurate, comprehensive and condensed information contained in distributed environmental information systems via public search interfaces raises several technological challenges. Our approach to tackle these challenges is based on a consequent use of ontologies. Starting with an analysis of requirements resulting from semantic search scenarios, we explain the advantages of using ontologies based on standards and aim to reuse and transform terminological systems available in the environmental domain into ontologies. We develop an architecture guided by the premise of exerting a minimum of influence on existing search infrastructures. As a consequence of using a (possibly large) number of ontologies, tools for ontology management are needed. A key argument for using ontologies is that nowadays -as an outcome of the Semantic Web initiative -very powerful processing tools are available. We elaborate ontology mapping as an example and outline how a comprehensive ontology management can be achieved.

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