NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings

Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we argue that effort to developing service descriptions, request translations, and matching mechanisms could be reduced using unrestricted natural language; allowing both: (1) end-users to intuitively express their needs using natural language, and (2) service developers to develop services without relying on syntactic/semantic description languages. Although there are some natural language-based service composition approaches, they restrict service retrieval to syntactic/semantic matching. With recent developments in Machine learning and Natural Language Processing, we motivate the use of Sentence Embeddings by leveraging richer semantic representations of sentences for service description, matching and retrieval. Experimental results show that service composition development effort may be reduced by more than 44\% while keeping a high precision/recall when matching high-level user requests with low-level service method invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on Services Computing) on July 1

KCDC - The KASCADE Cosmic-ray Data Centre

KCDC, the KASCADE Cosmic-ray Data Centre, is a web portal, where data of astroparticle physics experiments will be made available for the interested public. The KASCADE experiment, financed by public money, was a large-area detector for the measurement of high-energy cosmic rays via the detection of air showers. KASCADE and its extension KASCADE-Grande stopped finally the active data acquisition of all its components including the radio EAS experiment LOPES end of 2012 after more than 20 years of data taking. In a first release, with KCDC we provide to the public the measured and reconstructed parameters of more than 160 million air showers. In addition, KCDC provides the conceptional design, how the data can be treated and processed so that they are also usable outside the community of experts in the research field. Detailed educational examples make a use also possible for high-school students and early stage researchers.Comment: 8 pages, accepted proceeding of the ECRS-symposium, Kiel, 201