No abstract

In the last decade, stream processing has become a very active research domain motivated by the growing number of stream-based applications. These applications make use of continuous queries, which are processed by a stream processing engine (SPE) to generate timely results given the ephemeral input data. Variations of input data streams, in terms of both volume and distribution of values, have a large impact on computational resource requirements. Dynamic and Automatic Balanced Scaling for Storm (DABS-Storm) is an original solution for handling dynamic adaptation of continuous queries processing according to evolution of input stream properties, while controlling the system stability. Both fluctuations in data volume and distribution of values within data streams are handled by DABS-Storm to adjust the resources usage that best meets processing needs. To achieve this goal, the DABS-Storm holistic approach combines a proactive auto-parallelization algorithm with a latency-aware load balancing strategy.

The Functional Requirements for Bibliographic Records (FR-BR), an emerging model in the bibliographic domain, provide interesting possibilities in terms of cataloguing, representation and semantic enrichment of bibliographic data. However, the automated transformation of existing catalogs to fit this model is a requirement towards a wide adoption of FRBR in libraries. The cultural heritage community proposed a notable amount of FRBRization tools and projects, thus making it difficult for practitioners to compare and evaluate them. In this paper, we propose a synthetic and relevant classification of the FRBRization techniques according to specific criteria of comparison such as model expressiveness or specific enhancements.