Adaptive Scalable Analytics Platform

Get in Touch

• Join us at the BDVA Summit of the Big Data Value Association in Valencia, Spain (Nov 30 – Dec 2), where the ASAP project and the webLyzard Web intelligence platform will be presented.
• TEDx Modul University presentation of visual tools to analyze global communication flows, including charts and temporal controls for statistical indicators developed within ASAP.
• Prof. Arno Scharl from webLyzard technology represented ASAP at the SME Workshop of the ICT Proposers’ Day in Bratislava, Slovakia (26-27 Sep 2016).
• Track the latest news from the ASAP project by following our Twitter account @ASAP_EU.
• E-Mail us at info@asap-fp7.eu – we look forward to your feedback.

ASAP Overview

The ASAP FP7 research project developed a dynamic open-source execution framework for scalable data analytics. The underlying idea was that no single execution model is suitable for all types of tasks, and no single data model (and store) is suitable for all types of data. Complex analytical tasks over multi-engine environments therefore require integrated profiling, modeling, planning and scheduling functions.

Project Goals

To facilitate the building and execution of complex analytics workflows, the ASAP project pursued four main goals:

• A generic task-parallel programming model in conjunction with two runtime systems for distributed or parallel execution in the cloud. The runtimes include state-of-the-art features such as irregular general-purpose computations, resource elasticity, synchronization, data-transfer, locality and scheduling abstraction, the ability to handle large sets of irregularly distributed data, and fault-tolerance.
• A modeling framework that constantly evaluates the cost, quality and performance of available computational resources in order to decide on the most advantageous store, indexing and execution pattern.
• An adaptation methodology to enable analytics experts to amend submitted workflows by changing or modifying a workflow while it is being processed. Users can change the parameters of operators already comprised in the workflow, or the structure of the workflow by removing or adding operators.
• A visual analytics dashboard to show query results and metadata in an intuitive manner, with special focus on the interactive exploration of datasets, dynamic temporal controls, on-the-fly query refinement mechanisms, and the geospatial projection of structured and unstructured data.

The generic nature of the ASAP architecture supports a wide range of different tasks. Within the project, the consortium focused on the real-time analysis of Web content and telecommunications data. Currently extended as part of the EVOLVE big data project (Horizon 2020) and applied to a range of different use cases such as agriculture, mobility and maritime services, the content processing capabilities will also form the basis for planned Horizon Europe submissions.