More than ever, reducing the cost of data integration by efficiently evaluating queries is an important challenge, given that today the economic cost in computing cycles (see your cloud invoice); and in energy consumption and the performance required for some critical tasks have become important. Besides, new applications require solving even more complex queries including millions of sources, and data with high levels of volume and variety. These new challenges call for intelligent processes that can learn from previous experiences, that can be adaptable to changing requirements and dynamic execution contexts.
This workshop follows a first successful edition in conjunction with ICSOC 2019 in Toulouse that led to a vivid program with interesting discussion (https://straps-workshop.github.io/2019/). The second edition of the workshop STRAPS aims at promoting scientific discussion on the way data produced under different conditions can be efficiently integrated to answer simple, relational, analytical queries. These queries must cope to quality preferences associated with providers, algorithms and data trust. New scales in volume, velocity and value associated with integrated data collections require adapted solutions providing computing, storage and processing services potentially deployed on different highly distributed infrastructures and target architectures. With service, data and algorithms stemming from different and potentially huge numbers of providers, properties like provenance, quality and trust, arise as key properties to be quantified, evaluated and exposed to data consumers. How can data integration in such conditions be smart? This is the key question to be discussed by workshop participants.
Underlying approaches and algorithms continue to evolve particularly given the new levels of volume, velocity and value associated with data. Contemporary infrastructures for dealing with data are deployed in heterogeneous target architectures like cloud, multi-cloud, Internet of Things consisting of sensors and server farms deployed around the world. These infrastructures go beyond classic data management solutions and evolve towards different stacks configurations (data processing systems “a la carte”). They need to cope with new notions of scalability and of resources consumption guided by economic models, service level agreements and other quality warranties.
The workshop STRAPS aims at promoting scientific discussion on the way data stemming from different providers and produced under different conditions can be efficiently integrated to answer simple, relational, analytical queries ensuring providers, algorithms and data trust.
We invite the submission of work-in-progress research addressing various aspects of data integration and processing done in service-based infrastructures. The workshop welcomes submissions of technical, experimental, methodological papers, application papers, and papers on experience reports in real-life application settings addressing – though not limited to – the following topics:
We expect papers written in English between 8 and 12 Springer’s LNCS pages long ( Springer LNCS format), including references and Illustrations. Electronic submissions in PDF format can be proposed at the conference workshops submission site.
Submission of a paper should be regarded as an undertaking that, should the paper be accepted, at least one of the authors will register and attend the workshop to present the paper. Registration is subject to the terms and conditions of ICSOC.
A selected number of papers will be invited to be submitted as extended versions to be published in an edition of Proceedings series « Advances in Computer Science Research ».