TY - CHAP T1 - Definition of the DISPEL Language T2 - THE DATA BONANZA: Improving Knowledge Discovery for Science, Engineering and Business Y1 - 2013 A1 - Paul Martin A1 - Yaikhom, Gagarine ED - Malcolm Atkinson ED - Rob Baxter ED - Peter Brezany ED - Oscar Corcho ED - Michelle Galea ED - Parsons, Mark ED - Snelling, David ED - van Hemert, Jano KW - Data Streaming KW - Data-intensive Computing KW - Dispel AB - Chapter 10: "Definition of the DISPEL language", describes the novel aspects of the DISPEL language: its constructs, capabilities, and anticipated programming style. JF - THE DATA BONANZA: Improving Knowledge Discovery for Science, Engineering and Business T3 - {Parallel and Distributed Computing, series editor Albert Y. Zomaya} PB - John Wiley & Sons Inc. ER - TY - JOUR T1 - Data-Intensive Architecture for Scientific Knowledge Discovery JF - Distributed and Parallel Databases Y1 - 2012 A1 - Atkinson, Malcolm P. A1 - Chee Sun Liew A1 - Michelle Galea A1 - Paul Martin A1 - Krause, Amrey A1 - Adrian Mouat A1 - Oscar Corcho A1 - Snelling, David KW - Knowledge discovery, workflow management system AB - This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology. VL - 30 UR - http://dx.doi.org/10.1007/s10619-012-7105-3 IS - 5 ER - TY - RPRT T1 - Dispel Tutorial Y1 - 2012 A1 - Paul Martin KW - Dispel AB - Dispel is a strongly-typed imperative language for generating executable workflows for data-intensive distributed applications, particularly (but not exclusively) for use in computational sciences such as bioinformatics, astronomy and seismology — it has been designed to be a portable lingua franca by which researchers can interact with complex distributed research infrastructures without detailed knowledge of the underlying computational middleware, all in order to more easily conduct experiments in data integration, simulation and data-intensive modelling. This document is a tutorial for Dispel. ER - TY - CHAP T1 - DISPEL Reference Manual T2 - Advanced Data Mining and Integration Research for Europe (ADMIRE) Y1 - 2011 A1 - Paul Martin A1 - Yaikhom, Gagarine KW - DISPEL, ADMIRE AB - Reference manual for the Data Intensive Systems Process Engineering Language (DISPEL). JF - Advanced Data Mining and Integration Research for Europe (ADMIRE) UR - www.admire-project.eu ER - TY - RPRT T1 - EDIM1 Progress Report Y1 - 2011 A1 - Paul Martin A1 - Malcolm Atkinson A1 - Parsons, Mark A1 - Adam Carter A1 - Gareth Francis AB - The Edinburgh Data-Intensive Machine (EDIM1) is the product of a joint collaboration between the data-intensive group at the School of Informatics and EPCC. EDIM1 is an experimental system, offering an alternative architecture for data-intensive computation and providing a platform for evaluating tools for data-intensive research; a 120 node cluster of ‘data-bricks’ with high storage yet modest computational capacity. This document gives some background into the context in which EDIM1 was designed and constructed, as well as providing an overview of its use so far and future plans. ER -