Process Design for Natural Scientists [electronic resource] : An Agile Model-Driven Approach / edited by Anna-Lena Lamprecht, Tiziana Margaria.
Contributor(s): Lamprecht, Anna-Lena [editor.] | Margaria, Tiziana [editor.] | SpringerLink (Online service).
Material type:
BookSeries: Communications in Computer and Information Science: 500Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014Description: X, 253 p. 129 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662450062.Subject(s): Computer science | Software engineering | Computers | Database management | Computer simulation | Computer Science | Models and Principles | Software Engineering | Simulation and Modeling | Information Systems Applications (incl. Internet) | Database ManagementAdditional physical formats: Printed edition:: No titleDDC classification: 005.743 Online resources: Click here to access online
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Springer eBooksSummary: This book presents an agile and model-driven approach to manage scientific workflows. The approach is based on the Extreme Model Driven Design (XMDD) paradigm and aims at simplifying and automating the complex data analysis processes carried out by scientists in their day-to-day work. Besides documenting the impact the workflow modeling might have on the work of natural scientists, this book serves three major purposes: 1. It acts as a primer for practitioners who are interested to learn how to think in terms of services and workflows when facing domain-specific scientific processes. 2. It provides interesting material for readers already familiar with this kind of tools, because it introduces systematically both the technologies used in each case study and the basic concepts behind them. 3. As the addressed thematic field becomes increasingly relevant for lectures in both computer science and experimental sciences, it also provides helpful material for teachers that plan similar courses.
This book presents an agile and model-driven approach to manage scientific workflows. The approach is based on the Extreme Model Driven Design (XMDD) paradigm and aims at simplifying and automating the complex data analysis processes carried out by scientists in their day-to-day work. Besides documenting the impact the workflow modeling might have on the work of natural scientists, this book serves three major purposes: 1. It acts as a primer for practitioners who are interested to learn how to think in terms of services and workflows when facing domain-specific scientific processes. 2. It provides interesting material for readers already familiar with this kind of tools, because it introduces systematically both the technologies used in each case study and the basic concepts behind them. 3. As the addressed thematic field becomes increasingly relevant for lectures in both computer science and experimental sciences, it also provides helpful material for teachers that plan similar courses.
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