Life Science Workflow Services (LifeSWS): Motivations and Architecture

Reza Akbarinia, Christophe Botella, Alexis Joly, Florent Masseglia, Marta Mattoso, Eduardo Ogasawara, Daniel de Oliveira, Esther Pacitti, Fabio Porto, Christophe Pradal, Dennis Shasha, Patrick Valduriez

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Data driven science requires manipulating large datasets coming from various data sources through complex workflows based on a variety of models and languages. With the increasing number of big data sources and models developed by different groups, it is hard to relate models and data and use them in unanticipated ways for specific data analysis. Current solutions are typically ad-hoc, specialized for particular data, models and workflow systems. In this paper, we focus on data driven life science and propose an open service-based architecture, Life Science Workflow Services (LifeSWS), which provides data analysis workflow services for life sciences. We illustrate our motivations and rationale for the architecture with real use cases from life science.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Science and Business Media Deutschland GmbH
Pages1-24
Number of pages24
DOIs
StatePublished - 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14280 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Data driven science
  • Data science
  • Life science
  • Model life cycle
  • Service-based architecture
  • Workflows

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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