CAJ | 학술논문

E-Science关注数字环境下的科研活动，然而随着生物医学大数据的爆发，数据密集型科学研究为e-Science带来了新的挑战。科学工作流通过形式化科学计算的流程，支持在一个专门的程序环境下自动协调多任务多步骤的处理，从而减少科研投入，提高科研效率。文章首先归纳并总结了科学工作流的相关定义，然后分析了当前主流的科学工作流系统，提出科学工作流处理如何应对密集的生物医学数据，并基于Taverna开展了生物医学领域的科学工作流实验。最后总结了科学工作流当前的研究现状和存在的一些问题。
E-Science관주수자배경하적과연활동，연이수착생물의학대수거적폭발，수거밀집형과학연구위e-Science대래료신적도전。과학공작류통과형식화과학계산적류정，지지재일개전문적정서배경하자동협조다임무다보취적처리，종이감소과연투입，제고과연효솔。문장수선귀납병총결료과학공작류적상관정의，연후분석료당전주류적과학공작류계통，제출과학공작류처리여하응대밀집적생물의학수거，병기우Taverna개전료생물의학영역적과학공작류실험。최후총결료과학공작류당전적연구현상화존재적일사문제。
E-Science focuses on the scientific activities under digital environment. However, with the burst of biomedical big data, data intensive scientific research brings the new chal enges to e-Science. Scientific workflow supports formalizing the flow of scientific computing, automatical y coordinates multi-task and multi-steps process under a special program environment for reducing cost and promoting efficiency. In this paper, we explicit the definition of scientific workflow and then analyze the main current scientific workflow systems, besides, we propose how to deal with intensive biomedical data within scientific workflow, and some experiments have been done by using Taverna workbench. Final y, we conclude state of art of current research and some problems in this field.