基于过程挖掘的科学工作流交互式构建

doi:10.16182/j.issn1004731x.joss.21-0151

摘要/Abstract

摘要：

传统的交互式工作流构建方法在处理规模较大或流程复杂的工作流时构建效率较低。为此，提出了一种基于过程挖掘的工作流构建方法，采用启发式问答方式收集记录流程片段，通过特别设计的关系描述语言以实现工作流中不同层级和不同环节的过程描述，由描述文本转译生成的流程关系数据被输出到过程发现算法中，从而生成健全的工作流网络。实现了一套交互式工作流构建工具，并在科学工作流案例中进行了测试，验证了方法的有效性，在与其它方法相对比时表现出更佳的交互效率。

关键词: 科学工作流, 工作流构建, 过程挖掘, 关系描述语言, 人机交互

Abstract:

When dealing with large-scale or complex workflows, the construction efficiency of traditional interactive workflow construction methods is very low. To solve this problem, a workflow construction method based on process mining is proposed. Heuristic methods are used to collect process fragments. The specially designed relation description language is used to record the process description of different levels and aspects in the workflow as text. The text is translated to generate process relational data, which will be output to the process discovery algorithm to generate a sound workflow network. An interactive workflow construction software has been developed and tested in scientific workflow cases to verify the effectiveness of this method and show better interactive efficiency compared with other methods.

Key words: scientific workflow, workflow modeling, process mining, relation description language, human-computer interaction

中图分类号:

TP391

刘俊, 高阳, 徐涛, 赵青, 单桂华, 迟学斌. 基于过程挖掘的科学工作流交互式构建[J]. 系统仿真学报, 2022, 34(7): 1547-1558.

Jun Liu, Yang Gao, Tao Xu, Qing Zhao, Guihua Shan, Xuebin Chi. Interactive Construction of Scientific Workflow Based on Process Mining[J]. Journal of System Simulation, 2022, 34(7): 1547-1558.

图/表 9

图1

图2

图3

表1

流程关系挖掘推理条件列表

条件	结果
$a ∨ b$ 且 $a ⇒ c$	$b ⇒ c$
$a ∨ b$ 且 $c ⇒ a$	$c ⇒ b$
$a ∨ b$ 且 $a ∧ c$	$b ∧ c$
$a ∨ b$ 且 $a ∨ c$	$b ∨ c$
在同一条跟随语句中 $a ∧ b$ 且 $a ⇒ c$	$b ⇒ c$
在同一条跟随语句中 $a ∧ b$ 且 $c ⇒ a$	$c ⇒ b$

表1

图4

图5

图6

图7

图8

参考文献 32

1	Hull Duncan, Wolstencroft Katy, Stevens Robert, et al.Taverna: A Tool for Building and Running Workflows of Services[J]. Nucleic Acids Research (S0305-1048), 2006, 34(2): 729-732.
2	Ludäscher Bertram, Altintas Ilkay, Berkley Chad, et al.Scientific Workflow Management and the Kepler System[J]. Concurrency and Computation: Practice and Experience (S1532-0626), 2006, 18(10): 1039-1065.
3	Jalili V, Afgan E, Gu Q, et al. The Galaxy Platform for Accessible, Reproducible and Collaborative Biomedical Analyses: 2020 Update[J]. Nucleic Acids Research (S0305-1048), 2020, 48(W1): 395-402.
4	Hofmann, M, Klinkenberg R. RapidMiner: Data Mining Use Cases and Business Analytics Applications[M].United Kingdom: Chapman and Hau/CRC, 2016: 343-372.
5	Berthold, M, Cebron N R., Dill F, et al. KNIME-the Konstanz Information Miner: Version 2.0 and Beyond[J]. AcM SIGKDD Explorations Newsletter (S1931-0145), 2009, 11(1): 26-31.
6	Ivanchikj A, & Pautasso C. Sketching Process Models by Mining Participant Stories[C]// International Conference on Business Process Management. Vienna,Austria: BPM, 2019: 3-19.
7	Cook J, Wolf A. Discovering Models of Software Processes From Event-Based Data[J]. ACM Transactions on Software Engineering and Methodology (S1557-7392), 1998, 7(3): 215-249.
8	Murata, Tadao.Petri Nets: Properties, Analysis and Applications[J]. IEEE (S0018-9219), 1989, 77(4): 541-580.
9	Van der Aalst, Wil MP.The Application of Petri Nets to Workflow Management[J]. Journal of Circuits, Systems, and Computers (S0218-1266), 1998, 8(1): 21-66.
10	Fettke Peter. Business Process Modeling Notation[J].Wirtschaftsinformatik und Angewandte Informatik (S0937-6429), 2008, 50(6): 504-507.
11	Van der Aalst W. Causal Nets: A Modeling Language Tailored towards Process Discovery[C]// International Conference on Concurrency Theory. Aachen, Germany: Springer-Verlag, 2011: 28-42.
12	La Rosa M, Reijers H A, Van Der Aalst W M, et al.APROMORE: an Advanced Process Model Repository[J]. Expert Systems With Applications (S0957-4174), 2011, 38(6): 7029-7040.
13	Damij Nadja. Business Process Modelling Using Diagrammatic and Tabular Techniques[J]. Business Process Management Journal (S1463-7154), 2007, 13(1):70-90.
14	Ellson J, Gansner E, Koutsofios L, et al. Graphviz—Open Source Graph Drawing Tools[C]// International Symposium on Graph Drawing. Vienna,Austria:GD, 2001: 483-484.
15	Bergenthum Robin, Desel Jörg, Mauser Sebastian, and Lorenz Robert. Construction of Process Models from Example Runs[J]. Transactions on Petri Nets and Other Models of Concurrency (S1867-7193), 2009, 2(1):243-259.
16	Fahland Dirk. Oclets-Scenario-Based Modeling with Petri Nets[C]// Int'l Conference on Applications and Theory of Petri Nets. Paris, France: LNCS, 2009: 223-241.
17	Weijters A J, Van der Aalst W M. Rediscovering Workflow Models from Event-based Data using Little Thumb[J].Integrated Computer-Aided Engineering (S1069-2509), 2003, 10(2): 151-162.
18	Dixit P M, Verbeek H M W, Buijs J C, et al.Interactive Data-driven Process Model Construction[C]//International Conference on Conceptual Modeling, Xian, China: CCF, 2018: 251-265.
19	Weijters A., van der Aalst W..Rediscovering workflow models from event-based data[C]// 11th Dutch-Belgian Conference of Machine Learning. Antwerp,Belgium:Benelearn, 2001: 93-100.
20	Herbst J, Karagiannis D. An Inductive Approach to the Acquisition and Adaptation of Workflow Models[C]// IJCAI'99 Workshop on Intelligent Workflow and Process Management: The New Frontier for AI in Business. Stockhdm, Sweden, 1999: 52-57.
21	Agrawal R., Gunopulos D., Leymann F..Mining Process Models from Workflow logs[C]// 6th Int. Conf. Extending Database Technology (EDBT). Valencia, Spain: Springer, 1998: 467-483.
22	van der Aalst W, Weijters T, Maruster L.Workflow Mining: Discovering Process Models from Event Logs[J].IEEE Trans. Knowl. Data Eng. (S1041-4347), 2004, 16(1): 1128-1142.
23	Guo Q., Wen L., Wang J., et al. Mining Invisible Tasks in Non-Free-Choice Constructs[C]//International Conference on Business Process Management. Innsbruck, Australia 2015: 109-125.
24	Augusto A, Conforti R, Dumas M, et al. Automated Discovery of Structured Process Models From Event Logs: The Discover-and-Structure Approach[J]. Data and Knowledge Engineering (S0169-023X), 2018, 117(1): 373-392.
25	Weijters A, Ribeiro J. Flexible Heuristics Miner (FHM)[C]//IEEE Symposium on Computational Intelligence and Data Mining, Paris, France BETA, 2011: 310-317.
26	Mannhardt F., de Leoni M., Reijers H. A., et al. Data-Driven Process Discovery-Revealing Conditional Infrequent Behavior from Event Logs[C]// International Conference on Advanced Information Systems Engineering. Essen, Germany Springer, Cham, 2017: 545-560.
27	van Zelst S, van Dongen B, van der Aalst W, et al.Discovering Workflow Nets Using Integer Linear Programming[J]. Computing (S0010-485X), 2017, 100(5):1-28.
28	Leemans S. J. J., Fahland D., Aalst W. M. P. van der.Discovering Block-Structured Process Models from Event Logs-a Constructive Approach[C]// PETRI NETS'13 34th International Conference on Application and Theory of Petri Nets and Concurrency, Milan, Italy: Springer-Verlag, 2013: 311-329.
29	Leemans S. J. J., Fahland D., van der Aalst W. M. P..Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour[C]// Business Process Management Workshops-BPM 2013 International Workshops. Beijing, China, 2014: 66-78.
30	de Medeiros A K A, Weijters A J, van der Aalst W M.Genetic Process Mining: An Experimental Evaluation[J]. Data Mining and Knowledge Discovery (S1384-5810), 2007, 14(2): 245-304.
31	Buijs B J C, van Dongen F., van der Aalst W M.Quality Dimensions in Process Discovery: The Importance of Fitness, Precision, Generalization and Simplicity[J].International Journal of Cooperative Information Systems (S0218-8430), 2014, 23(1): 100-144.
32	张裕, 牛北方.一种轻量级分布式作业管理系统的设计与实现[J]. 科研信息化技术与应用, 2019, 10(1): 31-37.
	Zhang Yu, Niu Beifang. Design and Implementation of a Lightweight Distributed Job Management System[J]. E-science Technology & Application, 2019, 10(1): 31-37.

[1]	卢柏宏, 赵建军, 刘戈三. 电影虚拟摄影半实物仿真的研究与实现[J]. 系统仿真学报, 2021, 33(8): 1938-1946.
[2]	郭园, 童倩倩, 郑宇铠, 王子琦, 张玉茹, 王党校. 融合多元触觉和沉浸式视觉的可移植VR软件框架[J]. 系统仿真学报, 2020, 32(7): 1385-1392.
[3]	薛艳萍, 王学松, 武仲科, 王醒策, 周明全. Myo手势识别方法在古建筑漫游系统中的应用[J]. 系统仿真学报, 2019, 31(9): 1907-1915.
[4]	吴佳佳, 刘箴, 许辉煌, 刘婷婷, 王瑾, 柴艳杰. 面向康复训练的严肃游戏人机交互设计[J]. 系统仿真学报, 2019, 31(5): 909-918.
[5]	朱晓强, 潘虹艺, 徐浩, 宋磊, 朱梦尧, 王向阳. 头戴设备VR环境下光滑加权等距面交互建模[J]. 系统仿真学报, 2018, 30(7): 2459-2464.
[6]	王志文, 张子豪, 贾玉祥, 魏毅, 沈燕飞. 基于语音识别控制的人体运动仿真[J]. 系统仿真学报, 2018, 30(11): 4203-4209.
[7]	韩亮, 公璇, 王江云, 杜阳华. 跳伞模拟器人机交互可视化功能研究[J]. 系统仿真学报, 2017, 29(8): 1747-1752.
[8]	卢浩然, 张宇, 牛苗苗, 税午阳, 周明全. 基于Leap motion的三维文物虚拟拼接方法[J]. 系统仿真学报, 2015, 27(12): 3006-3011.