Design and Use of Anatomical Atlases for Radiotherapy

215 Pages·2014·8.42 MB·English

Dissertation
zur Erlangung des akademischen Grades
des Doktors der Naturwissenschaften
(Dr. rer. nat)
A Rule-Based Agent-Oriented Framework
for
Weakly-Structured Scienti(cid:28)c Work(cid:29)ows
eingereicht
am Institut f(cid:252)r Informatik
des Fachbereichs Mathematik und Informatik
der Freien Universit(cid:228)t Berlin
von
Zhili Zhao
Berlin, 2014
Gutachter:
Prof. Dr. Adrian Paschke
Department of Computer Science
Freie Universit(cid:228)t Berlin
Prof. Dr. Hans Weigand
Department of Information Systems and Management
Tilburg University
Tag der Disputation: 12. September 2014
ERKL˜RUNG/DECLARATION
Ich erkl(cid:228)re an Eides statt, dass ich die vorliegende Arbeit selbstst(cid:228)ndig verfasst,
anderealsdieangegebenenQuellen/Hilfsmittelnichtbenutzt,unddiedenbenutzten
Quellen w(cid:246)rtlich und inhaltlich entnommenen Stellen als solche kenntlich gemacht
habe.
I declare that I have authored this thesis independently, that I have not used other
than the declared sources/resources, and that I have explicitly marked all material
which has been quoted either literally or by content from the used sources.
Berlin, 29 July, 2014
Zhili Zhao

Abstract
Existingsolutionsforbusinesswork(cid:29)owsaswellasscienti(cid:28)cwork(cid:29)owsmainlyfo-
cusontheorchestratedandpre-structuredexecutionofcompute-intensiveanddata-
oriented tasks. On the contrary, this thesis explicitly considers Weakly-structured
Scienti(cid:28)cWork(cid:29)ows(WsSWFs),whichcontaingoal-orientedtasksthathavetomake
agile runtime decisions. They may involve interactions between multiple partici-
pants or have complicated logic to express scienti(cid:28)c policies and cater to dynamic
execution environments. In general, such WsSWFs not only need a rich process and
(domain-speci(cid:28)c) decision logic speci(cid:28)cation, but also require a (cid:29)exible execution
and human interaction.
The main research problem addressed in this thesis is the combination of the
rule-based knowledge representation with the agent technology for the purpose of
supporting the WsSWF execution from a technical perspective, and a Rule-based
Agent-oriented Framework (RbAF) is proposed.
The (cid:28)rst challenge is to describe work(cid:29)ows by declarative rules. This thesis
employs messaging reaction rules, which go beyond global Event-Condition-Action
(ECA)rulesandsupportperformingcomplexactionslocallywithincertaincontexts.
Basedonmessagingreactionrules,theRbAFo(cid:27)ersanevent-drivenarchitectureand
models complex work(cid:29)ow patterns with the rule-based Complex Event Processing
(CEP) technologies. In addition, a Concurrent Transaction Logic (CTR)-based for-
malsemanticswhichpreciselyde(cid:28)nestherule-basedwork(cid:29)owlanguageispresented.
The second challenge is the description of (domain-speci(cid:28)c) decision logic in
work(cid:29)ows. This thesis addresses the problem by exploiting bene(cid:28)ts of both Logic
Programming (LP) and Description Logic (DL). LP with derivation rules is more
expressive than typical Boolean expressions and also more understandable for do-
main experts. Moreover, the RbAF provides three ways to access domain-speci(cid:28)c
data encoded by Semantic Web technologies.
The third challenge is to support the (cid:29)exibility required by the WsSWFs. Be-
sides the rule-based process and decision logic speci(cid:28)cation, the RbAF employs
distributed rule-based agents as the work(cid:29)ow execution environment and supports
asynchronousinteractionbetweendistributedagents. Moreover,theRbAFcombines
two ways of the work(cid:29)ow composition: orchestration and choreography. Another
(cid:29)exible mechanism is to handle work(cid:29)ow exceptions at runtime based on a work(cid:29)ow
ontology structuring work(cid:29)ow resources.
One further challenge addressed in this thesis is to integrate human users into
the work(cid:29)ow execution. This thesis uses a human agent, which manages the life
cycle of human tasks and provides a Web interface for domain experts to operate
on human tasks. Human interaction also helps in handling exceptions that cannot
be automatically handled by the rule-based agents.
This thesis evaluates the RbAF from di(cid:27)erent perspectives. In contrast to three
prominent scienti(cid:28)c work(cid:29)ow systems, the rule-based work(cid:29)ow speci(cid:28)cation of this
thesis shows higher expressive power with respect to the work(cid:29)ow patterns that are
important for scienti(cid:28)c work(cid:29)ows. With respect to domain knowledge representa-
tion, the analysis results indicate that general (domain-speci(cid:28)c) decision logic in
the WsSWFs can be represented by normal logic programs, which support negation
and are more expressive than propositional and (cid:28)nite logic programs. An expressive
query language for DL is employed and di(cid:27)erent reasoners can be easily con(cid:28)gured
in the RbAF to reason domain ontologies with di(cid:27)erent expressivity. In terms of
an empirical evaluation, the RbAF supports most of the typical properties of com-
putational models, including di(cid:27)erent forms of execution cycles, non-deterministic
execution branches, parallel and concurrent execution, distributed computation and
asynchronouscommunication. Moreover, anexperimentalevaluationbasedonthree
real-world WsSWF use cases is also given to analyze the performance and demon-
strate the expressive power of the domain knowledge representation in the RbAF.
This thesis concludes that the RbAF provides both an expressive work(cid:29)ow descrip-
tion and a (cid:29)exible work(cid:29)ow execution environment, and meets requirements of the
WsSWFs (except provenance).
Keywords: scienti(cid:28)c work(cid:29)ows; weakly-structured processes; multi-agent sys-
tems; semantic web; logic programming; event-driven execution; user interaction
Acknowledgments
I would like to express my sincere gratitude to everyone who contributed to the
completion of this thesis. All of you made my study in Berlin so wonderful!
First and foremost, I would like to thank Prof. Dr. Adrian Paschke for supervis-
ing me in the past four years. Thanks for all your suggestions for my presentations
and papers. Without your advice and patience, this thesis would have never been
possible. I really appreciate everything you have done for me.
I am pleased to have Prof. Dr. Hans Weigand as the second examiner of my
thesis. I was impressed by your sincerity and amiability when I saw you at the
VMBOworkshopin2014forthe(cid:28)rsttime. Ialsowouldliketoexpressmygratitude
to Prof. Dr. Ruisheng Zhang. Although I left your group after my master study,
you still gave me a lot of valuable advice during my PhD study.
I am thankful to my present and past group members from all over the world for
interesting discussions and for sharing with me PhD student experience; Kia Tey-
mourian, Ralph Sch(cid:228)fermeier, Alexandru Todor, Shashishekar Ramakrishna, Mo-
hammed Almashraee, Marko Harasic, Mario Rothe, G(cid:246)khan Coskun, Ralf Heese,
Markus Luczak-R(cid:246)sch and Olga Streibel. In particular, I thank Shashishekar Ra-
makrishna for numerous hours of technical discussions on weekends.
Furthermore, I am thankful to Jialu Hu and Hui Yu for providing signi(cid:28)cant use
cases to evaluate my work. Without your patient explanation I could not identify
these use cases from your research domains and use them in my work. I really
appreciate it.
I also would like to thank my friends who I knew before and during my PhD
study; Dr. Lili Jiang, Zhen Dong, Dr. Jiazao Lin, Dr. Yi Yang, Kai Zhang, Hong
Zhang, Bin Zhang, Ting He, Tao Liao, Miaomiao Zhu, Yubin Zhao, Yuan Yang, Dr.
Rongjing Hu, Fan Ding, Jiaxuan Wei and Dr. Xiaoliang Fan. It is amazing to know
you and our friendship is the most precious wealth in my life! In particular, I thank
Dr. Jiazao Lin for encouraging me a lot in the most di(cid:30)cult time of my PhD study.
I also would like to give my gratitude to the (cid:28)nancial support of China Scholar-
ship Council (CSC) and Corporate Semantic Web (CSW) work group.
I am grateful to my family, especially to my parents, for always supporting and
encouraging me.
Finally, I deep gratitude my girlfriend Ying Li for always being there, although
we were not together most of the time.
Zhili Zhao, in Berlin

Contents
List of Figures xiii
List of Tables xv
List of Abbreviations xvii
1 Introduction 1
1.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Thesis Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.5 Literature Connections . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
I Background and State-of-the-Art 9
2 Background 11
2.1 Scienti(cid:28)c Work(cid:29)ows . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Scienti(cid:28)c Work(cid:29)ow Life Cycle . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Work(cid:29)ow Management Systems . . . . . . . . . . . . . . . . . . . . . 14
2.4 Scienti(cid:28)c vs. Business Work(cid:29)ows . . . . . . . . . . . . . . . . . . . . 15
2.5 Weakly-Structured Scienti(cid:28)c Work(cid:29)ows . . . . . . . . . . . . . . . . 18
2.5.1 Structured vs. Unstructured Processes . . . . . . . . . . . . . 18
2.5.2 WsSWF Examples . . . . . . . . . . . . . . . . . . . . . . . . 19
2.5.3 WsSWF Features . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.5.4 WsSWF Main Requirements . . . . . . . . . . . . . . . . . . . 27
2.6 Work(cid:29)ow Description-Related Technologies . . . . . . . . . . . . . . 27
2.7 Imperative vs. Declarative Programming . . . . . . . . . . . . . . . . 29
2.8 Logic Program Overview . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.9 Deductive, Abductive and Inductive Reasoning . . . . . . . . . . . . 35
2.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3 Flexible Work(cid:29)ow Compositions 39
3.1 Classic Work(cid:29)ow Languages . . . . . . . . . . . . . . . . . . . . . . . 39
3.2 Agent-Oriented Work(cid:29)ow Compositions . . . . . . . . . . . . . . . . 41
3.3 Rule-Based Work(cid:29)ow Languages . . . . . . . . . . . . . . . . . . . . 44
3.4 Main Scienti(cid:28)c Work(cid:29)ow Languages . . . . . . . . . . . . . . . . . . 46
3.5 E(cid:27)orts on Weakly-Structured Work(cid:29)ows . . . . . . . . . . . . . . . . 48
3.6 Semantic-Based Work(cid:29)ow Compositions . . . . . . . . . . . . . . . . 49
3.6.1 Semantic Web Services . . . . . . . . . . . . . . . . . . . . . . 50
x Contents
3.6.2 Ontology-Based Work(cid:29)ow Speci(cid:28)cations . . . . . . . . . . . . 52
3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
II Conceptual Framework 57
4 Rule-Based Agent-Oriented Framework 59
4.1 Hierarchy of the Rule-Based Work(cid:29)ow Speci(cid:28)cation . . . . . . . . . . 62
4.2 Upper-Level Work(cid:29)ow Ontology . . . . . . . . . . . . . . . . . . . . . 62
4.3 Declarative Work(cid:29)ow Speci(cid:28)cation . . . . . . . . . . . . . . . . . . . 64
4.3.1 Reaction Rules . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3.2 Event-Driven Work(cid:29)ow Execution . . . . . . . . . . . . . . . 67
4.3.3 CEP-Based Work(cid:29)ow Pattern Modeling . . . . . . . . . . . . 68
4.4 Domain Decision-Centric Logic Description . . . . . . . . . . . . . . 72
4.4.1 Derivation Rules . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.2 Semantic Web Data Query . . . . . . . . . . . . . . . . . . . 75
4.5 Integrating Orchestration with Choreography . . . . . . . . . . . . . 78
4.6 Human Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.7 Exception Handling. . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5 Formal Work(cid:29)ow Representation 85
5.1 Work(cid:29)ow Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.2 CTR Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.3 Work(cid:29)ow Representation Using CTR . . . . . . . . . . . . . . . . . . 91
5.3.1 Work(cid:29)ow Representation . . . . . . . . . . . . . . . . . . . . 91
5.3.2 Multiple Instances . . . . . . . . . . . . . . . . . . . . . . . . 94
5.3.3 Reactive Logic Representation. . . . . . . . . . . . . . . . . . 94
5.4 Communication between Processes . . . . . . . . . . . . . . . . . . . 96
5.5 Complex Event Processing . . . . . . . . . . . . . . . . . . . . . . . . 97
5.6 Exception Handling. . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
III Evaluation 103
6 Proof-of-Concepts 105
6.1 Prova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
6.2 The Work(cid:29)ow Ontology . . . . . . . . . . . . . . . . . . . . . . . . . 106
6.3 Mapping the CTR-Based Work(cid:29)ow Logic to Prova . . . . . . . . . . 108
6.4 Domain Logic Expression in Prova . . . . . . . . . . . . . . . . . . . 113
6.5 Enterprise Service Bus Mule . . . . . . . . . . . . . . . . . . . . . . . 116
6.5.1 Prova Agent Deployment . . . . . . . . . . . . . . . . . . . . 117
6.5.2 Mule ESB as Communication Middleware . . . . . . . . . . . 119
6.5.3 Translations between Reaction RuleML and Prova . . . . . . 120