E-CARGO and Role-Based Collaboration E-Book

Haibin Zhu

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: IEEE Series on Systems Science and Engineering
• Sprache: Englisch

Seitenzahl: 702

Veröffentlichungsjahr: 2021

Beschreibung

E-CARGO and Role-Based Collaboration A model for collaboratively solving complex problems E-CARGO and Role-Based Collaboration offers a unique guide that explains the nature of collaboration, explores an easy-to-follow process of collaboration, and defines a model to solve complex problems in collaboration and complex systems. Written by a noted expert on the topic, the book initiates the study of an effective collaborative system from a novel perspective. The role-based collaboration (RBC) methodology investigates the most important aspects of a variety of collaborative systems including societal-technical systems. The models and algorithms can also be applied across system engineering, production, and management. The RBC methodology provides insights into complex systems through the use of its core model E-CARGO. The E-CARGO model provides the fundamental components, principles, relationships, and structures for specifying the state, process, and evolution of complex systems. This important book: * Contains a set of concepts, models, and algorithms for the analysis, design, implementation, maintenance, and assessment of a complex system * Presents computational methods that use roles as a primary underlying mechanism to facilitate collaborative activities including role assignment * Explores the RBC methodology that concentrates on the aspects that can be handled by individuals to establish a well-formed team * Offers an authoritative book written by a noted expert on the topic Written for researchers and practitioners dealing with complex problems in collaboration systems and technologies, E-CARGO and Role-Based Collaboration contains a model to solve real world problems with the help of computer-based systems.

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E‐CARGO and Role‐Based Collaboration

Modeling and Solving Problems in the Complex World

Haibin Zhu

IEEE Press Series on Systems Science and EngineeringMengChu Zhou, Series Editor

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Author Biography

Dr. Haibin Zhu is a Full Professor and the Chair (July 2019–June 2021) of the Department of Computer Science and Mathematics, Founding Director of Collaborative Systems Laboratory, member of the University Budget Plan committee, Arts and Science Executive Committee, and the Research Committee, Nipissing University, Canada. He received a B.S. degree in computer engineering from the Institute of Engineering and Technology, China (1983), and M.S. (1988) and Ph.D. (1997) degrees in computer science from the National University of Defense Technology (NUDT), China. He was a visiting professor and a special lecturer in the College of Computing Sciences, New Jersey Institute of Technology, USA (1999–2002) and a lecturer, an associate professor and a full professor at NUDT (1988–2000). He has published or been accepted over 200 research works including 30 IEEE Transactions articles, five books, five book chapters, three journal issues, and three conference proceedings. He is the most productive author in the category of “Collaboration” https://ieeexplore.ieee.org/search/searchresult.jsp?newsearch=true&queryText=Collaboration.

He is a senior member of ACM, a full member of Sigma Xi, and a senior member of IEEE. He is serving as Associate Vice President, Systems Science and Engineering (SSE), and co‐chair of the technical committee of Distributed Intelligent Systems of IEEE Systems, Man and Cybernetics (SMC) Society, member of the SSE Technical Activity Committee, the Conferences and Meetings Committee, and the Electronic Communications Subcommittee of IEEE SMC Society, Associate Editor (AE) of IEEE Transactions on SMC: Systems, IEEE Transactions on Computational Social Systems, IEEE SMC Magazine, and IEEE Canada Review. He has been an active organizer for the annual IEEE Int’l Conf. on SMC since 2003, as Special Session Chair, Tutorial Chair, Area Co‐Chair, Social Media Co‐Chair, Web Co‐Chair, Poster Co‐Chair, Session Chair, and Special Session Organizer. He is the Publication Chair for the 1st IEEE Int’l Conf. of Human‐Machine Systems, Rome, Italy (Online due to COVID‐19), 7–9 September 2020 and a Poster Co‐Chair for the annual IEEE SMC Conference, Toronto, Canada (Online due to COVID‐19), 6–9 October 2020, was the Program Chair (PC) for 16th IEEE Int’l Conf. on Networking, Sensing and Control, Banff, AB, Canada, 8–11 May 2019. He is a PC Chair for 17th IEEE Int’l Conf. on Computer Supported Cooperative Work in Design, Dalian, China, 6–8 May 2020 (postponed due to COVID‐19), and was a PC Chair for 17th IEEE Int’l Conf. on Computer Supported Cooperative Work in Design, Whistler, BC, Canada, 27–29 June 2013. He also served as PC members for 120+ academic conferences.

He is the founding researcher of Role‐Based Collaboration and Adaptive Collaboration. He has offered over 70 invited talks including keynote and plenary talks on collaboration topics internationally, e.g. Canada, USA, China, UK, Germany, Turkey, Hong Kong, Macau, and Singapore. His research has been being sponsored by NSERC, IBM, DRDC, and OPIC.

He is the receipt of the meritorious service award from IEEE SMC Society (2018), the chancellor’s award for excellence in research (2011) and two research achievement awards from Nipissing University (2006, 2012), the IBM Eclipse Innovation Grant Awards (2004, 2005), the Best Paper Award from the 11th ISPE Int’l Conf. on Concurrent Engineering (ISPE/CE2004), the Educator’s Fellowship of OOPSLA’03, a 2nd class National Award for Education Achievement (1997), and three 1st Class Ministerial Research Achievement Awards from China (1997, 1994, and 1991).

His research interests include Collaboration Theory, Technologies, Systems, and Applications, Human‐Machine Systems, CSCW (Computer‐Supported Cooperative Work), Multi‐Agent Systems, Software Engineering, and Distributed Intelligent Systems.

Preface

This book was completed during the COVID‐19 pandemic, a difficult time when many of us struggled to play our routine roles without physical contact. Throughout this period, we saw a large transition toward online collaborative work. Interestingly, these online collaboration tools and platforms were built by the researchers and engineers in the collaboration field, or more exactly, the field of Computer‐Supported Cooperative Work (CSCW). Initially, CSCW was supposed to be the initial target field for Role‐Based Collaboration (RBC). Over the last 15 years, however, RBC has advanced far beyond the field of CSCW. The application of RBC now extends to all the cutting‐edge fields in the world, including production, services, management, system engineering, complex systems, cyber‐physical systems, big data, and Artificial Intelligence (AI).

During these challenging times, we are experiencing the dynamics and uncertainty of the world. This is natural, after all, the universe is infinite, various, and dynamic. In the human world, people have created many terms and concepts to describe and organize this world. Even for a language specialist, it is almost impossible to grasp all these terms in one’s lifetime. In this massive conceptual kingdom, there is a concept that has been used in common vocabulary since the early days of humanity. Despite this, there is no commonly accepted definition of the term even today. This term is “role.” Everyone understands the concept of a role, but it is difficult for anyone to fully define and describe it.

Human society can be abstracted into two types of perceptible units, namely people and things. Roles are the bond between people and people as well as people and things. Roles establish the relationship among people and things. Roles are laws, and the definition and interpretation of a role directly affect the normal operation of society. Confucius reiterated this idea in his famous adages: “名不正，则言不顺； 言不顺， 则事不成” read as “Míng bùzhèng, zé yán bù shùn; yán bù shùn, zé shì bùchéng,” which means “if the name is not right then speech will not be in order, and if speech is not in order then nothing will be accomplished” and “君君臣臣父父子子” read as “Jūn jūnchén chén fù fùzǐ zi,” which means “the king is the king, the minister the minister, the father is the father and the son the son.”

Human society is inconsistent and, at times, chaotic. The reason for this lies in the lack of proper definitions, understanding, and interpretation of roles. The definition of a role should be regulated by mechanisms higher than the human individual (agent), but the real world needs people to define roles. Because some individuals are self‐interested, they bring unfairness and disharmony to the definitions and explanations of specific roles. Although people try to introduce the concept of organization above individuals, organizations are themselves composed of individuals, and therefore, it is difficult to form a mechanism that is truly higher than individuals. Because of this, the social systems established by different countries around the world are not perfect. Some systems have shown superiority over a period of time, but sometimes they have performed poorly. This is because human society is “Agent‐Based.” “Role‐Based” is an ideal paradigm for the real world. Even though we could not fully implement a role‐based world, we may apply role‐based structures and management to certain aspects of the world, e.g., a school, a society, an enterprise, a company, an organization, a country, or an international organization.

Another role‐related human activity is the economy. In economic activities, a planned economy is composed of a collection of well‐organized roles. From the perspective of RBC, a planned economy is inherently more cost‐effective than a free economy, because a planned economy is an optimized role design strategy at its ideal state. However, a planned economy does not behave as expected in the real world. For a planned economy to work, the role designers must be absolutely correct and have no direct interest in the system being designed. That is to say, the role designer should not be a role player. However, in reality, the designers of the planned economy often failed to perfectly design the plan, because they design roles and play the roles they design. That is, the role designers are in the state that is similar to a Chinese saying “不识庐山真面目, 只缘身在此山中” read as “Bù shí lúshān zhēnmiànmù, zhǐ yuán shēn zài cǐ shānzhōng,” which means “the true face of Lushan is lost to my sight, for it is right in this mountain that I reside.” This book uses the phenomenon of human society to discuss the design of artificial systems, and it can be taken as a tool to discuss or simulate the management of human society.

I hope this book will assist humankind in clarifying and playing our roles better in the universe.

Now, let us look at artificial systems such as computer systems and software systems. For these manufactured systems, because the designer or manufacturer is the master of the system, people can be superior to the agents in the system and manage the agents without joining them. People can design and define roles for the system components, i.e., design or train agents; assign roles to agents, judge the agents' performance while the agents are playing roles; and schedule individual agents while roles are changed in the system. In this way, artificial systems can operate in a coordinated and consistent manner according to the tasks and constraints defined by the roles, thereby achieving the intention of the human manufacturer or designer. In this sense, role‐based design is a perfect method for engineering artificial systems, including modeling, analysis, design, construction, assessment, and maintenance.

Collaboration is required when there is a task that cannot be accomplished by an individual. Even people with high intelligence may not know how to handle collaboration well. Learning how to collaborate with others is a life‐long task. It requires a systematic and thorough investigation of the challenges in collaboration. Therefore, theories, technologies, practices, and systems to support collaboration should be proposed, tested, verified, validated, and taught.

Collaboration is complex because it is difficult for us to express collaboration activities with formal mathematical expressions. It is impossible to formalize every aspect of collaboration, because each of them, such as intelligence, emotions, or people, is complex enough for researchers to investigate for their whole lives. Therefore, “divide and conquer” is the fundamental method of conducting collaboration research, and we need to provide a pertinent level of abstraction and commit to the aspects that can be handled by an individual researcher or a well‐formed team.

RBC is a computational and research methodology that uses roles as a primary underlying mechanism to facilitate collaborative activities. It provides a set of concepts, models, components, and algorithms for establishing collaboration systems. The RBC methodology can be applied to the analysis, design, and development of all kinds of collaboration systems, including societal‐technical systems. The models and algorithms can also be applied to industries such as system engineering, production, management, and governance.

RBC provides insights into complex systems through the usage of its kernel Environments, Classes, Agents, Roles, Groups and Objects (E‐CARGO) model. The E‐CARGO model provides the fundamental components, principles, relationships, and structures for specifying the states, processes, and evolution of complex systems. This book investigates the nature of collaboration, proposes an easy‐to‐follow process for collaboration, and designs a model to formalize complex problems in collaboration and complex systems.

“Collaboration made easy” is the goal and theme of this book and is supported by RBC and E‐CARGO. Please note that while this book has started the research toward this goal, it is still far from reaching it. Readers are welcome to extend, apply, verify, validate, or criticize or even disqualify the proposed models, methods, formalizations, and solutions.

Haibin Zhu, PhD

North Bay, Ontario, Canada

Aug. 1, 2020

A Guide to Reading This Book

This book is written for senior students, graduate students, researchers, and practitioners in relevant engineering fields. This book can be a reference book for senior students, graduate students studying computing, systems engineering, industrial engineering, computational social systems, and any fields that deal with complex systems, who wish to apply computational methodology to their problem solving. The readers are supposed to have a background of object‐oriented programming, and discrete mathematics including set theory and predicate logic.

If you have knowledge of formalization and optimization, it should be easy for you to understand the algorithms and problem formalizations. However, you do not have to understand formalizations and optimizations before reading this book. You may choose to learn formalizations and optimization modeling through reading the book because all the symbols are specifically designed for this book. The optimization modeling is straightforward, and you do not have to know Linear Algebra at all. You may also choose to skip the formalization and optimization components, and focus on learning the concepts of role‐based collaboration and the contents that are useful for your research and practice. The following chart (Figure 0.1) can help you better obtain the information you need from this book. All the related Java codes are posted in github.com. Readers can access them by https://github.com/haibinnipissing/E‐CARGO‐Codes.

Figure 0.1 The flowchart to reading this book.

Acknowledgments

Writing a book is harder than I thought and more rewarding than I could have ever imagined.

Thanks go to the IBM Eclipse Innovation Awards which made my research on Role‐Based Collaboration (RBC) and the Environments ‐ Classes, Agents, Roles, Groups and Objects (E‐CARGO) model possible during my challenging start‐up research career.

Thanks to Natural Sciences and Engineering Research Council, Canada (NSERC) for its continuous support of my research.

I am eternally grateful to Emerita Distinguished Professor Murray Turoff of New Jersey Institute of Technology, USA, named as the father of computer conferencing. He invited me to New Jersey Institute of Technology as a visiting scholar in 1999 and then recommended me for a full‐time position, i.e. Special Lecturer at the same university in 2000. Working at NJIT started my academic career in the western world. The participation in the routine seminars of his group encouraged me to delve into the investigations of the exciting field of collaboration systems. His ideas in designing the EIES (Electronic Information Exchange System) provided me the inspirations for RBC and E‐CARGO.

This book would have been impossible without the strong support from my former collaborator, Distinguished Professor MengChu Zhou of New Jersey Institute of Technology, USA, who was ranked as World’s top 227th Computer Scientist in 2020. He stood by me during my every struggle and all my successes in my research. Without his collaboration and continuous support, I would not have been able to publish the initial stepping‐stone paper on Role‐Based Collaboration and E‐CARGO in IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews in 2006.

Thanks go to Professor Xianzhong Zhou, Nanjing University, China, and Professor Shaohua Teng, Guangdong University of Technology, China for their cooperation and support.

My visiting PhD students from Nanjing University, China helped me advance this research. They are Dr. Yin Sheng and Dr. Xianjun Zhu. I am grateful to be their co‐supervisor for their PhD Dissertations.

To my collaborators in the research of RBC and E‐CARGO, Professor Dongning Liu of Guangdong University of Technology, China, and Dr. Hua Ma of Hunan Normal University, China. They helped me extend the applications of RBC and E‐CARGO.

To my graduate students, Dr. Linyuan Liu, Luming Feng, Bo Lei, Pinzhi Wang, and Zhe Yu. Their questions make me think deeply and broadly.

Thanks go to the adjunct researcher Dr. Luca Ferrari, visiting researcher Dr. Hongyu Zhang and visiting graduate students Siqin Zhang, Mingjun Lu, and Baoying Huang in the Collaborative Systems Laboratory, Nipissing University, Canada. They help keep my research on RBC and E‐CARGO active and productive.

Thanks go to my former colleague, Mike Brewes, retired instructor of Nipissing University, Canada for his long‐term support in proofreading and editing my writings in the related research.

Thanks go to my research assistants, Eric Brownlee, and Zikai Wang at Nipissing University, Canada. Their hard work on proofreading the manuscript of this book removed many typos and made the presentation of this book more fluent and understandable. I would like to express my special thanks to the editorial team of Wiley including Mary Hatcher, Victoria Bradshaw, Teresa Netzler, and Gayathree Sekar. Without their hard work, this book could not be presented to the readers in such a graceful style. I should also thank Dr. Senyue Zhang, Xiaohui Li, Lisa Zhao, and Devin Li for their final readings which help polish the writing.

Thanks go to my wife, Jing Zhang, for her continuous patience and encouragement. She has done a lot of the yard work that should have been done by me for the past years. To my son Davis Yu Zhu, he lost many opportunities to play with me under the sunshine during his childhood due to my continuous research effort. He is also a reader and collaborator of my research.

Part 1Backgrounds

1Introduction

1.1 Collaboration and Collaboration Systems

It is a complex world. In a complex world, there are many problems for people to solve. To solve a problem, we need to establish the concepts, conduct abstraction to grasp the key points of the problem, design a model for the problem, provide a solution, and, finally, apply the solutions in the real world to verify whether the solution is acceptable. Albeit there are many simple problems that can be solved without much effort, researchers are only interested in complex problems. We should first clarify what a complex problem is.

To understand whether a problem is complex or not, we can simply check whether the problem can be formalized using symbols, formulas, equations, or other formal languages, where symbols have unique meanings. We can be assured that if a problem has not yet been formalized, it is a complex problem. On the other hand, if a problem can be formalized but the process to solve it has exponential complexity, it is also a complex problem. Under these criteria, collaboration is a complex problem.

We must admit that the research on collaboration is still in the stage of “infancy” (Miller‐Stevens et al. 2016; Morris and Miller‐Stevens 2016). The evidence to assert this claim derives from the following facts: (i) there is not a well‐accepted definition to the term “collaboration”; (ii) there is not a well‐accepted model to completely specify a collaboration system; and (iii) there is even no well‐established methodology that can be applied to conduct collaboration in specific fields, e.g. health care or manufacturing.

This book is a first attempt from the systems engineering’s viewpoint to kick off the investigation of collaboration and collaboration systems. This book aims to study collaboration, collaboration systems, and complex systems with the support of the model Environments – Classes, Agents, Roles, Groups, and Objects (E‐CARGO) and the Role‐Based Collaboration (RBC) (Zhu and Zhou 2006b) methodology.

1.1.1 Collaboration

Collaboration is a polymorphic word. It has many different meanings depending on different viewpoints and contexts. In the 1980s, Gray attempted to define “collaboration” in public administration as “the pool of appreciations and/or tangible resources, e.g. information, money, labor, etc., by two or more stakeholders, to solve a set of problems which neither can solve individually” (Gray 1985, p. 912). Many researchers have defined collaboration very differently since then (Gray 1989; Thomson 2001; Thomson and Perry 2006). Thomson states that “collaboration is a process in which autonomous actors interact through formal and informal negotiation, jointly creating rules and structures governing their relationships and ways to act or decide on the issues that brought them together; it is a process involving shared norms and mutually beneficial interactions” (Thomson 2001). In fact, even Gray’s definition has changed over time. In Gray’s 1989 paper, Gray redefined collaboration as something that “transforms adversarial interaction into a mutual search for information and for solutions that allow all those participating to ensure that their interests are represented” (Gray 1989, p. 7).

Collaboration is started when all the participants bring something to the table (expertise, money, ability to grant permission), and put their belongings on the table (Thomson and Perry 2006). Collaboration ends when all the parties agree that the result is satisfied (success) or the collaboration cannot continue anymore (failure).

We believe that collaboration is a joint effort of many (>1) people to accomplish a designated task. It is also a problem‐solving process that involves many (>1) different problem solvers (Hsieh and O'Neil Jr. 2002).

Definition 1.1

A team is a well‐organized group of participants that work together to achieve common goals.

Definition 1.2

Collaboration is a joint effort to form a team.

To understand these definitions, we need to first realize that collaboration is a joint effort from a group of people, not a job for one person. That is, collaboration requires participants to share, communicate, and interact amongst themselves. Secondly, collaboration needs to set a goal when collaboration starts, i.e., collaboration must produce an artifact, accomplish a task or provide a result. Thirdly, collaboration includes more than one participant, which can be a device, a computer system, a person, an organization, or even a country. Therefore, we can view collaboration as a complex system (Section 1.7).

Collaboration, as a research field, has all the properties of a field that demands investigation:

Collaboration is necessary. From

Figure 1.1

(UOPX news

2013

), it is reported that seven in ten people have worked in a dysfunctional team during their lifetime (Item 3). Furthermore, collaboration was necessary for human survival in early human history. Early primitives had to collaborate to build shelters to protect themselves from natural disasters. They had to collaborate to defend themselves from attacks by ferocious animals, such as wolves, tigers, and lions. They collaborated to kill animals to obtain enough food. Therefore, collaboration is a fundamental activity of the human world. No one lives completely alone. People collaborate when a single person cannot accomplish a complex or difficult task, or if a single person can complete a task but it is not economical to do so. For example, to move a piano into a house from the outside is an impossible task for one person to accomplish manually but not very hard for four people to work together. Similarly, people can make tofu dishes in a restaurant, but it is too costly for them to make raw tofu by themselves. By collaborating with a local grocery store to purchase raw tofu, they save considerable time and effort while increasing profit.

Figure 1.1 How important is teamwork? (ClassesandCareers.com).

Collaboration is complex and challenging. It requires many elements and involves a variety of combinatorics. For example, if a team has

m

members, the number of one‐to‐one connections between them is

= 

m

 ! /[2 !  × (

m

 − 2)!] = 

m

 × (

m

 − 1)/2; the numbers of subgroups of 3 members is

, … Therefore, the complexity of collaboration quickly becomes the exponential if we do not carefully organize.

Collaboration is interesting. It is fun to investigate the properties of collaboration. It provides researchers with many opportunities to satisfy their curiosities. The intermediate investigation results may be frustrating, surprising, and even exciting. Many collaboration problems may seem bewildering at the beginning. However, after sufficient effort, thinking, reasoning, and experiments are applied, exciting results may be unveiled. Such a process is similar to the aesthetic appreciation process, i.e. the result of an investigation rewards a feeling similar to sensing the beauty of art.

Collaboration is beneficial. Not only is the result of collaboration beneficial, but also is the collaboration process. Many methodologies, algorithms, and technologies developed from the research of collaboration make a fortune for people in different fields. Continuous efforts in collaboration research contribute to both the research community and industries. The following chapters will provide more concrete cases.

Collaboration requires people in a group to fulfill their obligations and respect the rights of others. To collaborate, people generally participate in a group or organization. The related parties must establish common goals by negotiation, divide the whole task into subtasks, distribute subtasks to related parties, and, finally, integrate all complete subtasks to a unified result.

Examining the components of collaboration and the type of interaction between them, collaboration can be classified into the following categories:

Natural Collaboration

occurs among people/organizations who are members of a team (

Figure 1.2

). Looking at

Figure 1.2

, we can observe how complex collaboration can be. Furthermore, the overlapping and interleaving of teams make collaboration even more complex.

Figure 1.2

presents three types of participants: the groups, the small groups, and the manager of a group. We may take the single‐large‐person icon as a manager, the three‐person icon as a small group, and a circle‐including‐person icons as a group. Please note that, in

Figure 1.2

, the sharing among the participants is hidden. Most of the problems in natural collaboration arise from the difficulties in sharing resources (Wondolleck and Yaffee

2000

) such as knowledge, information, and technologies.

Figure 1.2 Natural collaboration.

Computer‐Supported Cooperative Work (CSCW)

(Grudin

1994

) is a research topic that mainly focuses on innovations to support collaboration among people through computer systems (

Figure 1.3

). From

Figure 1.3

, we observe that people are collaborating through the use of computers. Note that we can include any equipment that facilitates collaborations, e.g. all the devices and equipment presented in

Figure 1.4

about Human–Computer/Machine Interaction.

Figure 1.3

clearly shows that the CSCW users are sharing the cloud, which is the most important resource in CSCW. If the cloud had unlimited storage capacity and unlimited communication bandwidth, CSCW technology would be easy to implement.

Figure 1.3 Computer‐supported cooperative work (CSCW).

Figure 1.4 Human–computer/machine interaction (HCI/HMI).

Human–Computer Interaction (HCI)

(Dix et al.

2003

, Preece et al.

1994

)

or Human Machine Interaction (HMI)