Shaping Knowledge

Complex Socio-Spatial Modelling for Adaptive Organizations

Jamie O’Brien, Jamie O'Brien

• Publisher: Chandos Publishing
• Year: 2014
• Print ISBN: 9781843347514
• eBook ISBN: 9781780634326
• Topic: Business
• Subtopic: Information Management
• Index: Business

Organizations in ever-changing environments depend upon their knowledge, as their survival depends upon effective thinking and agile actions. Any organization's knowledge is its prime asset yet its true value requires the activations of structure, query, search and decision. Shaping Knowledge provides an introduction to the key tools for thinking required by decision-making professionals in today's knowledge-intensive landscapes, and equips them with key skills to capitalize on knowledge resources. This book provides practical methods and critical insights for modelling knowledge-driven domains, providing a rich resource for exploration in professional development and practice. - Applies high-level theory work to an engineering domain - Proposes a novel approach to spatial, urban and interaction design - Brings a rare inter-disciplinary perspective to a convergent technology

1

Introduction and case study

Abstract

Knowledge is produced and developed in social and spatial settings, such as communities and networks. Knowledge and its spaces are complex and dynamic, which poses a problem to the modeller of monitoring and representation. In this chapter, the elements of knowledge and space are introduced with the purpose of developing a pragmatic approach for professional practice. Knowledge and space are discussed in terms of their interrelatedness, hierarchy and dimensionality. We continue to approach methods of representation by outlining key themes in frame and data analysis. These ‘abstract’ notions are given greater substance by way of a provocative case-study example of social and spatial change relating to a refuse disposal site in Merseyside. Finally, an overview of the remainder of the present book is provided.

Keywords

knowledge representation

spatial form

frame analysis

data analysis

Bidston Moss Merseyside

General introduction

Change is inevitable and adaptation is necessary. This book is an argumentative response to these guiding principles as they apply to space and society. Change and adaptation pose a range of problems in these areas, to individuals and to organizations. Changes in space and society can produce innovations in technological advancements, urban forms and regional and social networks; these changes can also bring challenges to the public good. People adapt to change when they share knowledge and enjoy the rewards of their endeavours as part of an organization. People suffer by change when they seek to isolate knowledge by way of codes and protocols that reflect individuated interests. Organizations are social and economic; they include families, workplaces, technology-enabled groups; they constitute strategic alignments, rankings and hierarchies. Sometimes they don’t work to the benefit of all their members and require, we would argue, constant monitoring and assessment. Organizations are arranged to deal with certain environmental conditions. As environments change, so organizations must change. Change requires knowledge, and knowledge is built by gleaning information, as well as the careful management and representation of that information.

An organization’s knowledge is arranged as models of its real world, which comprises the summation of its requirements and resources. The phrase ‘real-world problem’ is commonly understood to mean a matter of concern relating to the allocation, distribution or balancing of things that people need, depending on the order of priorities for those needs. Any model of the real world must help to secure the effectiveness of an organization in achieving these goals. The problem for the organization is that its own knowledge can be influenced by vested interests, or culturally specific perspectives, that weigh one set of priorities against another. An organization’s reading of the ‘real world’ will be affected by those interests and values, as well as by the methods of analysis selected for the task of gathering knowledge. We argue that knowledge is not brought to an organization ready for use, but is shaped by the organization’s own demands and pressures.

Real worlds are spatial, in the sense that their requirements and resources have dimensions. So, too, organizations make up some aspect of space in terms of their underlying structures and flows of knowledge. It is important to recognize that organizations do not simply ‘occupy’ some part of a space (although people do need physical environments in which to live and work). Space is the product of interactions between people and things, and organizations produce their own spaces in terms of the constant rearranging of people and things.

As organizations combine inseparably the social and the spatial, we describe organizations as being socio-spatial. Organizational spaces also involve the cooperation of and competition between people. Cooperation and competition are not value judgements over good and bad behaviours, but represent kinds of social activity that strive towards either grouping or defecting from the group. Cooperation and competition bring about distinctive social patterns; they are the basic drivers of socio-spatial change.

In this book, we aim to help organizations improve their knowledge-building. We offer a range of contrasting methods for turning information into knowledge. We explore ideas from social science, geography, economics and physics to offer various perspectives on the ways in which space and society change. The book is intended for a non-technical, professional audience. Many subjects are covered in rudimentary terms, with the expectation that interested readers will continue to explore these topics in greater depth. The work of other authors is referenced throughout the volume, and demonstrates the very many fields of research expertise and technical specialism that contribute to addressing this book’s basic concerns.

We have drawn from specialisms in agent-based modelling, including aspects of multi-agent systems, system dynamics, adaptive systems, spatial simulations, data management and argumentation. Each of these areas has excellent and up-to-date introductions, written by experts respective to these fields, including (but not limited to) Wooldridge (2009), Sterman (2000), Miller and Page (2007), O’Sullivan and Perry (2013), Robinson et al. (2013) and Walton (2013). Guidance on experimental design for visual systems has also been offered by Cunningham and Wallraven (2012), while O’Sullivan and Perry have also provided an outstanding web resource of spatial models based comprehensively on standard analytical and simulation methods.¹ The present author is indebted to these thorough-going and accessible introductions to their specialist fields, as well as to the range of freely available software upon which much of their contents can be implemented or tested practically (the present book does not cover aspects of software implementation). This book is intended as a broadly based introduction to diverse methods for modelling; its unique contribution is to bring these many approaches together into a single volume. Readers may also strengthen their background knowledge by exploring good introductions to logic, statistics, reasoning and discrete mathematics.² Our focus is on combining these various approaches so as to achieve robust and responsive organizational knowledge. Ultimately, this book is about professional approaches to building and testing models.

Effective model-making is key to effective planning. Planning constitutes an organization’s capability to adapt to changing environments. Adaptation must occur as and when it is necessary. Adaptation cannot be forward planned and then deployed at some pre-selected moment. Adaptation requires from the organization ad hoc and dynamic adjustment based on current knowledge. Knowledge requires constant calibration and renewal, continuous shaping and reshaping.

This book approaches the shaping of knowledge along theoretical and practical lines. The theoretical components of the discussion, dealing with agents, systems, topologies and patterns, are illustrated and explored through a series of case studies. Later in this introductory chapter, we provide a case study of spatial change in the United Kingdom (specifically in an area close to the author’s home). Chapter 6 later provides three more case studies, which broaden the scope of our enquiry in geographic and historical terms. The themes of these four case studies have been selected carefully for their representation of social spaces that are particularly sensitive to current environmental and demographic trends: industrial decline, rapid urban expansion in developing economies, ageing populations in advanced industrial economies and urban formation in response to climate change. Each of these trends has an expression in urban contexts (such as the spread or retreat of cities). However, this book remains focused on the socio-spatial knowledge that drives these urban forms.

We continue our introductory discussion in the next section with a theoretical outline of space and knowledge, before introducing issues in dimensionality and representation of knowledge. The middle section of the present chapter comprises a case study in the representation of socio-spatial change, including basic issues in data modelling. Finally we provide an overview of the book as a whole, including the subsequent chapters.

Space and knowledge

The spaces of our lived environments are complex and manifold, and so too are the many ways in which we can describe and define them. Knowledge – the means by which we transform space – also bears a diversity of forms, meanings and contentions. For the purposes of clarity and convenience we can identify two areas of meaning for ‘space’: as a set of geo-located data that refer to a region of the Earth’s surface, and as the way in which we navigate our worlds by making use of things, facts and their relationships (Pfeffer et al., 2010). In similar terms, ‘knowledge’ may be a scientifically derived corpus, which can be configured to influence policy for design or governance. Knowledge can also be everyday competence that is so commonplace as to go disregarded.

This book addresses the ways in which space and knowledge assert formative forces upon each other, seeming to separate into specialized systems. In other words, it is about the co-evolution of space and knowledge. Co-evolution relates to the dynamic interplay of knowledge, in the forms of our skilled actions and the social and technological landscapes upon which they work. Co-evolution ultimately relates to the ways in which our knowledge adapts to landscapes that human agents have transformed through our social and technological activities.

Understanding the co-evolution of space and knowledge is important because it helps us develop better models of humans’ collective influence upon spatial change. Better models help us make better decisions that support policies for infrastructural service design and deployment, resource allocation and sustainable development. Key spatial changes include urban growth, ageing populations and climatological effects such as retreating sea ice, rising water levels and desertification. Spatial changes are driven by knowledge, and have direct impacts on services and human environments. Knowledge of commercial opportunities drives population movements, leading to the expansion of cities into informal settlements (generally called slums); knowledge of medicine, health and well-being advances longevity, which leads to a greater number with age-related illnesses and impairments that put pressure on care services; knowledge of science and engineering applied to industry leads to carbon emissions, which lead to a warming climate and geological changes. Each of these examples provides powerful case studies for the co-evolution of space and knowledge and are treated in greater depth throughout this book. The key issue is that change brings about opportunities for development and growth and the potential for new wealth; it also brings about pressures on services and the environment. This means that the public and commercial networks that underpin growth can become overburdened by the multifarious needs of populations. Hence our models of spatial change must include a broad range of interacting needs and resources.

Space and knowledge are available to populations unequally. Space is sanctioned explicitly by market dynamics and political protections. In the private realm, exclusive housing and commercial properties are won by the highest bidders, thus maintaining the hold of wealthy elites over land uses. In the public realm, facilities are allocated to land controlled by universities or government agencies. In many cases public and private agents cooperate, for example as university spin-outs or healthcare providers, but they do not converge as a pure kind of ‘third space’: the public and the private remain in conflict over profit versus welfare outcomes.

Space is also protected implicitly through cultural modes of behaviour that distinguish access for one group to the exclusion of another. Cultural values distinguish space for men and women, for young and old, for workers and elites, for healthy and sick, and so on. Space is demarcated through modes of design, including architecture, fashions and allegiances.

Similarly, knowledge is sanctioned explicitly through access to schools and universities, as well as through professional institutions that uphold modes of communication not accessible to the general public (for example, the use of esoteric language in the legal and medical professions). Knowledge is protected implicitly through more colloquial modes of communication, such as culturally specific points of reference, or through power-relationship courtesies and undertones. In this way, knowledge has an immediate spatial dimension or, conversely, space is driven by knowledge. This is true of elite and general spaces. Universities, for example, concentrate specialist sets of knowledge as elites, and maintain culturally specific modes of communication for lea...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright page
• Dedication
• List of figures and tables
• Acknowledgements
• Preface
• About the author
• 1: Introduction and case study
• 2: Innovation, agency and technology
• 3: The dynamics of innovation
• 4: Modelling knowledge dynamics
• 5: Modelling socio-spatial agents
• 6: Case studies in socio-spatial change
• 7: Reasoning with graphs
• 8: Decisions and arguments
• 9: Directions for adaptive planning
• Glossary
• Sources for socio-spatial argumentation
• Bibliography
• Index