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Internal model control in the individual knowledge worker
Mark Gregory
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The paper (Gregory and Mcnamara 2017) Website www.markrogergregory.net
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Why model? Descriptions of the real world aren’t a sufficient abstract basis for either the design of information systems (IS field) or the parameterisation of simulation models (OR field) Therefore we need conceptual models But we also need active models (Conant and Ashby, 1970): “The only good regulator of a system is a model of that system”
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Cybernetic principles
Ashby’s Law of Requisite Variety (Ashby 1956) and the Good Regulator Theorem of Conant and Ashby (Conant and Ashby 1970) The latter theorem shows that the only good regulator of a system is a model of that system:
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Good regulator theorem
“The design of a complex regulator often includes the making of a model of the system to be regulated. The making of such a model has hitherto been regarded as optional, as merely one of many possible ways. In this paper, a theorem is presented which shows, under very broad conditions, that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated. (The exact assumptions are given.) Making a model is thus necessary. The theorem has the interesting corollary that the living brain, so far as it is to be successful and efficient as a regulator for survival, must proceed, in learning, by the formation of a model (or models) of its environment.” (Conant and Ashby 1970, p.89).
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Internal model principle of control theory
(Francis and Wonham 1976) suggested the internal model principle of control theory “A structurally stable synthesis must utilise feedback of the regulated variable, and incorporate in the feedback path a suitably reduplicated model of the dynamic structure of the disturbance and reference signals” (Francis and Wonham 1976, p.457) Feedback and feedforward must be informed and inform
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Perspectives Following and extending (Conant and Ashby, 1970): we must discern conceptual models in order to understand and (perhaps) design active models in order to regulate more effectively Design is the exception; bricolage is the norm, especially in areas such as personal information management We add a design science viewpoint (fairly « hard ») to the study of personal information management systems PIMS and a learning or enquiring systems point of view (« soft ») to the study of personal work systems PWS So as to surface and make explicit modelling to understand: we have designed a somewhat novel conceptual modelling approach, Conceprocity
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The system and the internal model
Q: What is the system under investigation? A: It is the personal work system (Alter 2013); (Baskerville 2011) constituted by the knowledge worker as she gets things done, as she informs her work, and as she reflects and learns Q: What is the form and function of the model which regulates that system? A: A « Working Model » which is a dynamic active representation of the life she seeks to live The true isomorphic model is likely to be difficult to perceive, changeable, very individual and fragmented But an effort should be made to discern it at least homomorphically and to make it concrete and active
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The model and how to model it
Q: How can we model the model? A1, the representational model: In this research, we have chosen to design and develop a knowledge mapping semi-formalism, called Conceprocity A2, the active model: aid this by a personal information management PIM application assembled from ICT-enabled affordances; here, UnIQue (Volkoff and Strong, 2013) argue that affordances are the generative mechanisms which can be identified in the real domain from the relation between organisations and IT artefacts that we can observe in the actual domain
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UnIQue Mark has designed, built, used and continued to evolve a proof-of-concept PIM application called UnIQue (pronounced uni-queue - unified information querying or, better, unified IQ usage environment) UnIQue is based on the affordances offered by (inter alia) InfoQube (InfoQube 2017) and Zotero (Zotero 2017)
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A planning grid in UnIQue
Offer affordances to planner and to her « manager » Grids and their contents can be tailored In fact, they must be, if the model is to be isomorphic with the life and objectives of the individual
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Representational modelling of how a knowledge worker uses information to regulate her work
This model needs a little introduction… we’ll return to it after that explanation
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Conceprocity: an introduction
Conceprocity – concept <-> process reciprocity – is a visual and textual language and toolset intended for capturing, expressing, communicating and co-creating models of topic areas of domain knowledge by domain experts or learners You, as an expert or a learner in your domain, decide the vocabulary You follow what are initially very simple grammar rules as you build a visual model of your understanding of a topic within your domain of interest You? Teacher / student / action researcher / autoethnographer… any knowledge worker Perhaps mentored
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Notions and their relationships
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Example knowledge representation KR: a Conceprocity map of the nugget “Planning and doing the shopping” This is the only « PIM » notion – everything else is personal work system
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UnIQue dictionary for “Do the shopping”
No one model is in and of itself sufficient Tables are informational models Conceprocity model = maps + dictionary 16
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Conceprocity notions summarised
Description Concepts Things, ideas, etc.; these are usable and (sometimes) decidable classes of explicit knowledge or data; subtypes exist for social ontology Actors People, organisations, external systems: types of agent Procedures The means of enacting knowledge in the form of specific activities, repeatable actions and processes – the latter being templates for repeated actions Typed Relationships Concepts are related by relationships or relationship instances (links). In CIAOPEA the only available type of relationship is an association; this should be given a name. In TROPICPEA, relationships have specific types Images Images illustrate concepts (or any other notion) Operators Logical operators, such as XOR, OR, AND or NOT Events EITHER occurrences in time that change the state of a class of objects OR named states of a class of objects Principles Constraints, rules or complex conditions; also, software Forms The means of interaction between a system user and an information system; this is typically a webpage or a form in a desktop application Entity Entities are normalised classes of data Views A view is an unnormalised and updatable query across one or more entities; frequently it is the computer representation as data of a concept Attributes An atomic property of an entity
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TROPICPEA links and grammar
Different types of links (relationships): Association: simple connection Aggregation: is-a, is-made-of independent parts Composition: is-a, is-made-of dependent parts Specialisation / Generalisation: kind-of Regulation: controls, directs, influences… Precedence: comes-after, comes-before… Entrant-Product (Input-Output, Input-Product): is an input to a procedure which yields output or product, causes, gives rise to… Instantiation: is an example (instance) of… Semantic: Venn, LIKE, ANALOGY, METAPHOR… Grammar Rules govern the valid types of links that may join the knowledge types- cf. (Paquette 2010)
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Significance of Conceprocity
Original starting point: making sense of complex scientific papers Subsequently: Modelling working models, PWS and PIMS both as-is and as-ought Method: analysing requirements and synthesising design approaches Modelling « light » processes as knowledge (how-to) nuggets Student use: learning; assessment?
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Personal working model, work system and information management system
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Representational modelling of how a knowledge worker uses information to regulate her work
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Some interim conclusions: is this important to knowledge workers?
We all have a personal working model, usually only a mental model We all inform our own actions, by data There is scope for: Better understanding, even model based reasoning, by means of representational models Better regulation by active, ICT-informed, informational models Slightly more design, slightly less bricolage
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Small, rich, thick data! Include lots of pictures!
Some of them, structured diagrams What do we mean by structure? Structure is how notions (such as concepts, procedures etc.) are related Discerning structure, as dictionary items and as diagrams, aids model based reasoning (Nersessian 1999)
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The wider applicability of a Conceprocity modelling approach
Structuring and representing conceptually-complex topics, particularly in the contexts of abductive conjectures and of design sketches Useful in information systems and operational research work Teaching: use by lecturers of structured concept maps - (Ausubel 2000) called them advance organizers Learning: Conceprocity is structured as a series of usage profiles, starting with rich pictures Mapping work systems (a.k.a. human activity systems) Teaching information systems requirements analysis using a structured approach
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Forthcoming papers - 1 Title Current co-authors
Target journal and CABS AJG Status Conceptual Knowledge Modelling applied to Design Science Research Gregory, Mark Wood-Harper, Trevor A Personal Working Model Macgilchrist, Renaud Descubes, Irena European Journal of Information Systems – AJG: 3; FNEGE: 1 Written and presented at conference. Structured reflection in Information Systems teaching and research Systèmes d'Information et Management – AJG: not ranked; FNEGE: 2 Knowledge Organisation by Concept Process Mapping (Sole author) Information and Organization – AJG: 3; FNEGE: 2 Written; awaits incorporation of additional empirical data. Mentored action learning applied to personal knowledge management Information Systems Journal – AJG: 3; FNEGE: 2 Written and presented at conference. (Gregory et al., 2012). Needs new empirical findings.
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Forthcoming papers – 2 Title Current co-authors
Target journal and CABS AJG Status A systems perspective on personal information management Macgilchrist, Renaud Systemic Practice and Action Research – AJG: 2; FNEGE: NR An empirical analysis of emergent concepts in the literature of Personal Information Management PIM, demonstrating the absence of a systems view in the literature and arguing for its necessity. Conjectures on the morphogenesis of meaning and its part in learning Macgilchrist, Renaud (first-named) Gregory, Mark Academy of Management Learning and Education – AJG: 4; FNEGE: 2 Originally authored by my local supervisor. My contribution is in its philosophical underpinnings. Model-based reasoning in the service of conceptualisation: a concept <-> process reciprocity approach (Sole author) Academy of Management Discoveries – not ranked
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References Gregory, Mark, and Tom Mcnamara “Internal Model Control in the Individual Knowledge Worker.” In . Loughborough University. InfoQube “InfoQube Information Management System.” Nersessian, Nancy J “Model-Based Reasoning in Conceptual Change.” In Model-Based Reasoning in Scientific Discovery, edited by Lorenzo Magnani, Nancy J. Nersessian, and Paul Thagard, 5–22. Springer US. Paquette, Gilbert Visual Knowledge and Competency Modeling - From Informal Learning Models to Semantic Web Ontologies. Hershey, PA: IGI Global. Volkoff, Olga, and Diane M. Strong “Critical Realism and Affordances: Theorizing IT-Associated Organizational Change Processes.” MIS Quarterly 37 (3): 819–34. Zotero “Zotero | Home.” Alter, Steven “Work System Theory: Overview of Core Concepts, Extensions, and Challenges for the Future.” Journal of the Association for Information Systems 14 (2): 72–121. Ashby, W. Ross An Introduction to Cybernetics. Chapman & Hall London. Ausubel, David P The Acquisition and Retention of Knowledge: A Cognitive View. Kluwer Academic Pub. Baskerville, Richard L “Individual Information Systems as a Research Arena.” European Journal of Information Systems 20 (3): 251–54. doi: /ejis Conant, Roger C., and W. Ross Ashby “Every Good Regulator of a System Must Be a Model of That System.” International Journal of Systems Science 1 (2): 89–97. Francis, Bruce A., and W. Murray Wonham “The Internal Model Principle of Control Theory.” Automatica 12 (5): 457–465. file:///D:\GD\research\My%20papers\2017%20OR59\Internal%20model%20control%20in%20the%20individual%20knowledge%20worker%20v2.0%20refs.docx
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