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Good explanatory constructs for Data, Information and Knowledge are central to the Information Systems (IS) field in general, and in particular to theorising how best to generate insight from Data. The central role of Knowledge within such theory has been highlighted recently, as well as the importance of Learning and Research frames (for Data Analytics). Building on these ideas, this paper briefly reviews several related literatures, for relevant ideas to enrich IS theory building. A consensus is found as to the complex, socially constructed nature of Knowledge or Knowing, and the importance of human sensemaking for theorizing how new insight is generated. The paper argues for an intuitive conceptual and practical distinction between Data (which exists as an independent, reified resource), and Information and Knowledge (both of which are embodied or embrained). It briefly outlines how the ideas identified can contribute to theorizing, highlighting specific areas for further inter-disciplinary research.
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© Cranfield University 2012
Theorizing Data, Information and Knowledge constructs and their inter-relationship
UKAIS 2013 Conference
Martin Douglas & Joe Peppard 19 March 2013
© Cranfield University 2008 © Cranfield University 2012
Structure
Introduction
Various Frames for Developing Insight
A Social Constructionist Perspective
Data is different to Information-Knowledge
Rethinking Data
Discussion
© Cranfield University 2008 © Cranfield University 2012
Introduction – The Big Data Imperative
Page 3
© Cranfield University 2008 © Cranfield University 2012
Introduction – Simplistic Practitioner Thinking
Processes & interactions not addressed (implicit)
Fairly simplistic thinking & Theory More is more… All you need are the right tools,
data warehouses As to People question:
=> More analysts needed So how do we derive Insight
from Data?
Page 4
© Cranfield University 2008 © Cranfield University 2012
Introduction – Inadequate IS Theory
Hard, rational school prevalent Emphasis on management decision
making, related system support & Information Management
Human aspects recognised as important and problematic
Recently, Kettinger & Li (2010) & Wang & Wang (2008) recognise Knowledge & Learning as important
Doesn’t really engage with the embodied, socially constructed nature of Insight (Information & Knowledge)
Use of input data, stored data, and frame of reference to process a decision (Davis & Olson: 1985: p.238)
Mental processing
Data storage
Storage for frames of reference
Input data Decision
Davis & Olson (1985: p238): Use of input data, stored data, and frame of reference to process a decision
Information Management Cycle (Marchand, Kettinger & Rollins: 2001)
Sensing
Collecting
Organising
Processing Maintaining
Intersecting learning cycles between Analyst & User (Wang & Wang: 2008: p.627)
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Several Adjacent Disciplines are also interested in this phenomenon...
Environment
Organisation
Situated Individuals
(within Communities of Practice)
Individual (internal)
Research (& Development) Absorptive Capacity Research Questions
Information Processing
Knowledge Management Knowing
Cognition
Situated/ Social Individual
Learning Organizational/ Market Based
Sensemaking
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Different purposes, units of analysis, terminology… However, can they Contribute to our thinking & theory?
© Cranfield University 2008 © Cranfield University 2012
A (Soft) IS Starting Point… Start theorising from Data Human seen as central Embodied nature of Information/Knowledge concepts recognised Idea of Information and Knowledge as a continuum More complex interactions envisaged between elements
Don’t really offer any thinking on how this occurs though…
A Socially Constructed Perspective (IS)
The links between data, capta, information and knowledge (Checkland & Holwell: 1998: p.90)
Facts Selected
or Created Facts
Meaningful Facts
Larger, longer- living structures of
meaningful Facts
Cognitive (Appreciative
settings) Context, Interests
DATA CAPTA INFORMATION KNOWLEDGE
© Cranfield University 2008 © Cranfield University 2012
A Socially Constructed Perspective (KM/OL)
KM/OL start from the opposite end… Don’t really engage with Information and Data constructs Also stress social dimension Tsoukas idea of Knowledge as ability to draw ever-finer distinctions Research Philosophy engages with Data though (eg Validity)
The links between data, capta, information and knowledge (Checkland & Holwell: 1998: p.90)
Facts Selected
or Created Facts
Meaningful Facts
Larger, longer- living structures of
meaningful Facts
Cognitive (Appreciative
settings) Context, Interests
DATA CAPTA INFORMATION KNOWLEDGE
© Cranfield University 2008 © Cranfield University 2012
A Socially Constructed Perspective (KM & Learning)
Consensus between social constructionists across several fields: Insight starts with individuals
Situated in an action context (e.g. community of practice)
Path dependency on prior knowledge/experience
Together with Context, impacts framing and enacted meaning
Complementarity and complex interaction between tacit and explicit/reified knowledge
Emphasise importance of social processes and taking a longitudinal view
Sensitivity to Epistemology and Ontology See also Paper Appendix for Detailed Contributions from KM, OL & Sensemaking
© Cranfield University 2008 © Cranfield University 2012
Facts Selected
or Created Facts
Meaningful Facts
Larger, longer- living structures of
meaningful Facts
Cognitive (Appreciative
settings) Context, Interests
DATA CAPTA INFORMATION KNOWLEDGE
Data is different to Information-Knowledge
The links between data, capta, information and knowledge (Checkland & Holwell: 1998: p.90)
Formal data
Tacit/subconscious
data�
Directly observed data�
Informal data�
Real world perceived by
individual �(social & physical) �
Knowledge ��
Memory�Values�
Cognitive�filter�
Real World
Embodied Meaning Data
© Cranfield University 2008 © Cranfield University 2012
Rethinking Data
Data as a reified ‘snapshot’ of phenomena Extend Orlikowski(1991) structuration to encompass Data
Dimensions Fields Classifications
© Cranfield University 2008 © Cranfield University 2012
Rethinking Data
Designer as facilitator collator and capturer of different user-views
© Cranfield University 2008 © Cranfield University 2012
Rethinking Data
Users have different interests in same/different data elements Different purposes & action contexts Capture often divorced from Use Processing as reified algorithmic ‘practice’
Customer Services Finance/Compliance
© Cranfield University 2008 © Cranfield University 2012
Rethinking Data
Data as a reified ‘snapshot’ of phenomena Recognises different user perspectives
i.e. action contexts – Communities of Practice (CoPs) Different purposes, language-meaning, identities
Role of Designer role & judgement highlighted Negotiation, facilitation, power (across boundaries/CoPs) When & How best to optimise Data design?
Validity (Quality) criteria for Data How well does it capture the phenomenon? Social versus physical phenomena?
Evolving, unintended use and inflexibility recognised (iterative learning) Tacit knowledge precepts Limits of codification & optimisation dilemmas (when) Aligns better with Agile approaches?
Increasing knowledge about a phenomenon Ever-finer distinctions (Tsoukas: 2005) Reflected in richer set of fields/classifications Path dependency/framing impact (Cohen & Levinthal: 1990)
Emphasises the importance of social processes and taking a longitudinal view
© Cranfield University 2008 © Cranfield University 2012
Discussion
Feedback on: Data vs Information-
Knowledge Avoid interchangeable use of
Data & Information terms
Developing a Reified concept of Data How far? Codified Knowledge/Algorithms
Inter-disciplinary opportunities
© Cranfield University 2008 © Cranfield University 2012
Discussion
Inter-disciplinary Opportunities Overlaps with OL & KM
Extend Vera & Crossan
Data at the intersection Learning from Data Exploration, research, etc Codified Knowledge/
Algorithms
Inter-disciplinary opportunities
Note: Cognition angle not covered (e.g. visualisation)
Overlaps: Organizational Learning & Knowledge Management (Vera & Crossan: 2003: p.127)
Learning from Data
Data Analytics Tools (various)
Information Systems
© Cranfield University 2008 © Cranfield University 2012
Appendices – Adjacent Discipline Overviews (Various Frames) (For Reference Only)
Page 18
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Dominant resource view cluster around Nonaka (1994)’s view, concerned with innovation and knowledge sharing: Socialization – conversion of tacit
knowledge to tacit knowledge between individuals through observation, imitation and practice (i.e. non-verbal)
Combination – combining sets of explicit knowledge held by individuals through social processes
Externalization – involving interaction between explicit and tacit knowledge through social dialogue to create shared concepts, normally within a team and often involving the use of metaphor
Internalization – is seen as closest to traditional organizational learning, although action is seen as an important component
This view is criticised for fundamentally misunderstanding the nature of tacit knowledge, which precludes conversion/externalisation
Nevertheless it agrees with the social constructionist knowing view in several key respects: its action orientation or purpose, its situation within a specific context and ‘interaction
community’ or community of practice the importance of reflection and sensemaking activities, and its social nature and the associated importance of dialogue
Spiral of Organizational Knowledge Creation (Nonaka: 1994: p.20)
Knowledge Management (Resource view)
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Grounded in work by Blackler (1995) (based on Vygotsky) and more recently Tsoukas (2005, 2009) Focused on Organisational Theory problems and largely theory building Emphasise process of acquiring knowledge rather
than privileging knowledge as an abstract resource Stress its embodied, social nature with the following
characteristics: Mediated, Situated, Provisional, Pragmatic
and Contested On tacit knowledge: Subsidiary particulars are
assimilated through experience and practice and are interiorised over time, forming an ‘unarticulated background’ which influences and frames action but cannot be focused on during action (Tsoukas: 2005)
Supported by cognitive research D’Eredita & Barreto: 2006), which highlights the following: Episodic nature of memory and knowledge,
its creation through relating current to prior episodes, based on attention to cues/stimuli
Advocates Reflection and Dialogue, with considerable research on how new knowledge emerges from ‘productive conversations’
Points to the potential role of ‘boundary objects’ for inter-disciplinary shared interpretations
Highlights the limitations inherent in privileging abstract, codified knowledge
Blackler (based on Vygotsky) (1995: p.1039)
Knowledge Management (Knowing view)
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
This is a vast field! It is also characterised by many different theories of learning. Given a social constructionist starting point for thinking about information and knowledge, Easterby-Smith & Lyles (2003: p.25) categorisation of the field based on underlying theory was particularly helpful: It identifies several
authors working across overlapping knowledge management and Learning fields
It brings Communities of Practice into view
Learning Psychological+perspectives+
Information+Processing+
Behavioural/+evolutionary+
Social+construction+
Applied++Learning+
Biological+ Storage(and(memory(are(distributed(across(organization(((March:(1991)(
( ( (
Learning+ Stimulus;response(is(lower(level(learning(((Fiol(&(Lyles:(1985)(Learning(as(computation((Huber:(1991)(
Consequences(shape(learning(((Lant(&(Mezias:(1990)(
Social(learning(is(embedded(in(relationships(((Orr:(1990;(Wenger:(1998)(
Single;loop(learning(is(driven(by(consequences((Argyris(&(Schon:(1974)(
Cognitive+ Sensemaking(is(higher(level(learning(((Fiol(&(Lyles:(1985)(
Trajectory(results(from(cumulative(prior(learning(((Nelson(&(Winter:(1982)(
Cognition(is(socially(mediated(sensemaking(((Weick:(1991)(
Learning(derives(from(experience(processing((Kolb:(1984)(and(from(action(and(reflection((Lewin:(1946)(Cognition(derives(from(shared(mental(models((Kim:(1993)(
Sociocultural+ ( ( Communities(socially(construct(meaning((Brown(&(Duguid:(1991)(
(
Psychodynamic+ ( Path(dependence(as(initial(state(shaping(future(behaviour.(History(matters((Nelson(&(Winter:(1982)(Organizational(learning(perspectives(
( Individual(and(group(defensiveness(undermines(organization(learning((Argyris(&(Schon:(1974)(
(
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Elkjaer (2003) contrasts social learning theory with individual learning theory, which she argues emphasises enhancement of individual cognitive frames and privileges abstract knowledge acquisition (e.g. conceptual bodies of knowledge) Over that which derives from practice She offers the following definition of social learning:
Learning (Social/Situated)
‘a#social#learning#theory#emphasizes#informality,#improvisation,#collective#action,#conversation#and#sense#making,#and#learning#is#of#a#distributed#and#provisional#nature’#(p.#44)!
She equates social learning with situated learning, practice based learning & learning as a cultural process, highlighting that much social learning theory has grown from a
criticism of individual learning theory, and ‘That it is impossible to separate knowing from
being and becoming. To be and become – or emerge as – a knowledgeable person demands participation in social processes’ (p. 46)
She argues for the need to synthesise these approaches, citing Dewey’s ideas as a starting point: Inseparability of identity, practice and knowledge
(sensitive to a particular context) Arguing for the importance of Inquiry, Reflection
and Experience This supports work by Vera & Crossan (2003), which argues for more research to look at the interaction of between knowledge and learning processes It supports a focus on Communities of Practice as a context for learning and knowledge creation, via reification & participation, leading to economies of meaning
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Sensemaking (Weick: 1995) Explains it as an explanatory process: ‘Grounded in iden+ty construc+on Retrospec+ve Enac+ve of sensible environments Social Ongoing Focused on and by extracted cues Driven by plausibility rather than accuracy’ as dis+nguishing characteris+cs (Weick: 1995: p.17)
He contributes several important ideas: Dis+nc+on between ambiguity & uncertainty
Interdependence between pre-‐exis+ng frames and cues (pragma+c, purpose-‐driven)
Role of arousal in likely narrowing context
Very consistent with and underpins much other social construc+onist work in learning & knowledge management (eg Tsoukas, Blackwell, Wenger)
Very interested in the role of IT given its pervasiveness & cites work by Orlikowski & Orr as good examples: Orlikowski highlights structura+on aspects of
IT systems Data can be seen in a similar light
© Cranfield University 2008 © Cranfield University 2012
Various Frames for Developing Insight
Research Based on the idea of gaining new knowledge being about researching Customers as a phenomenon of interest
This coalesced from three angles: Market Research in Marketing
Well established as a discipline Quantitative and qualitative approaches Issues of use/adoption/value (as in IS?)
R&D More product/technology focused Mostly organisation level unit of analysis Absorptive capacity ideas could be relevant
(Cohen & Levinthal: 1990 rather than Zahra & George: 2002) Path/context/frame dependency Insight = Rapid Problem solving
(pre-conditions the same)
Research Philosophy Research Questions lens per Blaikie (2007)
What, How & Why progression The likely importance of Ontology and Epistemology
Key take-aways: What, How & Why progression Sensitivity to Epistemology Corroboration for research and related
question validity Possible areas for contribution in due course
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