Theorizing data, information and knowledge constructs and their inter-relationship

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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. …

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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  • Great to see so many views for this! Especially given it was aimed at academics rather than practitioners… ;o)
    Feel free to contact me on martin.douglas@cranfield.ac.uk if you have any questions, e.g. practical implications, or are interested in how the research is progressing.
    I'm now at 2nd review stage of the PhD with fieldwork completed, some exploratory data analysis done and some emerging findings (the above was a summary based on my literature survey)
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  • 1. © Cranfield University 2012 Theorizing Data, Information and Knowledge constructs and their inter-relationship UKAIS 2013 Conference Martin Douglas & Joe Peppard 19 March 2013
  • 2. © 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
  • 3. © Cranfield University 2008© Cranfield University 2012 Introduction – The Big Data Imperative Page 3
  • 4. © 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
  • 5. © 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)
  • 6. © 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
  • 7. © 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?
  • 8. © 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
  • 9. © 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
  • 10. © 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
  • 11. © 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
  • 12. © 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
  • 13. © Cranfield University 2008© Cranfield University 2012 Rethinking Data Designer as facilitator collator and capturer of different user-views
  • 14. © 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
  • 15. © 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
  • 16. © 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
  • 17. © 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
  • 18. © Cranfield University 2008© Cranfield University 2012 Appendices – Adjacent Discipline Overviews (Various Frames) (For Reference Only) Page 18
  • 19. © 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)
  • 20. © 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)
  • 21. © 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)( (
  • 22. © 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
  • 23. © 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  
  • 24. © 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