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Example..
                                                                                Let ’s publish a paper f or t his nice Bahamas conf er ence…
                                                                                What about a hashing f unct ion f or sear ching lar ge
                                                                                image dat abases (int er net -> $ $ $ $ $ !)
           Research methods and
                                                                                      Ef f icient hashing f or lar ge image dat abases
               methodology
                                                                                     1.     Intro (there are so many images!)
                                                                                                                                   •Research methodology?
                                                                                     2.     The Algorithm (pseudo-code)
                                                                                     3.     Example (it works)                     •Objective?
                      Hans Weigand                                                   4.     Conclusions (it really works!)
                                                                                                                                   •Related research?
                      Univ of Tilburg                                                                                              •Validation?
Nov 2006                        Hans Weigand                                1    Nov 2006                                  Hans Weigand                         2




                                                                                               Knowledge and scientific
            Science fiction and fact
                                                                                                    knowledge
•   Objective knowledge                 •      Opinion, taste, hype
•   Repeatable experiments              •      handwaiving                                            intuitive knowledge
•   Valid reasoning                     •      rhetoric
                                                                                      knowledge of the
•   Unbiased                            •      university politics                                                         scientific knowledge
                                                                                      concrete
•   Revealing                           •      dull, uninteresting
•   Researcher as the shy               •      researchers highly                                     religious knowledge
    and cooperative genius                     competitive and over-self-
                                               confident
                                                                                                                                          Focuses on
                                                                                                                                          - the abstract
                                                                                                                                          - using logical reasoning
Nov 2006                        Hans Weigand                                3    Nov 2006                                  Hans Weigand
                                                                                                                                          - acquired methodologically
                                                                                                                                                                  4




             Course overview                                                              Overview of this introduction
•   Introduction (Hans Weigand)                                                  •        Basic research methodology (Verschuren/Doorewaard)
•   Philosophy of empirical sciences (Richard Starmans)
•   Philosophy of formal sciences (John-Jules Meyer)
                                                                                 •        What is IS/CS research? Wieringa, March
•   Research design (Hans Weigand, Hans Heerkens)                                •        Research paradigms in IS
•   Research methods (Hans Akkermans)
•   Research methods in
                                                                                 •        Research as communication
     – Agent Systems (Catholijn Jonker)
     – Machine Learning (Antal vd Bosch)
     – IR (Djoerd Hiemstra)
• Examples from two Ph.D. students
• How to write an article (Hans Akkermans)
Nov 2006                        Hans Weigand                                5    Nov 2006                                  Hans Weigand                         6




                                                                                                                                                                        1
Research Methodology                                                  Empirical cycle
  • Types of research                                             • Hypothesis
  • Conceptual research design                                    • Experiment
        – Research objective                                      • Evaluation
        – Research questions
        – Definition of concepts
  • Research planning                                                                          “is it true? (and why?)

  Nov 2006                            Hans Weigand       7        Nov 2006                      Hans Weigand                        8




                          Design cycle                                        H. Simon, The Sciences of the Artificial



  • Design
  • Simulation/implementation                                  The engineer, and more generally the designer, is concerned with how
                                                               things ought to be - how they ought to be in order to attain goals, and to
  • Evaluation                                                 function … With goals and "oughts" we also introduce into the picture
                                                               the dichotomy between normative and descriptive. Natural science has
                                “is it possible?” (and how?)   found a way to exclude the normative and to concern itself solely with
                                                               how things are … Artificial things can be characterized in terms of
                                                               functions, goals and adaptation.
Note: In CS, “implementation” can range from model to               Research methods: simulation and decomposition
proof-of-concept prototype to full implementation
  Nov 2006                            Hans Weigand       9        Nov 2006                      Hans Weigand                       10




             Theory/practice oriented                                             Research quadrant
  • Theory-oriented: develop or test theory
        – Involves experimentation                              empirical           physics,                   political poll
                                                                                    sociology
  • Practice-oriented: solve a problem
        – Involves intervention.
                                                                             “develop incremental         “develop web-site”
                                                                 design      NL parser”


                                                                             theory-oriented                   practice-oriented
  Nov 2006                            Hans Weigand      11        Nov 2006                      Hans Weigand                       12




                                                                                                                                            2
Research Methodology                                                         Research objective
                                                                      • Start exploring the project context
• Types of research
                                                                      • Formulate research objective
• Conceptual research design
                                                                            – useful (added-value)
      – Research objective
                                                                            – feasible
      – Research framework
                                                                            – clear
      – Research questions
                                                                      • The objective is to … by …
      – Definition of concepts
• Research planning                                                                             your contribution               your overall result

Nov 2006                     Hans Weigand                        13   Nov 2006                              Hans Weigand                          14




                Theory oriented                                                           Practice-oriented
• Theory development                                                  •   Problem finding
• Theory testing                            (cf. Glaser & Strauss)    •   Diagnosis
                                                                      •   Design
                                                                      •   Intervention                               Different kinds of research
A theory is more than accumulated knowledge, it provides a                                                           and research questions
                                                                      •   Evaluation
perspective (abstraction, interpretation) and is explanatory/
predictive


Nov 2006                     Hans Weigand                        15   Nov 2006                              Hans Weigand                          16




             Research framework                                           Research framework visualized
                                                                                              (example master project)

•   Specify short objective                                                 Interviews with
                                                                               consultants
•   Determine the object
                                                                                                      Proposal evolutionary
•   Establish the nature of the research                                                                 design method
                                                                                                                                   A/D method for
•   Determine ingredients                                                 Theory of IS design                                     evolutionary design
                                                                               methods
•   Visualize
                                                                                                      Application of method
                                                                                                           (case study)
NB: often, a research project combines several research types

Nov 2006                     Hans Weigand                        17   Nov 2006                              Hans Weigand                          18




                                                                                                                                                        3
Example: vd Heuvel (2002)                                                           Research questions
   “a methodology for objectifying legacy systems”

1. Problem definition               Explorative, desk research                • The questions that you state yourself for getting at
                                                                                your objective
2. Related research                 Literature review
                                                                              • Main question/subquestions
3. Design of solution               Meta-modeling
                                                                              • Requirements:
4. Validation of                    - Logical consistency metamodel
                                                                                    – Effectiveness (do you reach your objective?)
   proposed solution                - Implementability prototype
                                                                                    – Efficiency (balance between goal and means)
                                    - Plausibility     field experiment
5. Assessment of                                                                    – Steering function
                                                                                         • What type of knowledge is required?
   research results                                                                      • What material needs to be gathered?

Nov 2006                  Hans Weigand                          19            Nov 2006                           Hans Weigand                    20




How to get at research questions?                                                          Research Methodology
 • By exploring the research framework
                                                                              • Types of research
 • By unravelling key concepts
                                                                              • Conceptual research design
 • Use knowledge hierarchy:                                                         – Research objective
                                             prescriptive                           – Research framework
                                              evaluative                            – Research questions
   What is the best?                          predictive                            – Definition of concepts (tomorrow)
  Is A better then B?                        explanatory
     Is it possible?                                                          • Research planning
                                             descriptive
Nov 2006                  Hans Weigand                          21            Nov 2006                           Hans Weigand                    22




           Research planning : HOW?                                                               Research objective

• Research material
      – People, documents, observation                                            research                      research             research
      – Data sources, knowledge sources                                           question I                   question II          question III
• Research strategy
      – Survey, experiment, case study, grounded
        theory approach, desk research, …                                    r esear ch met hod A           r esear ch met hod B
                                                                               (e.g. case st udy)           (e.g. mat hemat ical
• Time planning                                                                                                    pr oof )         r esear ch met hod C
                                                                                                                                   (e.g. exper iment ing)
                                                                          Arrows represent your choices
Nov 2006                  Hans Weigand                          23            Nov 2006                           Hans Weigand                    24




                                                                                                                                                            4
Concluding remarks on research
                                                                                What is IS/CS research?
           methodology
 • Research needs preparation (GIGO)
 • Be aware of the choices that you make                                       Is CS a science?
 • During execution, the framework should
   always indicate the purpose of what you are                                 IS CS an engineering discipline?
   doing at that moment.                                                       Is it a formal science, branch of mathematics?
 • As research is a creative process, adapting
   the framework on the way is natural and
   should always be possible.
 Nov 2006                       Hans Weigand               25       Nov 2006                             Hans Weigand                    26




                  Wieringa/Heerkens                                                            March/Smith
 • Characterizes CS as design science                               • CS/IS research should integrate design and
 • Design is aimed at solving some problem (action                    “natural science research”
   problem, world problem)                                          • Design is aimed at creating things
 • The design itself is not research (contra Popper),               • Basic design activities: build and evaluate
   but the other steps in the intervention cycle give
   rise to knowledge problems that can be addressed                 • Natural science is aimed at developing theory –
   by scientific research                                             not restricted to natural phenomena, can also apply
 • Sometimes solving a knowledge problem requires                     to artifacts (contra Simon)
   solving an action problem                                        • Basic science activities: theorize and justify

 Nov 2006                       Hans Weigand               27       Nov 2006                             Hans Weigand                    28




                                                                                      Theory and Action
 March/Smith research framework
                                                                                         in balance
                       build   evaluat e t heor ize j ust if y
                                                                    theory                                                        practice
const r uct s                                                                                        knowledge problem
                                                                                                    knowledge problem
                                                                                                  knowledge problem


model
                                                                          theory problem                                 world problem
met hod
                                                                 -lack of t heor y
                                                                 -lack of validit y                 action problem
                                                                                                      action problem
inst ant iat ion                                                 -f alsif icat ion at t empt
(wor king pr ogr am)                                             -anomaly

 Nov 2006                       Hans Weigand               29       Nov 2006                             Hans Weigand                    30




                                                                                                                                              5
Ramesh et al                                                              Why mathematics?
 • Based on empirical study of publications                                       • Conceptual clarity
                                                                                        – like precise definitions in Law
 • Focus in CS is on formulating (80%) rather
                                                                                        – Could perhaps be reached also by UML diagram
   than describing or evaluating
                                                                                  • As a research method
 • Research methods: mainly conceptual/                                                 – to validate certain claims
   mathematical                                                                   • For the development of a (predictive) theory
 • Low reference to other discipline (some                                              – not really different from e.g. game theory in Economics
   mathematics)                                                                         – Example: relational algebra, complexity theory, ..

 Nov 2006                          Hans Weigand                           31      Nov 2006                       Hans Weigand                   32




            Research paradigms in IS                                                                  Interpretivism
 • Positivism (Comte) and rationalism (Descartes)
 • Post-modernism (Foucault, Derrida), cf.                                           The aim of interpretive research is to understand how
                                                                                     members of a social community, through their participation in
   interpretivism, constructivism, …
                                                                                     social processes, enact their particular realities and endow
 • Pragmatism (Peirce, Dewey, Rescher)                                               them meaning, and to show how these meanings, beliefs and
 • Critical theory (Habermas)                                                        intentions of the members help to constitute their social action
                                                                                     (Orlowski & Baroudi, 1991)

 Cf debate between rationalist AI tradition (Schank, Stefik/Bobrow) and
    Winograd & Flores, to which also Suchman contributed.


 Nov 2006                          Hans Weigand                           33      Nov 2006                       Hans Weigand                   34




                        Pragmatism
Not in the sense of opportunism, but concerned with
                                                                                                      Critical theory
action rather than with being                                        Ch. Peirce


“There is no such thing as genuine knowledge and fruitful                         • Knowledge is not neutral - be critical about
understanding except as the offspring of doing… Only by                             assumptions such as the technical
wrestling with the conditions of het problem at first hand,                         imperative to improve efficiency
seeking and finding his own way, does he think“
                                                                    John Dewey    • Knowledge must be legitimated by
“Thinking is not different in kind from the use of natural
materials and energies ..”                                                          consensus and democratic discourse
Knowledge of a thing is knowledge of what you can do with it.                     • Knowledge is not neutral – science should
Tries to bridge empirical science and design science.                               serve social goals such as emancipation

 Nov 2006                          Hans Weigand                           35      Nov 2006                       Hans Weigand                   36




                                                                                                                                                        6
Research as communication                                                                                 So …
                                                                                        • Communicate! (publish, discuss, review,…)
  • Researchers communicate via papers,                                                 • Be clear! (Grice’s conversational maxims)
    presentations, discussions                                                          • Take communication partners seriously!
  • In communicating, they make descriptive                                                  –     Read related research
                                                                                             –     Try to understand
    and normative statements (validity claims)
                                                                                             –     Refer
  • These claims may be challenged by others,                                                –     Consider their goals and expectations
    leading to discussion                                                               • Don’t “drop an idea”; try to convince!
  • Discussion is as essential as research                                              • Justify your claims!
    activities itself
  Nov 2006                                 Hans Weigand                            37   Nov 2006                          Hans Weigand                  38




Maxim of Quantity:
 1. Make your contribution to the conversation as informative as necessary.                        How to justify your claims?
2. Do not make your contribution to the conversation more informative than
necessary.

Maxim of Quality:
                                                                                                              "Ik ben er nog steeds van overtuigd dat
1. Do not say what you believe to be false.
                                                                                                              zoals ik het doe je het moet doen want
2. Do not say that for which you lack adequate evidence.
                                                                                                              anders zou ik het niet doen."
Maxim of Relevance:
Be relevant (i.e., say things related to the current topic of the conversation).

Maxim of Manner:
1. Avoid obscurity of expression.
2. Avoid ambiguity.
3. Be brief (avoid unnecessary wordiness).
4. Be orderly.


  Nov 2006                                 Hans Weigand                            39   Nov 2006                          Hans Weigand                  40




                                                                                                                   Literature
             How to justify your claims?                                                • Designing a research project – P. Verschuren, H.
                                                                                          Doorewaard. Utrecht, 1999.
  •   Grounding (empirical, simulation, …)                                              • Desiging Information Technology in the postmodern age – R.
                                                                                          Coyne, 1997
  •   Careful reasoning                                                                 • Qualitative methods in management research – E.
                                                                                          Gummesson
  •   Examples (not just for explanation, but to put your claim to the test)
                                                                                        • The sciences of the artificial. H. Simon, 1967
  •   Delimitation                                                                      • Research in Computer Science: an empirical study
                                                                                           -Ramesh et al, 2004
  •   Be clear about the status of your claim.                                          • Design and natural science research on information
                                                                                          technology - March, Smith, 1995


  Nov 2006                                 Hans Weigand                            41   Nov 2006                          Hans Weigand                  42




                                                                                                                                                             7

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Research methodology

  • 1. Example.. Let ’s publish a paper f or t his nice Bahamas conf er ence… What about a hashing f unct ion f or sear ching lar ge image dat abases (int er net -> $ $ $ $ $ !) Research methods and Ef f icient hashing f or lar ge image dat abases methodology 1. Intro (there are so many images!) •Research methodology? 2. The Algorithm (pseudo-code) 3. Example (it works) •Objective? Hans Weigand 4. Conclusions (it really works!) •Related research? Univ of Tilburg •Validation? Nov 2006 Hans Weigand 1 Nov 2006 Hans Weigand 2 Knowledge and scientific Science fiction and fact knowledge • Objective knowledge • Opinion, taste, hype • Repeatable experiments • handwaiving intuitive knowledge • Valid reasoning • rhetoric knowledge of the • Unbiased • university politics scientific knowledge concrete • Revealing • dull, uninteresting • Researcher as the shy • researchers highly religious knowledge and cooperative genius competitive and over-self- confident Focuses on - the abstract - using logical reasoning Nov 2006 Hans Weigand 3 Nov 2006 Hans Weigand - acquired methodologically 4 Course overview Overview of this introduction • Introduction (Hans Weigand) • Basic research methodology (Verschuren/Doorewaard) • Philosophy of empirical sciences (Richard Starmans) • Philosophy of formal sciences (John-Jules Meyer) • What is IS/CS research? Wieringa, March • Research design (Hans Weigand, Hans Heerkens) • Research paradigms in IS • Research methods (Hans Akkermans) • Research methods in • Research as communication – Agent Systems (Catholijn Jonker) – Machine Learning (Antal vd Bosch) – IR (Djoerd Hiemstra) • Examples from two Ph.D. students • How to write an article (Hans Akkermans) Nov 2006 Hans Weigand 5 Nov 2006 Hans Weigand 6 1
  • 2. Research Methodology Empirical cycle • Types of research • Hypothesis • Conceptual research design • Experiment – Research objective • Evaluation – Research questions – Definition of concepts • Research planning “is it true? (and why?) Nov 2006 Hans Weigand 7 Nov 2006 Hans Weigand 8 Design cycle H. Simon, The Sciences of the Artificial • Design • Simulation/implementation The engineer, and more generally the designer, is concerned with how things ought to be - how they ought to be in order to attain goals, and to • Evaluation function … With goals and "oughts" we also introduce into the picture the dichotomy between normative and descriptive. Natural science has “is it possible?” (and how?) found a way to exclude the normative and to concern itself solely with how things are … Artificial things can be characterized in terms of functions, goals and adaptation. Note: In CS, “implementation” can range from model to Research methods: simulation and decomposition proof-of-concept prototype to full implementation Nov 2006 Hans Weigand 9 Nov 2006 Hans Weigand 10 Theory/practice oriented Research quadrant • Theory-oriented: develop or test theory – Involves experimentation empirical physics, political poll sociology • Practice-oriented: solve a problem – Involves intervention. “develop incremental “develop web-site” design NL parser” theory-oriented practice-oriented Nov 2006 Hans Weigand 11 Nov 2006 Hans Weigand 12 2
  • 3. Research Methodology Research objective • Start exploring the project context • Types of research • Formulate research objective • Conceptual research design – useful (added-value) – Research objective – feasible – Research framework – clear – Research questions • The objective is to … by … – Definition of concepts • Research planning your contribution your overall result Nov 2006 Hans Weigand 13 Nov 2006 Hans Weigand 14 Theory oriented Practice-oriented • Theory development • Problem finding • Theory testing (cf. Glaser & Strauss) • Diagnosis • Design • Intervention Different kinds of research A theory is more than accumulated knowledge, it provides a and research questions • Evaluation perspective (abstraction, interpretation) and is explanatory/ predictive Nov 2006 Hans Weigand 15 Nov 2006 Hans Weigand 16 Research framework Research framework visualized (example master project) • Specify short objective Interviews with consultants • Determine the object Proposal evolutionary • Establish the nature of the research design method A/D method for • Determine ingredients Theory of IS design evolutionary design methods • Visualize Application of method (case study) NB: often, a research project combines several research types Nov 2006 Hans Weigand 17 Nov 2006 Hans Weigand 18 3
  • 4. Example: vd Heuvel (2002) Research questions “a methodology for objectifying legacy systems” 1. Problem definition Explorative, desk research • The questions that you state yourself for getting at your objective 2. Related research Literature review • Main question/subquestions 3. Design of solution Meta-modeling • Requirements: 4. Validation of - Logical consistency metamodel – Effectiveness (do you reach your objective?) proposed solution - Implementability prototype – Efficiency (balance between goal and means) - Plausibility field experiment 5. Assessment of – Steering function • What type of knowledge is required? research results • What material needs to be gathered? Nov 2006 Hans Weigand 19 Nov 2006 Hans Weigand 20 How to get at research questions? Research Methodology • By exploring the research framework • Types of research • By unravelling key concepts • Conceptual research design • Use knowledge hierarchy: – Research objective prescriptive – Research framework evaluative – Research questions What is the best? predictive – Definition of concepts (tomorrow) Is A better then B? explanatory Is it possible? • Research planning descriptive Nov 2006 Hans Weigand 21 Nov 2006 Hans Weigand 22 Research planning : HOW? Research objective • Research material – People, documents, observation research research research – Data sources, knowledge sources question I question II question III • Research strategy – Survey, experiment, case study, grounded theory approach, desk research, … r esear ch met hod A r esear ch met hod B (e.g. case st udy) (e.g. mat hemat ical • Time planning pr oof ) r esear ch met hod C (e.g. exper iment ing) Arrows represent your choices Nov 2006 Hans Weigand 23 Nov 2006 Hans Weigand 24 4
  • 5. Concluding remarks on research What is IS/CS research? methodology • Research needs preparation (GIGO) • Be aware of the choices that you make Is CS a science? • During execution, the framework should always indicate the purpose of what you are IS CS an engineering discipline? doing at that moment. Is it a formal science, branch of mathematics? • As research is a creative process, adapting the framework on the way is natural and should always be possible. Nov 2006 Hans Weigand 25 Nov 2006 Hans Weigand 26 Wieringa/Heerkens March/Smith • Characterizes CS as design science • CS/IS research should integrate design and • Design is aimed at solving some problem (action “natural science research” problem, world problem) • Design is aimed at creating things • The design itself is not research (contra Popper), • Basic design activities: build and evaluate but the other steps in the intervention cycle give rise to knowledge problems that can be addressed • Natural science is aimed at developing theory – by scientific research not restricted to natural phenomena, can also apply • Sometimes solving a knowledge problem requires to artifacts (contra Simon) solving an action problem • Basic science activities: theorize and justify Nov 2006 Hans Weigand 27 Nov 2006 Hans Weigand 28 Theory and Action March/Smith research framework in balance build evaluat e t heor ize j ust if y theory practice const r uct s knowledge problem knowledge problem knowledge problem model theory problem world problem met hod -lack of t heor y -lack of validit y action problem action problem inst ant iat ion -f alsif icat ion at t empt (wor king pr ogr am) -anomaly Nov 2006 Hans Weigand 29 Nov 2006 Hans Weigand 30 5
  • 6. Ramesh et al Why mathematics? • Based on empirical study of publications • Conceptual clarity – like precise definitions in Law • Focus in CS is on formulating (80%) rather – Could perhaps be reached also by UML diagram than describing or evaluating • As a research method • Research methods: mainly conceptual/ – to validate certain claims mathematical • For the development of a (predictive) theory • Low reference to other discipline (some – not really different from e.g. game theory in Economics mathematics) – Example: relational algebra, complexity theory, .. Nov 2006 Hans Weigand 31 Nov 2006 Hans Weigand 32 Research paradigms in IS Interpretivism • Positivism (Comte) and rationalism (Descartes) • Post-modernism (Foucault, Derrida), cf. The aim of interpretive research is to understand how members of a social community, through their participation in interpretivism, constructivism, … social processes, enact their particular realities and endow • Pragmatism (Peirce, Dewey, Rescher) them meaning, and to show how these meanings, beliefs and • Critical theory (Habermas) intentions of the members help to constitute their social action (Orlowski & Baroudi, 1991) Cf debate between rationalist AI tradition (Schank, Stefik/Bobrow) and Winograd & Flores, to which also Suchman contributed. Nov 2006 Hans Weigand 33 Nov 2006 Hans Weigand 34 Pragmatism Not in the sense of opportunism, but concerned with Critical theory action rather than with being Ch. Peirce “There is no such thing as genuine knowledge and fruitful • Knowledge is not neutral - be critical about understanding except as the offspring of doing… Only by assumptions such as the technical wrestling with the conditions of het problem at first hand, imperative to improve efficiency seeking and finding his own way, does he think“ John Dewey • Knowledge must be legitimated by “Thinking is not different in kind from the use of natural materials and energies ..” consensus and democratic discourse Knowledge of a thing is knowledge of what you can do with it. • Knowledge is not neutral – science should Tries to bridge empirical science and design science. serve social goals such as emancipation Nov 2006 Hans Weigand 35 Nov 2006 Hans Weigand 36 6
  • 7. Research as communication So … • Communicate! (publish, discuss, review,…) • Researchers communicate via papers, • Be clear! (Grice’s conversational maxims) presentations, discussions • Take communication partners seriously! • In communicating, they make descriptive – Read related research – Try to understand and normative statements (validity claims) – Refer • These claims may be challenged by others, – Consider their goals and expectations leading to discussion • Don’t “drop an idea”; try to convince! • Discussion is as essential as research • Justify your claims! activities itself Nov 2006 Hans Weigand 37 Nov 2006 Hans Weigand 38 Maxim of Quantity: 1. Make your contribution to the conversation as informative as necessary. How to justify your claims? 2. Do not make your contribution to the conversation more informative than necessary. Maxim of Quality: "Ik ben er nog steeds van overtuigd dat 1. Do not say what you believe to be false. zoals ik het doe je het moet doen want 2. Do not say that for which you lack adequate evidence. anders zou ik het niet doen." Maxim of Relevance: Be relevant (i.e., say things related to the current topic of the conversation). Maxim of Manner: 1. Avoid obscurity of expression. 2. Avoid ambiguity. 3. Be brief (avoid unnecessary wordiness). 4. Be orderly. Nov 2006 Hans Weigand 39 Nov 2006 Hans Weigand 40 Literature How to justify your claims? • Designing a research project – P. Verschuren, H. Doorewaard. Utrecht, 1999. • Grounding (empirical, simulation, …) • Desiging Information Technology in the postmodern age – R. Coyne, 1997 • Careful reasoning • Qualitative methods in management research – E. Gummesson • Examples (not just for explanation, but to put your claim to the test) • The sciences of the artificial. H. Simon, 1967 • Delimitation • Research in Computer Science: an empirical study -Ramesh et al, 2004 • Be clear about the status of your claim. • Design and natural science research on information technology - March, Smith, 1995 Nov 2006 Hans Weigand 41 Nov 2006 Hans Weigand 42 7