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Research 2.0 Fridolin WildKMi, The Open University f.wild@open.ac.uk
“the application of new practices that focus on opening up the research process to broaden participation and collaborationwith the help of new technologies that are able to foster continuous engagement and further development.” (Ullmann et al., 2010) Research 2.0
practices
The scientific method (1.0) In its popular version: http://en.wikipedia.org/wiki/Scientific_method Four essential elements[34][35][36] of a scientific method[37] are iterations,[38][39]recursions,[40]interleavings, or orderings of the following:  Characterizations(observations,[41] definitions, and measurements of the subject of inquiry) Hypotheses[42][43] (theoretical, hypothetical explanations of observations and measurements of the subject)[44] Predictions (reasoning including logicaldeduction[45] from the hypothesis or theory) Experiments[46] (tests of all of the above) … and the same in linear form: Define a question Gather information and resources (observe) Form an explanatory hypothesis Perform an experiment and collect data, testing the hypothesis Analyze the data Interpret the data and draw conclusions that serve as a starting point for new hypothesis Publish results Retest (frequently done by other scientists)
Remember: it took a while for this method to gain ground in Computer Science ;)
The scientific method (0.5) ‘Advocacy research’ “Remember the term advocacy research? … much research consisted of the model that some characterized as‘conceive an idea, analyze the idea, advocate the idea’. At the conclusion of many research papers was a discussion of the implications for practice, which usually concluded with the claim that the idea should be transferred to practice as quickly as possible. Or words to that effect.” “Colin Potts referred to this as the ‘research-then-transfer’approach, contrasting it with what he called the ‘industry-as-laboratory’approach.” (Glass, 1994)
The scientific method is surely not outdated. And don’t worry: people are already patching it (cf. Shneiderman et al., 2011).
The scientific method 2.0 = the method of conducting (1.0)  	+ an open method of communicating,      supported with Web 2.0 technology
Research 2.0 practices (STELLARNET d6.3, 2009: expert brainstorming)
Research 2.0 practices (Kraker, 2010: focus groups)
As with all methods, there is a secret hope:maybe this helps to increase also quality.
“What was this crisis? It was the realization that occurred, right around the turn of the century, that research in computing and software - as it was then focused - was all too often both arrogant and narrow. It was arrogant because many computing researchers of that era were doing research in a topic they thought they understood, but didn’t. It is amazing that, in retrospect, those computer scientists simply didn’t know what they didn’t know. It was narrow because, of all the research models twentieth century computer scientists might have used, most of them were stuck using only one of them.” (Glass, 1994) Again: not new. quality is in constantly in crisis.
participation
Participants: the problem ,[object Object],With conflicting leitmotifs of academic versus vocational primacy: academic autonomy versus vocational qualification (cf. Oechsle & Hessler, 2011) ‘Ivory tower’ versus profit-oriented, mainstream-only ‘flatlands’ Competing with other opportunities for knowledge development (such as industry)
Flip Coin
What if we could broaden participation?
“Instead of relying solely on the traditional ‘cottage industry’ model in which a small group of researchers in a single location do everything from data collection to analysis and publication of the results, more and more science is conducted as industrial-scale projects, with large, often globally dispersed teams focused on a particular task.” (Hannay, 2010)  From the cottage industry modelto far-flung teams
… and to Mass participation “Social Media Technologies […] facilitate remarkably diverse and broad participation while accelerating the formation of effective collaborations.” (Shneiderman et al., 2011) “Science 2.0 is about more than improved workflows, efficiency and sharing within communities, it also offers opportunities to greatly broaden participation beyond existing scientific communities and bridge between communities.” (Underwood et al., 2009)
The visible commons “Social media are already restructuring the ways in which scholars form collaborations and communicate their results. What used to be called theinvisible college of personal scholarly communications is now a vast and highly visible, searchable, and influential infrastructure.” (Shneiderman et al., 2011)  These new scholarly social networks, the visible commons, ignite hot topics, accelerate data sharing, and enable rapid refinements to theories in ways that were never before possible.” (Shneiderman et al., 2011)
New Mechanisms neededfor broadened participation From R to R2: from Retrieval to Retrieval & Recommendation From reference lists to clustered co-authorship networks From 1:1 mail exchange to webcasting with social media With microattribution: “scholarly credit for the many small contributions that people make” (Hannay, 2010) And with Open peer reviews (cf. Cronin, 2011; Peer Review Survey, 2009): 32% of researchers believe the current peer review system is the best we can achieve. But what about the other 68%?  58% would be less likely to review if their signed report was published;  76% favor the double-blind system;  73% say that technological advances have made it easier to review;  84% believe that without peer review there would be no control in science;  61% rejected an invitation to review an article in the last year;  86% say they enjoy reviewing and will continue to review. From wikipedia.org to stateoftheart.net
“Not every computing scientist will be interested in studying social media, but computing science social media research can have a profound impact on every discipline.” (Shneiderman et al., 2011)
technologies
Simply not good enough Against popular belief, uptake of web 2.0 in scholarly communication is not a “being of special interest of the younger. […] In particular, degree of adoption is positively associated with older age groups […] [and] more senior positions”. (Procter et al., 2011) “One reason for this is clear: current tools simply aren’t good enough.” (Hannay, 2010)
Today: progress (see papers) Reinhardt et al.: scientific event management Moedritscher: activity recommendations De Vocht et al.: aggregation of scientific event data from social media Tomberg et al.: CfPontology See also the earlier workshops: Science 2.0 (ECTEL 2009) and Research 2.0 (ECTEL 2010)
summary
Research 2.0: a paradigm shift? Surely it is a “mélange of sociology, enthusiasm and scientific promise” (Wikipedia on Kuhn) Promise: New theories evolving (connectivism, culturalism, network science, …) Sociology: extended scientific method And a lot of Enthusiasm
My big question to you: What are the next grand challenges to be mastered? How will we know if we mastered them? When?
BEWARE. THE END IS NEAR.

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I-Know'11: Track: Recommendation, Data Sharing, and Research Practices in Science 2.0 (invited talk)

  • 1. Research 2.0 Fridolin WildKMi, The Open University f.wild@open.ac.uk
  • 2. “the application of new practices that focus on opening up the research process to broaden participation and collaborationwith the help of new technologies that are able to foster continuous engagement and further development.” (Ullmann et al., 2010) Research 2.0
  • 4. The scientific method (1.0) In its popular version: http://en.wikipedia.org/wiki/Scientific_method Four essential elements[34][35][36] of a scientific method[37] are iterations,[38][39]recursions,[40]interleavings, or orderings of the following: Characterizations(observations,[41] definitions, and measurements of the subject of inquiry) Hypotheses[42][43] (theoretical, hypothetical explanations of observations and measurements of the subject)[44] Predictions (reasoning including logicaldeduction[45] from the hypothesis or theory) Experiments[46] (tests of all of the above) … and the same in linear form: Define a question Gather information and resources (observe) Form an explanatory hypothesis Perform an experiment and collect data, testing the hypothesis Analyze the data Interpret the data and draw conclusions that serve as a starting point for new hypothesis Publish results Retest (frequently done by other scientists)
  • 5. Remember: it took a while for this method to gain ground in Computer Science ;)
  • 6. The scientific method (0.5) ‘Advocacy research’ “Remember the term advocacy research? … much research consisted of the model that some characterized as‘conceive an idea, analyze the idea, advocate the idea’. At the conclusion of many research papers was a discussion of the implications for practice, which usually concluded with the claim that the idea should be transferred to practice as quickly as possible. Or words to that effect.” “Colin Potts referred to this as the ‘research-then-transfer’approach, contrasting it with what he called the ‘industry-as-laboratory’approach.” (Glass, 1994)
  • 7.
  • 8. The scientific method is surely not outdated. And don’t worry: people are already patching it (cf. Shneiderman et al., 2011).
  • 9. The scientific method 2.0 = the method of conducting (1.0) + an open method of communicating, supported with Web 2.0 technology
  • 10. Research 2.0 practices (STELLARNET d6.3, 2009: expert brainstorming)
  • 11. Research 2.0 practices (Kraker, 2010: focus groups)
  • 12. As with all methods, there is a secret hope:maybe this helps to increase also quality.
  • 13. “What was this crisis? It was the realization that occurred, right around the turn of the century, that research in computing and software - as it was then focused - was all too often both arrogant and narrow. It was arrogant because many computing researchers of that era were doing research in a topic they thought they understood, but didn’t. It is amazing that, in retrospect, those computer scientists simply didn’t know what they didn’t know. It was narrow because, of all the research models twentieth century computer scientists might have used, most of them were stuck using only one of them.” (Glass, 1994) Again: not new. quality is in constantly in crisis.
  • 15.
  • 17. What if we could broaden participation?
  • 18. “Instead of relying solely on the traditional ‘cottage industry’ model in which a small group of researchers in a single location do everything from data collection to analysis and publication of the results, more and more science is conducted as industrial-scale projects, with large, often globally dispersed teams focused on a particular task.” (Hannay, 2010) From the cottage industry modelto far-flung teams
  • 19. … and to Mass participation “Social Media Technologies […] facilitate remarkably diverse and broad participation while accelerating the formation of effective collaborations.” (Shneiderman et al., 2011) “Science 2.0 is about more than improved workflows, efficiency and sharing within communities, it also offers opportunities to greatly broaden participation beyond existing scientific communities and bridge between communities.” (Underwood et al., 2009)
  • 20. The visible commons “Social media are already restructuring the ways in which scholars form collaborations and communicate their results. What used to be called theinvisible college of personal scholarly communications is now a vast and highly visible, searchable, and influential infrastructure.” (Shneiderman et al., 2011) These new scholarly social networks, the visible commons, ignite hot topics, accelerate data sharing, and enable rapid refinements to theories in ways that were never before possible.” (Shneiderman et al., 2011)
  • 21. New Mechanisms neededfor broadened participation From R to R2: from Retrieval to Retrieval & Recommendation From reference lists to clustered co-authorship networks From 1:1 mail exchange to webcasting with social media With microattribution: “scholarly credit for the many small contributions that people make” (Hannay, 2010) And with Open peer reviews (cf. Cronin, 2011; Peer Review Survey, 2009): 32% of researchers believe the current peer review system is the best we can achieve. But what about the other 68%? 58% would be less likely to review if their signed report was published; 76% favor the double-blind system; 73% say that technological advances have made it easier to review; 84% believe that without peer review there would be no control in science; 61% rejected an invitation to review an article in the last year; 86% say they enjoy reviewing and will continue to review. From wikipedia.org to stateoftheart.net
  • 22. “Not every computing scientist will be interested in studying social media, but computing science social media research can have a profound impact on every discipline.” (Shneiderman et al., 2011)
  • 24. Simply not good enough Against popular belief, uptake of web 2.0 in scholarly communication is not a “being of special interest of the younger. […] In particular, degree of adoption is positively associated with older age groups […] [and] more senior positions”. (Procter et al., 2011) “One reason for this is clear: current tools simply aren’t good enough.” (Hannay, 2010)
  • 25. Today: progress (see papers) Reinhardt et al.: scientific event management Moedritscher: activity recommendations De Vocht et al.: aggregation of scientific event data from social media Tomberg et al.: CfPontology See also the earlier workshops: Science 2.0 (ECTEL 2009) and Research 2.0 (ECTEL 2010)
  • 27. Research 2.0: a paradigm shift? Surely it is a “mélange of sociology, enthusiasm and scientific promise” (Wikipedia on Kuhn) Promise: New theories evolving (connectivism, culturalism, network science, …) Sociology: extended scientific method And a lot of Enthusiasm
  • 28. My big question to you: What are the next grand challenges to be mastered? How will we know if we mastered them? When?
  • 29. BEWARE. THE END IS NEAR.