Wednesday, 19 November 2014

Special Issue of DLib on "New Opportunities, Methods and Tools for Mining Scientific Publications"

This special issue contains 14 articles on Mining Scientific Publications and a  report on the Research Data Alliance (RDA) 4th Plenary Meeting.  This might be of interest to those seeking data for simulating science.

To see the titles, authors and abstracts of the 14 articles, go to:
http://www.dlib.org/dlib/november14/11contents.html.


Friday, 17 October 2014

Paper: Simulations suggest that social and natural sciences differ in their research strategies adapted to work for different knowledge landscapes

Simulations suggest that social and natural sciences differ in their research strategies adapted to work for different knowledge landscapes

Do different field of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed different optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. The best technique for all situations simulated, is to adjust the number of researchers needed to explore a knowledge cluster according to the opportunities and the level of crowding in that cluster. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in journals containing a small number of articles. The natural science seem to adapt their research strategies to landscapes with large knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small knowledge clusters. The work shows that quantitative measures estimating differences between social and natural sciences are feasible.
Coming out in PLoS in the next few weeks.

More details and paper at: http://arxiv.org/abs/1403.5107

Wednesday, 15 October 2014

CfP: special issue of Scientometrics on "Simulating the Social Processes of Science"



A Call for Papers for a special issue of Scientometrics on:

“Simulating the Social Processes of Science”

Deadline: 30th April 2015
 (PDF version here)

Motivation

Science is the result of complex interactions between institutions and individuals self-organizing their research. There has been a tendency to depict/sketch science as an individual, cognitive endeavour marked by new ideas, breakthroughs and problem solving activities. However, there is no doubt that science is also substantially a social process.  That is, science relies on many inter-personal processes, including: selection and communication of research findings, discussion of method, checking and judgement of others’ research, development of norms of scientific behaviour, organisation of the application of specialist skills/tools, and the organisation of each field (e.g. allocation of funding).  Furthermore, science is full of the social phenomena that are observed elsewhere: fashions, concern with status and reputation, group-identification, collective judgements, social norms, competitive and defensive actions, to name a few.  

Although we sometimes can directly observe scientists interacting, usually our theorising about this is indirect, via the traces of their behaviour (individual and social) in terms of the documents they produce, such as journal articles, patents or grant applications. Empirical observations of science – in the form of quantitative studies – for a long time remained focuses primarily on traces of formal communication. The simple reason is, those are captured in a structured way in bibliographic databases, and available for analysis. However there are other sources of data about the behaviour of researchers.  These include, for example altmetrics, but also the more qualitative evidence that can be harvested from narratives, interviews, and questionnaires or science history accounts. Agent-based models are particularly suitable for building upon hypotheses derived from such micro-level data as they encapsulate hypotheses about behaviour and produce outputs that can be validated against macro-level observable traces and data (Moss and Edmonds 2005). 

This special issue calls for models that explicitly represent the interactions between individual researchers, capturing aspects of the social processes of science. They may build upon hypotheses about individual behaviour from a variety of sources, including: the sociology of science, cognitive science, or qualitative observations as long as they also are comparable with some kind of validation data. Their heuristic power unfolds when the system under study involves substantial interaction between heterogeneous actors or over within complex networks.  Such models hold out the potential as a complementary tool to the existing range of quantitative and metric approaches. New insights about science can be gained by comparing and relating different kinds of model, including data, statistical, observational, psychological and computational. This special issue aims to present a state of the art in terms such computational models.

The Topic

We are looking for original articles that use simulation methods to understand and explore the social (i.e. inter-researcher) processes that contribute to the phenomena we call science.  These could be simple or complex, agent-based or otherwise, but need to go beyond data analyses and data description approaches that only deal with the relation of macro-level variables.  All models should link individual interactions between researchers to outcomes that are possible to measure (at least in principle).  All models should list their conceptual, epistemic or empirical points of departure – being as clear as possible as to the assumptions on which they are built. Given the focus of the journal, the models should be presented and assessed in formal or numerical ways. They should be validated with empirical data where possible. We are also open to the submission of models that lead to new ideas about measuring and observations and might accept one survey paper covering the field up to the present. However, overall we will favour submissions that take some effort in aligning assumptions and theories with observations and data.

Specific topics could include, but are not limited to, the following:
 

  • How individual and social behaviour of researchers result in citation networks, such as those we observe?
  • When and how researchers choose to co-author papers or write grant applications together?
  • How is current production of scientific knowledge by individuals and groups influenced by project-funded science and evaluation schemes?
  •  How does the individual career path unfolds under the condition of globalization and team science? How the structure and social practices of science impact upon the career of early stage researchers?
  • What are the properties of peer review, including the effectiveness and robustness of alternative systems and what are their influences on scholarship?
  • How academic topics emerge, are maintained and finally fall out of fashion?
  • What are the social and reputational factors behind the success or frustration of interdisciplinary research?
  • How can we describe, analyse and model the impact of different social aspects upon the development of scientific knowledge: trust, reference group identification, honesty, methods of measuring reputation, team working, etc.?

History

Broadly this approach goes back to (Gilbert 1997), but interest in this has recently intensified. There was a workshop, then book on “Models of Science Dynamics” (Scharnhorst et al. 2012), which did not focus on models of the social processes of science, but included a review of agent-based models up to that point (Payette, 2012). Then their followed special issue of position papers on this topic in the Journal of Artificial Societies and Social Simulation, in 2011 (Edmonds et al. 2011), followed by some papers appearing at simulation conferences (ESSA, ECMS, MABS), leading up to the week-long Lorentz Workshop on this topic in April 2014. http://knowescape.org/simulating-the-social-processes-of-science-a-summary. Contributors to this special issue are by no means limited to those involved in the above.

Submission

Although participants of these previous events are encouraged to submit revised and mature versions of their papers, this is an open call that will be freshly peer-reviewed according to the normal standards of Scientometrics, without any prior preference.  However, the editors reserve the right to reject papers that clearly fall out of the scope of this special issue, without review. Therefore, potential contributors are asked to submit their papers prior to the regular reviewing process by email to Bruce Edmonds (bruce@edmonds.name) for possible selection by the 30th April 2015. Authors will then receive instructions for submission along with some technical notes.

Special Issue Editors

  • Bruce Edmonds, Professor of Social Simulation, Centre for Policy Modelling, Manchester Metropolitan University, UK.
  • Andrea Scharnhorst, Royal Netherlands Academy of Arts and Sciences, Data Archiving and Networked Services, Amsterdam, Netherlands

References

Edmonds, B., Gilbert, N., Ahrweiler, P. & Scharnhorst, A. (2011) Special Issue of the Journal of Artificial Societies and Social Simulation  on 'Simulating the Social Processes of Science' 14,(4) (Introduction to special issue is at: http://jasss.soc.surrey.ac.uk/14/4/14.html).
Gilbert, N. (1997). A simulation of the structure of academic science. Sociological Research Online, 2(2), http://www.socresonline.org.uk/2/2/3.html.
Moss, S. and Edmonds, B. (2005) Sociology and Simulation: - Statistical and Qualitative Cross-Validation, American Journal of Sociology, 110(4) 1095-1131.
Payette N. (2012) Agent-based models of science. In Scharnhorst, Börner, and Scharnhorst A., Börner K. & Van den Besselaar, P. (eds.) (2012). Models of Science Dynamics. Springer. Ch 4, pp. 127-157

Saturday, 6 September 2014

Slides from the Session on the Social Processes of Science @ Social Simulation 2014

Session on: Simulating the Social Processes of Science, At Social Simulation 2014, Barcelona.

Chair: B. Edmonds
The slides are available at: http://cfpm.org/spos/SSC2014_session/

Tuesday, 29 April 2014

Collaborators needed to develop a paper on research career structures

Eric Silverman (Southampton) is looking for collaborators who want to develop a paper on research career structures.  The paper will summarise some of the studies done so far on short-term research contracts and their effect on young researchers, particularly women.  The goal will be to identify the interacting factors which affect early-career academics who are trying to develop a career, and use this as a foundation for a modelling project in future.  Anyone who is interested should contact Eric at e.silverman@soton.ac.uk.

Saturday, 12 April 2014

SSPOS resource list (data, tools etc.)

This is the list of resources contributed by workshop participants.

Data set [please add your name, name of data set, and references such as pointer to an archive, ....] 

  • Scholarly Database at IU with 28M papers, patents, grants, clinical trials that can be cross searched. Datasets can be downloaded as dump in easy to process formats.

Data to mimic/factual evidence for beliefs and negotiation
  • Conover, Michael. 2013. "Digital Democracy The Structure and Dynamics of Political Communication in a Large Scale Social Media Stream". Thesis 

Database of data sources

Model tools you use [public such as NetLogo, Java library or tailor made]

  • Stuart Rossiter: MASON as a programmer-friendly transparent Java ABM framework; AnyLogic as a user-focused, visual, multi-paradigm commercial tool (not just ABM); dabbled in Repast Simphony but find it a little too much of a half-way house; intending to use NetLogo more (unfairly branded a 'beginner's ABM tool' IMO) after some previous dabbling in StarLogo.

Data Sources for Models of Academic Careers
  • Enengel,  B., Muhar, A., Penker, M., Freyer, B., Drlik, S., & Ritter, F.  (2011). Co-production of knowledge in transdisciplinary doctoral theses  on landscape development—An analysis of actor roles and knowledge types  in different research phases. Landscape and Urban Planning, 105,  106-117.     

Mailing List

You can subscribe to the mailing of the workshop by sending an email to:

sympa@sympa.ethz.ch

with the following text in the body of the email:

SUBSCRIBE ssps Your Name

(Example)
SUBSCRIBE ssps Stefano Balietti

To unsubscribe use:

SIGNOFF ssps

To send a message the the TO field is

ssps@sympa.ethz.ch

The mailing list is public at the moment, but it will be changed to moderated in the next days when enough people have subscribed.

Peer Review & Open Science

As discussed in the peer review group, the 'future of peer review' is strongly linked with movements towards open access and open science. Some references below which I (Stuart Rossiter) think are particularly good; feel free to comment / add more. (In particular, I think there is a baseline understanding of the landscape needed to avoid naïvely reinventing the wheel in certain ideas.)

Richard Poynder is an open access journalist / commentator with a great neutral viewpoint. His series of (long) interviews with prominent open access figures gives some great background to the people, ideas and progress. If you're interested in Open Access, follow him on Google+: he acts as a broadcast point for all OA developments (including criticisms from publishers, etc.).

Björn Brembs is particularly interesting for ideas on radical restructuring of publication, and Stevan Harnad for the original OA idea and a strong message on Green and Gold OA (see their interviews above). Brembs has also published some data-heavy critiques of journal rank, and his ideas relate to those of Martin Eve (a librarian).

Christopher Lee's Selected Papers Network (SPN) idea is very interesting, and his paper on it really captures all the nuances/problems of (journal) peer review (and as such is a good summary of the 'state of peer review' as well), and pre-empts all the 'yes, but...' questions for his idea. (Jan de Ruiter is also a big fan of this.) It also starts looking at the missing piece: how do reviewers get recognition/kudos for reviewing? Although it would be cool, he's not that  Christopher Lee :-)


For a concrete open peer review platform and journal, Pöschl has a paper about the platform for his ACP journal (which has been in place for some time).

In terms of open science more generally, the Science Code Manifesto is a good starting point (and the founding authors, especially Victoria Stodden, Cameron Neylon and Peter Suber).

Interesting References on Scarce Time Allocation and Science

Geard, Nic and Noble, Jason (2010) 'Modelling Academic Research Funding as a
Resource Allocation Problem', Proceedings of WCSS 2010 <http://eprints.soton.ac.uk/271374/7/fundingModel.pdf>.

Radner, Roy (1975) 'A Behavioural Model of Cost Reduction', Bell Journal of Economics, 6(1), Spring, pp. 196-215. 

A list of actions decided at the plenary session on the last day...

...along with those who agreed to (at least initially) coordinate them.  If you wish to help organise, contribute or be involved in any particular action, please contact the persons named.  News of these will also be posted here.
  • A second SSPOS workshop, Valencia, Spain, in 2016 (jointly supported by PEERE and KnowEScape) -- Bulent Ozel, Francisco Grimaldo, Bruce Edmonds
  • Peer Review Roadmap -- Francisco Grimaldo
  • Relating/mapping models -- Edmund Chattoe-Brown
  • Knowledge of available data sets -- Andrea Scharnhorst (via her list which I will post)
  • List of Stylised Facts & Generative Mechanisms -- Christopher Watts
  • List of Challenge problems -- Bruce Edmonds
  • "SimScience" games -- Andre Martins
  • Overview/position paper (PlosOne?) -- Stuart Rossiter, Bruce Edmonds
  • Publication options in order of preference: JASSS, Frontiers, Scientometrics, Research Policy, Topics in Cognitive Science, Springer book -- Bruce Edmonds

Thursday, 10 April 2014

Bruce Edmonds' slides on "Belief Change via Social Influence and Explanatory Coherence"

At: http://cfpm.org/spos/lcw/Edmonds_Belief_Change_via_Social_Influence_and_%20Explanatory_Coherence_SPOS_LEIDEN_2014.pptx

Alexander Petersen's slides on "Quantifying the role of teamwork and reputation across scientific careers"

At: http://cfpm.org/spos/lcw/Petersen_Quantifying_Role_of_Teamwork_Leiden_2014.pdf

Ingo Scholtes' slides on "When your social position predicts your success: Lessons from Open Source communities and citations"

At: http://cfpm.org/spos/lcw/Scholtes_When_your_social_position_predicts_your_success_Leiden_2014.pdf

Loet Leydesdorff's slides on "Can the Socio-Cognitive Process of Science be Simulated?"

At: http://cfpm.org/spos/lcw/Leydesdorff_Can_Social_Processes_of_Science_be_Simulated_LorentzCenter.April14.pptx

Diego Garlaschelli's slides on "Reconciling long-term cultural diversity and short-term collective social behavior: an interdisciplinary challenge"

Reference: Valori et al., PNAS vol. 109, no. 4, pp. 1068-1073 (2012)

Slides at: http://cfpm.org/spos/lcw/Garlaschelli_Reconciling_2014_04_10%20Lorentz%20Center.pdf

Bülent Özel's slides on "A Multi-agent Simulation Model on Individual Cognitive Structures and Collaboration in Sciences"

At: http://cfpm.org/spos/lcw/Ozel_A%20Multi-agent_Simulation_Model_on_Individual_Cognitive_Structures_and_Collaboration_in_Sciences_SPOS2014.pdf

Wednesday, 9 April 2014

Simulating social processes of science mailing list

homepage
https://sympa.ethz.ch/sympa/info/ssps

SUBSCRIBE ssps Your Name

(Example)
SUBSCRIBE ssps Stefano Balietti

SIGNOFF ssps

Link to document about data sets and tools

https://hackpad.com/SSPoS-resource-list-CUcVelM17bP
To be used directly to share models, datasets

Group photo from workshop...

...Andre Martins, Elena Mas Tur and Ozul Bulent had not arrived by this point.


Slides from Francisco Grimaldo et al on "Mechanisms for science: Leasons learned from modeling peer review"

Mechanisms for science: Leasons learned from modeling peer review
Francisco Grimaldo, Juan Bautista Cabotà (U.València) Mario Paolucci (LABSS- ISTC- CNR)
Flaminio Squazzoni (GECS-U. Brescia)

Available at: http://cfpm.org/spos/lcw/Francisco%20Grimaldo%20Moreno%20et%20al%20P2014-SPOS.pdf

Brainstormed research questions for Interdisciplinarity Group

Brainstormed research questions for Interdisciplinarity Group

  1. How do disciplines emerge/develop? (Foundational)
  2. How can interdisciplinarity help/hinder in the search for knowledge?
  3. Does successful interdisciplinary research lead to a new speciality?
  4. What patterns of expectations lead to lead to success of interdisciplinary approaches? (management of interdisciplinary teams)
  5. What constitutes a successful interdisciplinary project? (Foundational)
  6. What is the impact of participating in interdisciplinary projects on early stage researchers?
  7. What processes facilitate the appearance of interdisciplinary communications?
  8. What are the respective roles of people, ideas, and institutions in the emergence of interdisciplinary research?
  9. What are the challenges involved in doing interdisciplinary projects?
  10. How do we identify disciplines? (Foundational)
  11. How do new problems motivate/cause the emergence of new disciplines?

In answer to the question "How do we identify disciplines?" there were the following suggestions:

  • Coherency of beliefs
  • Similar tools, methods, and reference points
  • Same Heroes
  • Establishing milestones (a conference series, association, journal, summer school, phds etc)
  • Inter-reading
  • Specific markers (prizes, awards etc.)

Tuesday, 8 April 2014

Wednesday morning version of the timetable


Monday
Tuesday
Wednesday
Thursday
Friday

Theme
Context, Positions and Approaches
Models and Underpinnings
Models and Applications
Applications, Open Questions, Directions  and Issues
What next?

9:00
Registration and Coffee
Mario Paolucci and Francisco Grimaldo: developing simulation models of peer review
Alexander Petersen: Quantifying the role of teamwork and reputation
Ingo Scholtes: lessons from open source and citations
Elena Mas Tur: Diffusion of scientific knowledge: a percolation model
Diego Garlaschelli: long-term cultural diversity and short-term collective behaviour
Janusz Holyst: Information slows down hierarchy growth
Breakout groups: further initiatives and funding opportunities

10.00
Introduction to the Lorentz Centre

Nicolas Payette: a survey of previous models

10.30
Coffee break
Coffee break
Coffee break
Coffee break

11.00
Invited Speaker: Katy Börner
Free discussion period around simulations
Free discussion period around simulations
Free discussion period around simulations
Invited Speaker: Paul Thagard

12.30
Lunch
Lunch
Lunch
Lunch
Farewell Lunch

14.00
Brief Introduction to the workshop by organisers
Bruce Edmonds:  incorporating cognitive dissonance with social influence

Coffee break

Free discussion period around simulations
Free discussion period or relaxation
Andre Martins: Theory Acceptance
Bulent Ozel: Individual Cognitive
Structures and Collaboration in Science
Possible extended discussions

Poster Presentations of all participants

15.30
Coffee break
Coffee break

16.00 –
17.00
Frank Schweitzer: Beyond simulating science
Loet Leydesdorff: The exchanges of expectations in scholarly discourse
Short presentations on arising issues from the discussions so far and Open Discussion

17.00 – 17.30
Plenary reports of discussions / developments

Evening
Welcome drinks

Social dinner


Workshop focus questions in order of judged level of interest....

Key Questions in rough order of interest (as judged by a quick show of hands by workshop participants):
  • What data sources are there available to help text/develop simulations of scientific processes?
  • How do the cognitive and social processes interact to develop collective knowledge?
  • What do simulations suggest about the organisation of research?
  • How can we progress our understanding of science using social simulation?
  • How do the social processes contribute to the agreement/disagreement between groups of scientists? 
  • Are there any cognitive "foundations" upon which to base social simulations of science?
  • How is division of labour/specialisation self-organised in science?

Monday, 7 April 2014

Katy Borner's Slides on "Mulit Level Science Models"...

...from her invited talk today are available at:
   http://cns.iu.edu/docs/presentations/2014-borner-scimodeling-nl.pdf

Talks of Elena Mas Tur and Alexander Petersen are now swapped...

...since Elena will not be here until Wednesday.

Thus the timetable looks like this:


Monday
Tuesday
Wednesday
Thursday
Friday

Theme
Context, Positions and Approaches
Models and Underpinnings
Models and Applications
Applications, Open Questions, Directions  and Issues
What next?

9:00
Registration and Coffee
Mario Paolucci and Francisco Grimaldo: developing simulation models of peer review
Alexander Petersen: Quantifying the role of teamwork and reputation
Ingo Scholtes: lessons from open source and citations
Elena Mas Tur: Diffusion of scientific knowledge: a percolation model
Diego Garlaschelli: long-term cultural diversity and short-term collective behaviour
Janusz Holyst: Information slows down hierarchy growth
Breakout groups: further initiatives and funding opportunities

10.00
Introduction to the Lorentz Centre

Nicolas Payette: a survey of previous models

10.30
Coffee break
Coffee break
Coffee break
Coffee break

11.00
Invited Speaker: Katy Börner
Free discussion period around simulations
Free discussion period around simulations
Short presentations on arising issues from the discussions so far
Invited Speaker: Paul Thagard

12.30
Lunch
Lunch
Lunch
Lunch
Farewell Lunch

14.00
Brief Introduction to the workshop by organisers
Andre Martins: Theory Acceptance
Bruce Edmonds:  incorporating cognitive dissonance with social influence
Free discussion period or relaxation
Parallel group discussions on a selection of these issues
Possible extended discussions

Poster Presentations of all participants

15.30
Coffee break
Coffee break
Coffee break

16.00 –
17.00
Frank Schweitzer: Beyond simulating science
Loet Leydesdorff: The exchanges of expectations in scholarly discourse
Free discussion period around simulations
Plenary Reports from Groups and Open Discussion

17.00 – 17.30
Plenary reports of discussions / developments

Evening
Welcome drinks

Social dinner