This document analyzes the community dynamics of three open source bioinformatics projects (BioJava, Biopython, and BioPerl) over their lifetimes of 10+ years based on mailing list and version control data. It finds that most users are only active for their first 3 years before leaving, with survival rates declining over time, but those who survive longer than 3 years tend to remain engaged indefinitely. It also analyzes the social networks of the communities and finds indicators of "core generations" that evolve every 5 years and help define the projects' organization structures. Threats to the validity of the findings are also discussed.

1. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
Community Dynamics in Open
Source Software Projects:
Aging and Social Reshaping
Anna Hannemann and Ralf Klamma
RWTH Aachen University
Advanced Community Information Systems (ACIS)
hannemann@dbis.rwth-aachen.de

2. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-2
Motivation for Study Settings
 Address interdisciplinary projects (Bioinformatics)
– Biology meets Computer Science
– High disparities in level of development experience
– Better approximation for end-user integration in
community information systems (Lead User1, Open
Innovation2, etc.)
 Analysis of long-tail: based on mailing lists
 Dynamic analysis: community evolution
– Demographic perspective
– Social structure perspective1 von Hippel, E. “Lead users: a source of novel product concepts”, 1986
2 Chesbrough, H. “Open Innovation: The new imperative for creating and profiting from technology”, 2003

3. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-3
Open Bio*
 BioJava, Biopython, BioPerl
 Similar problems, infrastructure, organizational issues
 Open Bioinformatics Foundation
 Long-term: over 13 years
Project* #Messages #User in ML #Commits #Developers LOC
BioJava 11951 2208 8267 94 290608
Biopython 16108 1138 16868 143 249566
BioPerl 31755 2824 12848 139 383351
* [Data on May 20, 2013]

4. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-4
Newcomers vs. Survived Users
BioJava

5. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-5
Newcomers vs. Survived Users
Biopython

6. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-6
Newcomers vs. Survived Users
BioPerl

7. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-7
External Factors
 High attention to Bioinformatics due to
sequencing of human genome
 Cross-project influence: rich get richer
 Personal aspects:
– doing PhD for 3 years
– being in a project with room for OSS

8. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-8
Population Ecology
 Year of birth t0i: date of the first message from user i
to project mailing list
 Age group (x; x+1): all currently active project
participants participating in the project for min x and
max x+1 years
 Currently active: at least one posting to the mailing
lists in current year
 Survival rate (x; x+1)è(x+1; x+2): percentage of
active users in age group (x; x+1) in the last year,
who still active in the current year

9. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-9
Population Ecology, Example 2010
 Age groups
– (0,1) people started in 2010
– (1,2) people started in 2009, still active in 2010
– (2,3) people started in 2008, still active in 2010
– …
 Survival rates
– |(1,2)|2010/|(0,1)|2009
– |(2,3)|2010/|(1,2)|2009
– |(3,4)|2010/|(2,3)|2009
– ...

10. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-10
Demographic Forecast
P0 = 0;1( )! (1;2)"# $% & 20%
P1 = 1;2( )! 2;3( )"# $% & 40%
Pm = x;x +1( )! (x +1;x + 2)"# $% & 90%,'x >1
 Power-law distribution of survival rates
 Rebirth phenomena

11. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-11
Conclusions and Discussion (1)
 Survival pattern:
– Prediction of minimal number of newcomers required to
support the same level of participation
– Longer than three years survives only 7.2%
– Who saves over three years, stays “forever”
 No maximal participation duration
– Number of “oldies” increases continuously
– Possible seclusion against newcomers
newcomer t+1
! 0;1( )t
*0.2 + 1;2( )t
*0.4+… x;x +1( )t
*0.9,"x >1

12. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-12
Social Network Analysis
 Social Network (1 for each year)
– Nodes: Email Participants
– Relations: Same thread
 Shortest path
 Diameter
 Node betweenness
 Largest connected component
 Density
 Transitivity
 Edge betweenness clustering
Biopython Network for 2012

13. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-13
Social Measures

14. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-14
Dynamic of Diameter
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
5
6
7
8
9
10
11
12
Diameter
Dynamic of Diameter
BioJava
Biopython
BioPerl

15. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-15
Dynamic of Max Betweenness
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
MaximalBetweenness
Normalized
Dynamic of Maximal Betweenness
BioJava
Biopython
BioPerl

16. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-16
BioJava, Social Network, 2006

17. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-17
Biopython, Social Network, 2005

18. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-18
BioPerl, Social Network, 2004

19. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-19
BioJava, Core Evolution

20. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-20
Biopython, Core Evolution

21. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-21
BioPerl, Core Evolution

22. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-22
Development Evolution, Biopython

23. TeLLNet
Lehrstuhl Informatik 5
(Information Systems)
Prof. Dr. M. Jarke
I5-FL-MMYY-23
Conclusion and Discussion (2)
 Core evolution
– Evolves strongly
– Core generations (ca. 5 year periods)
– Dangerous for the whole project
– Defines organizational principles
– Can be predicted by combination of diameter and max
betweenness
 Threats to Validity
– Evolution step size (year to year, release to release, etc.)
– Scientist driven OSS
– Construct validity: quality of data; network construction
– Internal validity: observation – explanation