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Replication of FLOSS Research as eResearch Andrea Wiggins, James Howison, & Kevin Crowston Syracuse University School of Information Studies 12 September 2008 ~ Oxford e-Research Conference
FLOSS Research ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
eResearch for FLOSS ,[object Object],[object Object],[object Object],[object Object],[object Object]
Replicating FLOSS Research ,[object Object],[object Object],[object Object],[object Object]
Studies Selected for Replication Classifies projects based on metrics for success and stage of project growth English & Schweik, 2007 Examines growth rate of software Robles et al., 2005 Examines dynamics of social networks of project communications over time Howison et al., 2006 Examines distribution of project sizes for consistency with preferential attachment theory of growth in scale-free network Conklin, 2004 Applies competency rallying to predict success of projects based on various factors Scozzi & Crowston, 2002 Description Study
Using Taverna ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Building Workflows ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Do the Rich Get Richer? 1: Get data  2: Analyze data
Dynamic Social Network Analysis 1: Get data 2: Manipulate data 3: Analyze & plot
Classification of Projects 1: Get data & prepare it for analysis 2: Classify 3: Analyze classification
Using Workflows ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Comparing Results Developer-project distribution Distribution on log-log scale Original figures Replication
Comparing Analysis Parameters ,[object Object],[object Object],[object Object],[object Object],[object Object]
Sharing Workflows ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned: Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lessons Learned: Design ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Design Strategy: Parameterize ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Design Strategy: Modularity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object]

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Replicating FLOSS Research as eResearch

  • 1. Replication of FLOSS Research as eResearch Andrea Wiggins, James Howison, & Kevin Crowston Syracuse University School of Information Studies 12 September 2008 ~ Oxford e-Research Conference
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  • 5. Studies Selected for Replication Classifies projects based on metrics for success and stage of project growth English & Schweik, 2007 Examines growth rate of software Robles et al., 2005 Examines dynamics of social networks of project communications over time Howison et al., 2006 Examines distribution of project sizes for consistency with preferential attachment theory of growth in scale-free network Conklin, 2004 Applies competency rallying to predict success of projects based on various factors Scozzi & Crowston, 2002 Description Study
  • 6.
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  • 8. Do the Rich Get Richer? 1: Get data 2: Analyze data
  • 9. Dynamic Social Network Analysis 1: Get data 2: Manipulate data 3: Analyze & plot
  • 10. Classification of Projects 1: Get data & prepare it for analysis 2: Classify 3: Analyze classification
  • 11.
  • 12. Comparing Results Developer-project distribution Distribution on log-log scale Original figures Replication
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