The document outlines various research and academic software projects led by Mercè Crosas at Harvard University, focusing on building user-friendly, open-source technology solutions to enhance research transparency, data sharing, and academic website creation. It highlights specific projects like Dataverse for data management, OpenScholar for website building, and Zelig for statistical analysis, along with best practices in software development. The overall goal is to empower researchers through technology while promoting community engagement and continuous improvement.

1. Research and Academic
Software Projects
at the Institute for
Quantitative Social Science
Mercè Crosas, Ph.D.
Chief Data Science andTechnology Officer
IQSS, Harvard University
twitter: @mercecrosas web: mercecrosas.com

2. The Big Picture
Identify a
problem or
need in
research or
academia

3. The Big Picture
Identify a
problem or
need in
research or
academia
Build a
technology
solution,
easy- to-use,
gives control
to researcher

4. The Big Picture
Identify a
problem or
need in
research or
academia
Build a
technology
solution,
easy- to-use,
gives control
to researcher
Generalizable,
Open-source

5. The Big Picture
Identify a
problem or
need in
research or
academia
Build a
technology
solution,
easy- to-use,
gives control
to researcher
Build a
community
that makes
the
technology
better
Generalizable,
Open-source

6. Example: Dataverse

7. Example: Dataverse
๏ How do we increase data sharing to
improve research transparency and
replication with incentives to
researchers?

8. Example: Dataverse
๏ How do we increase data sharing to
improve research transparency and
replication with incentives to
researchers?
๏ Provide a repository solution, where
researchers have control of branding
and access of their data, and get credit
through data citation.

9. Example: OpenScholar

10. Example: OpenScholar
๏ How do we enable scholars to build
their academic web sites in a cost
effective way?

11. Example: OpenScholar
๏ How do we enable scholars to build
their academic web sites in a cost
effective way?
๏ Provide a web site builder with pre-set
features for academics, where a single
hosting serves thousands of sites.

12. Example: Zelig

13. Example: Zelig
๏ How do we simplify using thousands of
R statistical methods built by different
authors?

14. Example: Zelig
๏ How do we simplify using thousands of
R statistical methods built by different
authors?
๏ Provide a statistical package that uses
the same three commands for all
methods, with consistent
documentation.

15. Example: Consilience

16. Example: Consilience
๏ How do we make sense of thousands
(or millions!) of texts?

17. Example: Consilience
๏ How do we make sense of thousands
(or millions!) of texts?
๏ Provide an application that helps
researchers explore many possible
ways of categorizing documents.

18. The Process
Research,
standards &
best practices
Development,
testing &
releases
Input
from users,
community,
stakeholders
Dataverse
Case Study

19. metadata standards,
harvesting protocols,
data transfer, data
citation, provenance,
connecting to journals,
integrating with cloud
computing, ….
The Process
Research,
standards &
best practices
Development,
testing &
releases
Input
from users,
community,
stakeholders
Dataverse
Case Study

20. metadata standards,
harvesting protocols,
data transfer, data
citation, provenance,
connecting to journals,
integrating with cloud
computing, ….
The Process
Research,
standards &
best practices
Development,
testing &
releases
Input
from users,
community,
stakeholders
Dataverse
Case Study
usability testing,
community calls,
annual community
meeting, pull
requests

21. The Process DetailsDataverse
Case Study

22. The Process DetailsDataverse
Case Study
An agile process, integrating Waffle + GitHub + Jenkins, including these steps:

23. The Process DetailsDataverse
Case Study
An agile process, integrating Waffle + GitHub + Jenkins, including these steps:
Backlog > Ready > Dev > Code Review > QA > Usability Test > Polishing > Done

24. The Process DetailsDataverse
Case Study
An agile process, integrating Waffle + GitHub + Jenkins, including these steps:
Backlog > Ready > Dev > Code Review > QA > Usability Test > Polishing > Done
Pull Requests

25. Not only Best Practices in
Process, but also in Coding

26. Not only Best Practices in
Process, but also in Coding

27. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.

28. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.

29. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.

30. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.
4. Don't repeat yourself (or others).

31. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.
4. Don't repeat yourself (or others).
5. Plan for mistakes.

32. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.
4. Don't repeat yourself (or others).
5. Plan for mistakes.
6. Optimize software only after it works correctly.

33. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.
4. Don't repeat yourself (or others).
5. Plan for mistakes.
6. Optimize software only after it works correctly.
7. Document design and purpose, not mechanics.

34. Not only Best Practices in
Process, but also in Coding
1. Write programs for people, not computers.
2. Let the computer do the work.
3. Make incremental changes.
4. Don't repeat yourself (or others).
5. Plan for mistakes.
6. Optimize software only after it works correctly.
7. Document design and purpose, not mechanics.
8. Collaborate.

35. Impact at Harvard
6,833 OpenScholar sites created
13,904 Registered users
75,378 Publications posted
24 Academic departments

36. Impact at Harvard
243 Dataverses from Harvard affiliates
1,226 Datasets by Harvard affiliates as authors
1,427 Registered Harvard users

37. Broader Impact

38. Dataverse world-wide impact

39. Dataverses by Category

40. Datasets by Subject

41. 53 Stats Models, easy-to-use

42. Thank you!
Presented by @mercecrosas mercecrosas.com
dataverse.org
dataverse.harvard.edu
openscholar.org
projects.iq.harvard.edu
scholar.harvard.edu
zeligproject.org
Coming soon!
iq.harvard.edu