Workshop in Sustainable Software for Science: Practice and Experience

Communities

Karen Cranston!
National Evolutionary
...
Communities for sustainable software

Developers

Users

software is
useful & usable

discussion!
help!
feedback

features...
Extensibility
❖

data management is a generic problem!

❖

iRODS = highly customizable data management solution!
❖
❖

❖

m...
Co-ordination of effort
❖

high-energy physics relies computer modeling!

❖

lack of coordination between projects!

❖

pr...
Ketan Maheshwari⇤ , David Kelly⇤ , Scott J. Krieder† , Justin M. Wozniak⇤ ,
Daniel S. Katz‡ , Mei Zhi-Gang§ , Mainak Mookh...
Make it usable
❖

Good software engineering processes
important!
❖

❖

easier for people to use and contribute!

Service-b...
Hackathons
❖

NESCent = (domain scientists) + (in-house
informatics team)!

❖

Hackathon model:
❖

hands-on coding event w...
Identify gaps
❖

Tools & APIs for access to online data / resources!

❖

Direct collaboration / support for data providers...
Good software engineering
❖

More welcoming for developers!

❖

Easier for users to engage / test!

❖

Find common require...
Community engagement

❖

Multiple communication channels!

❖

Direct interaction!

❖

People and centers with cross-over
s...
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WSSSPE: Building communities

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Summary of papers submitted to WSSSPE 2013 that address the role of communities in scientific software.

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WSSSPE: Building communities

  1. 1. Workshop in Sustainable Software for Science: Practice and Experience Communities Karen Cranston! National Evolutionary Synthesis Center! @kcranstn http://wssspe.researchcomputing.org.uk/! Workshop notes at http://bit.ly/wssspe13! These slides: http://www.slideshare.net/kcranstn/wssspe-cranston-community
  2. 2. Communities for sustainable software Developers Users software is useful & usable discussion! help! feedback features added; bugs fixed
  3. 3. Extensibility ❖ data management is a generic problem! ❖ iRODS = highly customizable data management solution! ❖ ❖ ❖ many functions (data access, processing, provenance…)! uses create policies for specific needs! over 25 science & engineering domains in user list! Moore, Reagan M. Extensible Generic Data Management Software. http:// arxiv.org/abs/1309.5372
  4. 4. Co-ordination of effort ❖ high-energy physics relies computer modeling! ❖ lack of coordination between projects! ❖ propose:! ❖ develop teams of technical specialists ! ❖ target many different architectures! ❖ common scripting language / APIs Bruhwiler, David; Vay, Jean-Luc; Cameron G. R. Geddes; Koniges, Alice; Friedman, Alex; P. Grote, David (2013): White Paper on DOE-HEP Accelerator Modeling Science Activities. http://dx.doi.org/10.6084/m9.figshare.793816
  5. 5. Ketan Maheshwari⇤ , David Kelly⇤ , Scott J. Krieder† , Justin M. Wozniak⇤ , Daniel S. Katz‡ , Mei Zhi-Gang§ , Mainak Mookherjee¶ User engagement ⇤ MCS Division, Argonne National Laboratory † Department of Computer Science, Illinois Institute of Technology ‡ Computation Institute, University of Chicago & Argonne National Laboratory § Nuclear Engineering Division, Argonne National Laboratory ¶ Department of Earth and Atmospheric Sciences, Cornell University ❖ Involve scientists in feedback and improvement! Abstract—Effective use of parallel and distributed computing science depends upon multiple interdependent entities and ctivities that form an ecosystem. Active engagement between pplication users and technology catalysts is a crucial activity hat forms an integral part of this ecosystem. Technology catalysts ay a ❖ crucial role benefiting communities beyond a single user roup. An effective user-engagement, use and reuse of tools and chniques has a broad impact on software sustainability. From ur experience, we sketch a life-cycle for user-engagement activity scientific computational environment and posit that application vel reusability promotes software sustainability. We describe ur experience in engaging two user groups from different ientific domains reusing a common software and configuration ❖ n different computational infrastructures. Index Terms—Technology-catalyst, user-engagement, scientific omputation ‘Technology catalysts’: people with domain & technical skills Fig. 1. Activities and transitions in user engagement cycle. identify generic software pattern for running common modern science. In software on different HPC architecture this experience paper, we report on following: 1) Experience in scientific community engagement descr ing activities performed at different levels in order I. I NTRODUCTION support scientific users with applications Maheshwari, K.; D. Kelly, S.J. Krieder, J.M. Wozniak, D.S. Katz, M. Zhi-Gang, M. deployed o Domain scientists often have limited time to investigate the new, Mookherjee. Reusability in Science: From Initial Userlarger and faster systems. Engagement to Dissemination of apabilities that a large scale computing and data-handling 2) A sketch and demonstration the elements of a success Results. http://arxiv.org/abs/1309.1813 frastructure combined with a high performance software scientific application deployment cycle. amework could bring to their scientific activities. Technology
  6. 6. Make it usable ❖ Good software engineering processes important! ❖ ❖ easier for people to use and contribute! Service-based business models! ❖ multiple communication channels, maintenance, training Hanwell, Marcus; Perera, Amitha; Turner, Wes; O'Leary, Patrick; Osterdahl, Katie; Hoffman, Bill; Schroeder, Will (2013): Sustainable Software Ecosystems for Open Science. http:// dx.doi.org/10.6084/m9.figshare.790756
  7. 7. Hackathons ❖ NESCent = (domain scientists) + (in-house informatics team)! ❖ Hackathon model: ❖ hands-on coding event with users, researcherdevelopers, software engineers! ❖ Community mailing list critical resource years later Cranston, Karen; Vision, Todd; O'Meara, Brian; Lapp, Hilmar (2013): A grassroots approach to software sustainability. http://dx.doi.org/10.6084/m9.figshare.790739
  8. 8. Identify gaps ❖ Tools & APIs for access to online data / resources! ❖ Direct collaboration / support for data providers! ❖ Workshops and training for users Chamberlain, Scott; Hart, Edmund; Ram, Karthik; Boettiger, Carl (2013): rOpenSci - a collaborative effort to develop R-based tools for facilitating Open Science.! http://dx.doi.org/10.6084/m9.figshare.791569
  9. 9. Good software engineering ❖ More welcoming for developers! ❖ Easier for users to engage / test! ❖ Find common requirements across projects! ❖ Don’t neglect usability ! ❖ Open-source software!
  10. 10. Community engagement ❖ Multiple communication channels! ❖ Direct interaction! ❖ People and centers with cross-over skills

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