Campus Cyberinfrastructure Guy Almes, ECAR-CCI Working Group Chair Director, Academy for Advanced Telecommunications and Learning Technologies, Texas A&M University ECAR Annual Meeting 28 January 2014 • Tempe, AZ http://www.educause.edu/ecar/ecar-working-groups/campus-cyberinfrastructure-working-group

Past Work: NSF CACI Reports From early 2011 through May 2012, we studied all six of the Task Force Reports to NSF’s Advisory Committee for Cyberinfrastructure. Grand Challenges HPC Data and Visualization Software Learning and Workforce Campus Bridging and wrote a white paper that, for each Report, summarized, reinforced, critiqued, and offered applications to ourselves.

Past Work: Transitioning to IPv6 In October 2013, we issued a focused report on “Transitioning to IPv6”. This complements the technical leadership of (e.g.) the Internet2 IPv6 Working Group. Key claim: There is a strong “value proposition” for each campus to transition to (include) IPv6 as a normative part of their network Very short aspect: “Staying with classic IPv4” is not an option Also, this led to an interesting twist on ECAR rules

Current Work: Big Data We are now moving toward the completion of a study of how the phenomena of “big data” impacts research campus cyberinfrastructure. Think of “big” as suggesting “some aspects of the bigness is a key challenge in getting things done”. Aspects: Volume Velocity Variety Veracity

Challenges due to Volume Good news: 3 TByte drives are inexpensive. Bad news: the value to users of large datasets is growing even faster, so creating and operating file systems in the petabyte range So funding, highly expert staffing are important. Comment on Jevons Paradox Also, Volume drives the difficulty of moving data across the country

Challenges due to Velocity Rate of production of new data What to discard; what to keep? Large Hadron Collider as an example

Challenges due to Variety and Veracity Deeper challenges of scientific data management Metadata needs for searching Unfortunately, more discipline-specific than we’d like Issues relating to provenance Documenting the data, where did it come from Issues relating to reproducibility Could you repeat an experiment 10 years from now? Example from genomics

Elements of a Vision Consider a new faculty member Over a period of, say, 30 years, they will gather data, crunch, produce data, evolve their codes, share with colleagues How could that faculty member organize their data and codes so that, e.g., a student 15 years from now could work from a recently completed project?

Challenges to funding agencies NSF and other funding agencies are requiring data management plans, but this is often perceived as a hassle These funding agencies could identify emerging best practices from the best of these plans They could then identify/fund the creation of tools needed to make adopting such best practices relatively easy Then they could encourage adoption of these best practices by PIs

Challenges to InCommon Controlled sharing of datasets is a broad theme At least notionally, consider the use of “Access Control Lists” to name the individuals/groups who may read or write a given dataset Emerging technologies from InCommon could support nationwide approaches to naming such individuals/groups

Challenges to the Internet2 community Moving big data is increasingly hard. For example, the time required to move $100 worth of storage across the country is increasing over time. Emerging technologies, including 100-Gb/s wide-area networks (both Internet2 backbone and RONs) and the ScienceDMZ structure on our campuses, are helping us address this

Challenges to ourselves The CCI WG has participants from (at least) two groups on campus: HPC computing groups, experienced at supporting computing and, increasingly, highly capable parallel file systems Library groups, experienced at organizing data in the increasingly digital university setting How can we, together, support our researchers to address the data management challenges resulting from big data

Broad CCI emphases Enabling campus CI as an enabler of research by faculty, students, and staff Whatever, of a conceptual, technical, or practical nature, inhibits this enabling is an enemy