We present Brown Dog, two highly extensible services that aim to leverage any existing pieces of code, libraries, services, or standalone software (past or present) towards providing users with a simple to use and programmable means of automated aid in the curation and indexing of distributed collections of uncurated and/or unstructured data. Data collections such as these encompassing large varieties of data, in addition to large amounts of data, pose a significant challenge within modern day "Big Data" efforts. The two services, the Data Access Proxy (DAP) and the Data Tilling Service (DTS), focusing on format conversions and content based analysis/extraction respectively, wrap relevant conversion and extraction operations within arbitrary software, manages their deployment in an elastic manner, and manages job execution from behind a deliberately compact REST API. We describe both the motivation and need/scientific drivers for such services, the constituent components that allow for arbitrary software/code to be used and managed, and lastly an evaluation of the systems capabilities and scalability.

DIBBs Brown Dog is a recent cyberinfrastructure effort which aims to create two new services to aid users in the searching, accessing, and usage of digital data and provide these services in a manner that is as broadly and easily accessible as possible. At its lowest level, the Data Access Proxy (DAP) providing file format conversion capabilities and the Data Tilling Service (DTS) providing content based extractions, will be accessible via a deliberately compact REST interface. On top of this a number of client libraries and applications can and are being constructed to even further reduce the overhead of accessing the provided functionality (e.g. libraries in Javascript, Python, R, Matlab and interfaces such as bookmarklets, browser extensions, and other standalone applications). At the heart of the two services, however, is their extensibility, allowing one to potentially incorporate any library or tool as a conversion or extraction component within the services towards both the leveraging of the functionality they provide as well as the preservation of the tools themselves.

This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research?

An ongoing US National Science Foundation-funded project, the Institute for Chemistry Literacy through Computational Science (ICLCS), involves instructing rural Illinois high school chemistry teachers in the educational uses of computation. The project's training helps participants become educational leaders and change agents. In this article, we report on the participants and their students' classroom experiences and discuss how petascale computing will impact educational uses of computational science and further promote scientific literacy..