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Presentation at WebEx Meeting June 15, 2012 1 Slide 2 Context Challenge Anticipated Outcomes Framework Timeline & Guidance Comment and Questions 2 Slide 3 Integrative and multi-scale Not bound by organizational limits Multi-disciplinary collaboration Data Forests Heterogeneous Distributed, diverse Central repositories Data needs to be accessible and interoperable across funding agency and national boundaries 3 Slide 4 Diverse sources and sizes. Simulations, experiments, observations From a variety of disciplines Connected, distributed, or centralized. Across a range of length and time scales, resolutions, and accuracies. 4 Slide 5 Multi-scale approaches 5 Slide 6 6 A modeling paradigm: solving complex nanostructures. No single data set contains sufficient information by itself to constrain a unique solution. Experimental tools Computational tools Digital Data Digital Data Slide 7 7 Leveraging internet models, to optimize the global Physical Internet for distribution of goods worldwide to minimize time, energy consumption and cost. Efficient real-time access, processing, interpretation and management of global sensory and event data is a fundamental element of this work at the (CELDi) Center for Excellence in Logistics and Distribution Universities: Arkansas, Clemson, Berkeley, Oklahoma, Missouri, Arizona State, Oklahoma State, Virginia Tech Members: Over 25 members from industry and government Slide 8 A charrette is a collaborative session in which a group of designers drafts a solution to a problem. Often refers to activities that are focused on producing actionable plans for future funding. The DataWay charrette is the beginning of a process. To engage the community in developing strategies that identify and support the emergence of broadly useful ideas for a data infrastructure that facilitates and promotes efficient data utilization and management across the research communities. 8 Slide 9 An engaged community, increasingly contributing to an interactive website. A growing repository of white papers defining the elements of key issues. Iterative discovery process leading to consensus on the best approaches. Integrated and sustained connections among elements of the discovery process. 9 Slide 10 Comprehensive and integrated CI To transform research, innovation and education Focus on computational and data-intensive science to address complex problems Four major components Data-enabled science New computational infrastructure Community research networks Access and connections to CI facilities Slide 11 DataNet Long-term preservation and access of data Data Infrastructure Building Blocks (DIBBs) Software Infrastructure for Sustained Innovation (SI 2 ) Cyber-Enabled Discovery and Innovation (CDI) Data enabled science and engineering Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA) Slide 12 12 Build strategies that support the development of infrastructure that will: Slide 13 13 An infrastructure framework that supports dataAn infrastructure framework that supports data Collection Curation Analysis Visualization Integration Searching for data sets from experiments and simulations from many sources and at many scales. Salient issues includeSalient issues include Validation Annotation Interoperability Ontology Slide 14 http://sydney.edu.au/engineering/it/~shhong/temporal.htm 14 Slide 15 Support the development of integrated and interactive services that transcend fields and accelerate discovery in complex, multi-scale problems. Create interoperable digital-access infrastructures, providing open, extensible and sustainable networks. Foster collaborations and the sharing of observations, simulations, and other relevant scientific information. Facilitate data transfer between individual researchers and data systems & applications. Integrate research and education. 15 A common architecture is needed to produce an effective, interworking, sustainable system to: A common architecture is needed to produce an effective, interworking, sustainable system to: Slide 16 Jun 2012Jul-Sept 2012Oct 2012Nov/Dec 2012Nov/11-Apr/13May 2013 DCL Released Two WebEx events Charrette Short-term enabling awards Proposed framework approaches developed 16 Slide 17 17 The charrette planning process is open to all. We welcome a wide range of ideas and strategies Participant selection will consider the collective: Expertise in relevant cyberinfrastructure, data management, and software fields Representation of a broad range of scientific domains Slide 18 NSF will work with the community to prepare for the charrette. An emphasis on engaging and connecting research: both in communities where data-enabled science is already a focus, as well as other communities on the cusp of data science. We seek participation from other government agencies (e.g. DOE, NIH, NASA) and the scientific communities they support. We seek participation from other countries, particularly in Europe and Asia, and projects they support, especially those that need to share data across countries. Expected outcomes from the charrette include multiple enabling awards to design framework(s) and build community involvement. 18 Slide 19 A DataWay website will provide information on the charrette. Guidance for the community Preparation instructions FAQs The charrette will be in October. A final date will be announced on the website and in a Dear Colleague Letter. A second webinar will be held in August. Questions/comments to DataWay@nsf.gov 19 Slide 20 Where discoveries begin 20 Slide 21 21