How Will Applications Drive Future Data-Intensive Systems? Data-Intensive Computing Workshop Applications Break-Out Session.

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Presentation transcript:

How Will Applications Drive Future Data-Intensive Systems? Data-Intensive Computing Workshop Applications Break-Out Session

Some Driving Applications Google-style Search Social Networking (Facebook/Twitter) Data warehouse mining Biomedical Sensor networks (e.g., video, radar) Cosmology Astro Climate Fusion Machine translation National security Disaster preparedness Financial analytics GIS Many Domains benefit from Data-Intensive Computing

Common Application Structures Big Data Derived Data Query backgroundlive Anticipated vs. ad hoc analysis/queries Derived Data Query

Application Trends: Scale E.g., Climate Change Studies need: 5 orders of magnitude data scale 5 orders of magnitude speed scale (including algorithmic improvements) But More than That…

Application Trends: Features SW as service, pervasive mobile clients P2P interaction Built-in verifiability/ provenance of answers Too much raw data; must decide what (derived) data to retain Dealing with privacy controls, role-based authentication Multi-resolution, Multi-D visualization (multi-sensory presentation) at scale Queries expressed using multimedia Heterogeneity, Cross data sources Increased value of data=>increased demand for data security/integrity Big Data Challenges: Around the Corner for All of Us

Reducing App Development Time Key issues: Effective workflow tools: need for convergence to open, standard tools (Multi-user: Tasks are collaborative) Effective big data libraries & frameworks Avoid recoding when scale changes Use familiar APIs (C.S. stuff just works)

Some Lessons Learned Curriculum mismatch between domain scientists and computer science courses Hard to determine the resource needs of an app a priori Cross-disciplinary work is challenging –More cross-disciplinary possibilities in sharing Big Data Typically not a big data cliff: can make do with less data, but improve with more data –Although some apps need min data size to be useful –Meet needs of those already feeling the pinch vs. Trying to leap ahead Economics: data is free, networking is free –Payment may not be money: what demand of users