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The growing onslaught of astronomical data available presents a great challenge. Astronomy lacks an easy-to-use and scalable way to collect and distribute expert information about objects from datasets of tens of thousands to billions of individual events and objects. Over the next decade, the amount of information available to the typical astronomer will grow by two orders of magnitude both in raw data size and in the number of objects.
This project pursues three research directions, each of which has the potential to transform how astronomers interface with large datasets: (1) a scalable annotation framework to enable linking of observations to specific experiments, models, or other observations; (2) a continuous workflow enactment system that would support automated reasoning in the presence of uncertainty; and (3) a computational framework for interactively analyzing astronomical datasets, allowing the construction and testing of hypotheses.
Project plans include the design and development of a prototype system (AstroShelf) and its evaluation using two timely science programs: (a) Using multi-wavelength data from the DEEP3 and AEGIS surveys, develop methods to incorporate images and catalogs from disparate datasets, allowing us to study how the demographics of galaxies have changed over the last 8 billion years. (b) Using properties of time-variable events found by the Pan-STARRS survey, develop techniques for rapid classification of transient phenomena, dissemination of their properties, and incorporation of feedback from follow-up observations. AstroShelf will include a publicly accessible, flexible annotation system for public datasets, which will also lend itself to outreach efforts involving annotations by the general public.
This projectâ€™s significant impact is the ability to share information and expert opinions quickly and widely, about each new observation or event, fundamentally changing our ability to learn about the Universe; such functionality can also be applied in support of other scientific domains.Top
NSF OIA-1028162 (PI: Alexandros Labrinidis; Co-PIs: Panos Chrysanthis, Jeffrey Newman, Georgeta Marai, William Wood-Vasey) NSF AbstractTop
- Pitt Chronicle (July 18, 2011)
- University Times (July 7, 2011)
- Pittsburgh Tribune-Review (July 2, 2011)
- Pitt News (June 28, 2011)
- Award page at NSF
- Advanced Data Management Technologies Lab
- Interdisciplinary Visualization Research Lab
[ 2015 | 2014 | 2012 | 2011 ]
- Roxana Gheorghiu, Alexandros Labrinidis, Panos K. Chrysanthis, Unifying Qualitative and Quantitative Database Preferences to Enhance Query Personalization, 2nd International Workshop on Exploratory Search in Databases and the Web (ExploreDB'15), 6-8, May 2015, Co-located with ACM SIGMOD 2015.
- Xiaoyu Ge, Panos K. Chrysanthis, Alexandros Labrinidis, Preferential Diversity, 2nd International Workshop on Exploratory Search in Databases and the Web (ExploreDB'15), 9-14, May 2015, Co-located with ACM SIGMOD 2015.
- Roxana Gheorghiu, Alexandros Labrinidis, Panos K. Chrysanthis, A user-friendly framework for database preferences, The 10th International Conference on Collaborative Computing (CollaborateCom'14), 1-10, Miami, Florida, USA, October 2014.
- Panayiotis Neophytou, Roxana Gheorghiu, Rebecca Hachey, Timothy Luciani, Di Bao, Alexandros Labrinidis, G. Elisabeta Marai, Panos K. Chrysanthis, AstroShelf: Understanding the Universe Through Scalable Navigation of a Galaxy of Annotations, Proc. of the 31st ACM International Conference on Management of Data (SIGMOD'12), pp. 1-4, Scottsdale, Arizona, May 2012.
- Panayiotis Neophytou, Panos K. Chrysanthis, Alexandros Labrinidis, CONFLuEnCE: Implementation and Application Design, Proc. of the 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'11), pp. 181-190, Orlando, Florida, October 2011.
- Panayiotis Neophytou, Panos K. Chrysanthis, Alexandros Labrinidis, CONFLuEnCE: CONtinuous workFLow ExeCution Engine, Proc. of the 30th ACM International Conference on Management of Data (SIGMOD'11), pp. 1311-1314, Athens, Greece, June 2011, DOI:10.1145/1989323.1989485.
[ 2016 | 2015 | 2014 | 2013 | 2012 | 2011 ]
- Humaira Ehsan, Mohamed A. Sharaf, Panos K. Chrysanthis, MuVE: Efficient Multi-Objective View Recommendation for Visual Data Exploration, 32nd IEEE International Conference on Data Engineering (ICDE'16), pp. 1-12, May 2016.
- Thao N. Pham, Panos K. Chrysanthis, Alexandros Labrinidis, Avoiding class warfare: Managing Continuous Queries with Differentiated Classes of Service, VLDB Journal (VLDB J. 2016), 25(2):197-221, April 2016, 11/12/2015 published on-line.
- Angen Zheng, Alexandros Labrinidis, Panos K. Chrysanthis, Planar: Parallel Lightweight Architecture-Aware Adaptive Graph Repartitioning, 32nd IEEE International Conference on Data Engineering (ICDE'16), pp. 1-12, January 2016.
- Angen Zheng, Alexandros Labrinidis, Patrick H. Pisciuneri, Panos K. Chrysanthis, Peyman Givi, PARAGON: Parallel Architecture-Aware Graph Partition Refinement Algorithm, 19th International Conference on Extending Database Technology (EDBT'16), pp. 1-12, January 2016.
- Patrick H. Pisciuneri, Angen Zheng, Peyman Givi, Alexandros Labrinidis, Panos K. Chrysanthis, Repartitioning Strategies for Massively Parallel Simulation of Reacting Flow, 68th Annual Meeting of the APS Division of Fluid Dynamics (APS'15), 60(21):503, November 2015.
- Andreas Konstantinidis, George Nikolaides, Georgios Chatzimilioudis, Giannis Evagorou, Demetrios Zeinalipour-Yazti, Panos K. Chrysanthis, Radiomap Prefetching for Indoor Navigation in Intermittently Connected Wi-Fi Networks, 16th IEEE International Conference on Mobile Data Management (MDM'15), Vol.1, pp. 34-43, June 2015.
- Nick R. Katsipoulakis, Cory Thoma, Eric A. Gratta, Alexandros Labrinidis, Adam J. Lee, Panos K. Chrysanthis, CE-Storm: Confidential Elastic Processing of Data Streams, Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data (SIGMOD'15), 859-864, May 2015.
- Nathan R. Ong, Stephen E. Rojcewicz, Nicholas L. Farnan, Adam J. Lee, Panos K. Chrysanthis, Ting Yu, Interactive Preference-aware Query Optimization, IEEE 31st International Conference on Data Engineering (ICDE'15), 1512-1515, Seoul, South Korea, April 2015.
- Angen Zheng, Alexandros Labrinidis, Panos K. Chrysanthis, Architecture-Aware Graph Repartitioning for Data-Intensive Scientific Computing, 1st International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphDM'14), 78-85, October 2014.
- Nicholas L. Farnan, Adam J. Lee, Panos K. Chrysanthis, Ting Yu, PAQO: Preference-Aware Query Optimization for Decentralized Database Systems, IEEE International Conference on Data Engineering (ICDE'14), 424-435, April 2014.
- Nicholas L. Farnan, Adam J. Lee, Panos K. Chrysanthis, Ting Yu, PAQO: A Preference-Aware Query Optimizer for PostgreSQL, International Conference on Very Large Databases (VLDB'13), 6(12): 1334-1337, August 2013.
- Panayiotis Neophytou, Panos K. Chrysanthis, Alexandros Labrinidis, A continuous workflow scheduling framework, Proceedings of the 2nd ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies (SWEET'13), 1-12, June 2013.
- Nicholas L. Farnan, Adam J. Lee, Panos K. Chrysanthis, Ting Yu, Enabling Intensional Access Control via Preference-aware Query Optimization, Symposium on Access Control Models and Technologies (SACMAT'13), 189-192, Amsterdam, The Netherlands, June 2013.
- Roxana Gheorghiu, Alexandros Labrinidis, Panos K. Chrysanthis, Database Preferences -A Unified Model, 6th International Workshop on Personalized Access, Profile Management, and Context Awareness in Databases (PersDB'12), 1-6, August 2012.
- Lory Al Moakar, Alexandros Labrinidis, Panos K. Chrysanthis, Adaptive Class-Based Scheduling of Continuous Queries, Proc. of the Seventh International Workshop on Self-Managing Database Systems (SMDB'12), pp. 1-6, April 2012.
- Marian K. Iskander, Dave W. Wilkinson, Adam J. Lee, Panos K. Chrysanthis, Enforcing Policy and Data Consistency of Cloud Transactions, Proc. of the 2nd ICDCS International Workshop on Security and Privacy on the Cloud (ICDCS-SPCC'11), pp. 253-262, Minneapolis, Minnesota, June 2011, DOI:10.1109/ICDCSW.2011.42.