|Awardee:||FLORIDA INTERNATIONAL UNIVERSITY|
|Doing Business As Name:||Florida International University|
|Estimated Total Award Amount:||$ 1,000,000|
|Funds Obligated to Date:||
|Awarding Agency Code:||4900|
|Funding Agency Code:||4900|
|Primary Program Source:||040100 NSF RESEARCH & RELATED ACTIVIT|
|Award Title or Description:||MRI: Development of a High-Performance Database Appliance for Geospatial Applications|
|Federal Award ID Number:||0821345|
|Parent DUNS ID:||159621697|
|Program:||MAJOR RESEARCH INSTRUMENTATION|
|Street:||11200 SW 8TH ST|
|Awardee Cong. District:||26|
Primary Place of Performance
|Organization Name:||Florida International University|
|Street:||11200 SW 8TH ST|
Abstract at Time of Award
Proposal #: CNS 08-21345 PI(s): Rishe, Naphtali D. Christidis, Evangelos; Li, Tao; Rangaswami, Raju Institution: Florida International University Miami, FL 33174-2516 Title: MRI/Dev.: Dev. Of a High Performance Database Appliance for Geospatial Applications Project Proposed: This project, developing a high-performance next-generation hardware/software instrument able to efficiently perform complex geospatial and other queries, enables close-to-storage complex operations related to geospatial data transformation and querying, including data search with information retrieval (keywords), structural (SQL), and geospatial criteria. This replicable instrument consists of a scalable storage and computation cloud comprising an array of processors, each equipped with solid-state disks (SSD) and mechanical disks. This coupling of processors to SSDs allows an order of magnitude in performance improvement for many geospatial problems. The work entails adapting existing spatial database management, querying, and interface systems to this new architecture and deploying open-standard APIs. The instrument will include a base-map comprising nationwide aerial photography, street vectors, demographics, and cadastre data. For completeness of the basemap, most of the data (40TB) already assembled, ameliorated, and mosaiced for the TerraFly project that will be ported into the instrument, requires expansion. The instrument facilitates several areas in computer science research, including query algorithms, storage systems, geographic information systems (GIS), and data mining, feature recognition, and visualization. Examples of enabled research on algorithms range from optimization of query filtering on keywords 'containment in the objects' description to enriching spatial query languages to incorporate IR constraints and creating complex personalized ranking functions that consider the shape, location, and textual description of objects. Many examples involve feature recognition, appropriately serving multiple computer science and disaster mitigation research areas. Moreover, the enablement of real-time multi-dimensional indexing, combined with the multitude of geospatial data, also facilitates applied research in disaster management (e.g., use of high-resolution hurricane impact models to predict the possibility of damage on a house-by-house basis). Broader Impacts: This project enables applications in environmental monitoring, transportation, education, public health, and safety. By providing efficient spatial and temporal management of data needed by many constituencies such as disaster management, the instrument broadly benefits society. Specifically, the instrument impacts computer science and disaster mitigation research nationwide. Once the instrument is successfully commercialized, it should also serve many critical government and business applications requiring high-performance querying of very large geospatial databases. Furthermore, many students in this Minority Serving University (MSI) are likely to be inspired to continue towards a graduate degree and/or benefit by continuing their careers in science and engineering.
Publications Produced as a Result of this Research
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
Zolotov, S; Ben Yosef, D; Rishe, ND; Yesha, Y; Karnieli, E "Metabolic profiling in personalized medicine: bridging the gap between knowledge and clinical practice in Type 2 diabetes" PERSONALIZED MEDICINE, v.8, 2011, p.445. doi:10.2217/PME.11.3 View record at Web of Science
Harry S Glauber, Naphtali Rishe, Eddy Karnieli "Introduction to Personalized Medicine in Diabetes Mellitus" Rambam Maimonides Medical Journal, v.5, 2014, p.1.
Aniket Bochare, Aryya Gangopadhyay, Yelena Yesha, Anupam Joshi, Yaacov Yesha, Michael A. Grasso, Mary Brady, Naphtali Rishe "Integrating Domain Knowledge in Supervised Machine Learning to Assess the Risk of Breast Cancer" International Journal of Medical Engineering and Informatics, v.6, 2014, p.87.
Jaime Ballesteros, Bogdan Carbunar, Mahmudur Rahman, Naphtali Rishe, Sundararaj S. Iyengar "Towards Safe Cities: A Mobile and Social Networking Approach" Online Extended Edition of IEEE Transactions on Parallel and Distributed Systems, v., 2013, p..
Jaime Ballesteros, Bogdan Carbunar, Mahmudur Rahman, Naphtali Rishe, Sundararaj S. Iyengar "Towards Safe Cities: A Mobile and Social Networking Approach" IEEE Transactions on Parallel and Distributed Systems, v.25, 2014, p.2451. doi:10.1109/TPDS.2013.190
Mingjin Zhang, Huibo Wang, Yun Lu, Tao Li, Yudong Guang, Chang Liu, Erik Edrosa, Hongtai Li, Naphtali Rishe "TerraFly GeoCloud: An Online Spatial Data Analysis and Visualization System" ACM Transactions on Intelligent Systems and Technology, v.6, 2015, p..
Yun Lu, Ming Zhao, Lixi Wang, Naphtali Rishe "v-TerraFly: Large Scale Distributed Spatial Data Visualization with Autonomic Resource Management" Springer Journal Of Big Data, v., 2014, p..
Publications Produced as Conference Proceedings
Cary, A;Sun, ZG;Hristidis, V;Rishe, N "Experiences on Processing Spatial Data with MapReduce" 21st International Conference on Scientific and Statistical Database Management, v.5566, 2009, p.302 View record at Web of Science
Cary, A;Wolfson, O;Rishe, N "Efficient and Scalable Method for Processing Top-k Spatial Boolean Queries" 22nd International Conference on Scientific and Statistical Database Management, v.6187, 2010, p.87 View record at Web of Science
Project Outcomes Report
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The High Performance Database Research Center (http://HPDRC.fiu.edu/) and the TerraFly Geospatial Data Service (http://TerraFly.fiu.edu) at Florida International University (FIU) have developed a high-performance hardware/software system able to perform close-to-storage complex operations related to geospatial data transformation and querying, including data search with Information-Retrieval (keywords), Structural (SQL), and geospatial criteria. This system was built as a scalable storage and computation cloud comprised of an array of processors, equipped with solid-state (SSD) and mechanical disks, and a large amount of geospatial data (areal, satellite, and vector). This coupling of processors to SSDs allows significant performance improvement for many geospatial problems. FIU's development effort involved adapting existing spatial database management, querying, and interface systems to this new architecture and deploying open-standard APIs. The Instrument mosaics a base-map comprised of nationwide aerial photography and satellite imagery, street vectors, demographics, and cadastre data. The system includes precise geocoding and the boundary polygons of over 100 million parcels, representing most of the U.S. properties.
The Instrument facilitates several areas of Computer Science research, including query algorithms, storage systems, GIS, data mining, feature recognition, and visualization. The enablement of real-time multi-dimensional indexing combined with the multitude of geospatial data also facilitates applied research in disaster management, e.g. using high-resolution hurricane impact models to predict the possibility of damage on a house-by-house basis.
The instrument is a high-performance database appliance uniquely suited to efficiently perform complex geospatial and other queries. The cutting edge technological solutions developed for the instrument leveraged TerraFly geospatial technologies (http://TerraFly.com). TerraFly is a technology for visualization and querying of geospatial data that provides users with the experience of virtual "flight" over maps comprised of aerial and satellite imagery overlaid with geo-referenced data. Capabilities include user-friendly geospatial querying, data drill-down, interfaces with real-time data suppliers, demographic analysis, annotation, route dissemination via autopilots, customizable applications, production of aerial atlases, and an application programming interface (API) that allows rapid deployment of interactive Web applications to produce systems for disaster mitigation, ecology, real estate, tourism, and municipalities.
The development of the instrument has brought about significant technological advances in data querying, processing and integration technologies. One such project involved the merging of the FIU-Miner framework with TerraFly GeoCloud, to optimize the execution of the spatial data analysis tasks by maximizing the parallelization of sub-tasks in the corresponding workflow. Another project involved the development of new interface technologies for human-computer interactions, including work on Touch-midAir-Motion Gesture Framework (http://CAKE.fiu.edu/MultiTouch) that led to the publication of a book and multiple papers.
Other examples of enabled research include development and open sourcing of TerraFly sksOpen and SpsJoin. TerraFly sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. It allows online users to index their own spatial data, and offer query visualization with improved performance and scalability on large spatial datasets.
SpsJoin (Spatial Set-Similarity Join) is a platform that merges geospatial and text processing techniques for efficiently pe...
For specific questions or comments about this information including the NSF Project Outcomes Report, contact us.