| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | August 29, 2014 |
| Latest Amendment Date: | July 21, 2015 |
| Award Number: | 1420941 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Maria Zemankova
IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2014 |
| End Date: | August 31, 2018 (Estimated) |
| Total Intended Award Amount: | $248,603.00 |
| Total Awarded Amount to Date: | $248,603.00 |
| Funds Obligated to Date: |
FY 2015 = $84,565.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
70 WASHINGTON SQ S NEW YORK NY US 10012-1019 (212)998-2121 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
P.O. Box 129188 Abu Dhabi AE |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Info Integration & Informatics |
| Primary Program Source: |
01001516DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
More data is available today than ever before, and this availability has enabled groundbreaking new applications and societal advances. However, today's computing technology that stores, organizes, and searches data is struggling to keep up to the demands imposed by the data's growth and by the requirements of new applications. Data management systems need to adapt to support the evolving information needs of modern applications. This project will extend data management technology to support constrained search for collections of data items that satisfy complex requirements. The need for this functionality arises in many domains: Online marketplaces group products into meaningful collections based on customer preferences, travel agents organize vacation packages that coordinate travel and hotel reservations, and dietitians design meal plans that satisfy complex nutritional needs. Currently, such applications have to resort to ad hoc solutions that lead to suboptimal results and poor performance.
This project will establish the theoretical foundations and will address practical aspects of providing support for packages. A package is a group of data items that collectively satisfy a set of constraints. This project will extend data management technology to provide full-fledged support for packages, and will make contributions on three fronts: (1) a declarative language to support querying for packages, (2) evaluation strategies to efficiently compute answers to package queries, and (3) interaction techniques for package specification. The broader impact of this work will be the advancement of data management technology to handle emerging application needs, which in turn will increase the positive impact that data and computing systems have on society.
For further information see the project web site at: http://packagebuilder.cs.umass.edu
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
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.
Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. This project has introduced a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. The contributions include an end-to-end system to support package queries, a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets, allowing the declarative specification and efficient evaluation of a significant class of constrained optimization problems—integer linear programs—within a database.
Intellectual Merit: The project introduced a new data processing paradigm, package queries, which captures a variety of practical, real-world problems that require groups of data items to satisfy constraints collectively. Package queries are defined over traditional relations, but return packages or sets of tuples instead of tuples. This project developed language extensions to traditional database queries, to allow for the declarative specification of package constraints, and produced a method for automatically translating the declarative specification of a package query into a mathematical formulation that can be evaluated by existing constrained optimization tools. Moreover, the project developed scalable package evaluation algorithms with approximation guarantees, and parallelization techniques. This project has moved constrained optimization analysis closer to the data, eliminating the complexity of data extraction and transformation, development of custom, error-prone, and non-generalizable solutions, and loading of results into the database.
Broader Impacts: This project is a significant contribution to the topic of in-database analytics, simplifying workflows and facilitating domain experts’ access to specialized problem-solving capabilities. These advances remove data use barriers for significant groups of data users. The project fostered a new collaboration between two junior PIs, and formed the bulk of the dissertation work of one PhD student and supported several other PhD students, from groups traditionally under-represented in computer science. The project also involved several undergraduate students in research. Results from this project have been published in premier data management venues and have been recognized with several awards, including an ACM SIGMOD Research Highlight Award, a best of VLDB citation, a CHI best paper award and a Communications of the ACM Research Highlight.
Last Modified: 11/30/2018
Modified by: Azza Abouzied
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