US20130066920A1 - Relational Database Model Optimized for the Use and Maintenance of Watchlist Data in a High Demand Environment - Google Patents
Relational Database Model Optimized for the Use and Maintenance of Watchlist Data in a High Demand Environment Download PDFInfo
- Publication number
- US20130066920A1 US20130066920A1 US13/232,412 US201113232412A US2013066920A1 US 20130066920 A1 US20130066920 A1 US 20130066920A1 US 201113232412 A US201113232412 A US 201113232412A US 2013066920 A1 US2013066920 A1 US 2013066920A1
- Authority
- US
- United States
- Prior art keywords
- watchlist
- information
- tables
- entry table
- agency
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000012423 maintenance Methods 0.000 title 1
- 238000000034 method Methods 0.000 claims description 15
- 238000007726 management method Methods 0.000 claims description 6
- 230000037308 hair color Effects 0.000 claims description 4
- 230000002123 temporal effect Effects 0.000 claims description 4
- 238000013500 data storage Methods 0.000 claims 2
- 238000012545 processing Methods 0.000 description 12
- 230000008901 benefit Effects 0.000 description 5
- 230000004075 alteration Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
- 230000010006 flight Effects 0.000 description 1
- 239000004081 narcotic agent Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012502 risk assessment Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
Definitions
- This disclosure relates to a system and method for accessing and managing data related to a plurality of watchlists. More specifically, this disclosure relates to a method and system for accessing and managing data related to a plurality of traveler watchlists utilizing a watchlist table, a watchlist entry table for storing high-level information, and a plurality of detail tables associated with the watchlist entry table for storing detailed information.
- a system for accessing and storing traveler-related watchlist information is disclosed.
- a means for storing data related to one or more watchlists in a relational database management system (“RDBMS”) is disclosed.
- RDBMS relational database management system
- a normalized layout of the tables of the database allows the RDBMS to satisfy queries in a performance-optimized manner, while the minimal number of required attributes allows for the greatest degree of flexibility in its use.
- Query information may be especially fast when the model is deployed in an enterprise class RDBMS incorporating such features as index-organized tables and partitioning.
- An advantage of one embodiment of the disclosure may be improved performance in using and maintaining watchlist related data.
- Another advantage of one embodiment of the disclosure may be separating detailed watchlist information from high level watchlist information.
- FIG. 1 depicts a model of the system in accordance with the present disclosure.
- the disclosed system relates to a system 10 and method for accessing and managing data related to a plurality of watchlists in a relational database system in a high demand environment.
- the system 10 comprises a watchlist table 12 , a plurality of agency tables 14 , a watchlist entry table 16 , and plurality of detail tables 18 .
- a hub-and-spoke architecture may be utilized wherein the watchlist entry table 16 serves as the hub with the plurality of detail tables 18 serving as the spokes.
- the watchlist table 12 is preferably configured to capture or store metadata about the data stored throughout the system 10 .
- This metadata may include (for example only) information about when the particular watchlist entry was created, loaded, or received from the respective agency.
- the metadata may also include temporal information wherein the temporal information may define an effective start and stop time for the particular watchlist.
- the watchlist table 12 may also be associated with a plurality of agency tables 14 .
- the agency tables 14 may realize the many-to-many relationship between agencies that produce or maintain watchlists (i.e. FBI, CIA, law enforcement, etc.) and the various watchlists that may be maintained within the system 10 .
- the watchlist entry table 16 may be a key component of the present disclosure. This main table may serve as the primary repository for high-level information related to watchlists. High-level information may include the minimal set of watchlist attributes which have been determined to increase system performance. For instance, attributes that are regularly searched in order to identify possible watchlist violations would appropriately be stored in the watchlist entry table 16 , while the detailed information about the particular attributes would more preferably be stored in the detail tables 18 .
- the watchlist entry table 16 attributes are defined by the particular business requirements of the system 10 .
- the watchlist entry table 16 attributes may include name, ethnic code, gender, date of birth, place of birth, height, hair color, eye color, and family information (such as the number of children cohabitating with the individual).
- fast searches can still be performed to gather individuals that satisfy particular criteria maintained in the watchlist entry table 16 . (I.e., the system 10 may quickly search for all individuals born in a certain city between a particular time.) Because each of these key attributes is stored in a single table, performance may be improved because the RDBMS is not called upon to perform joins across numerous related tables.
- the list of key attributes stored in the watchlist entry table 16 may change based upon the particular business requirements.
- demographic information is a key searching component, and thus demographic information is properly stored in the watchlist entry table 16 .
- the watchlist entry table 16 is thus designed to store the attributes that are used for regular and fast searching of the entire data set stored in the system 10 .
- the detail tables 18 preferably contain the detailed information about the respective high level information contained in the watchlist entry table 16 . Once a search has been performed using the watchlist entry table 16 , detailed information about the respective watchlist information may then be retrieved from the detail tables 18 .
- the computationally expensive step of searching across all individuals for particular criteria is optimized by segregating pre-selected criteria into a watchlist entry table 16 and searching across that table. Once the individuals of interest are returned, detailed information about them can be retrieved from the detail tables 18 .
- the watchlist table 12 , agency tables 14 , watchlist entry table 16 , and detail tables 18 may be centrally located in a single location or remotely located from one another. Additionally, the watchlist table 12 may be a single database table, or may be a combination of tables logically presented to appear as a single table.
- Appendix A is a data model dictionary for one embodiment of the present disclosure for use in the immigration control and identity management space. The contents of Exhibit A is herein incorporated by reference.
- the system 10 may preferably be implemented in a computing system, which can include a personal computer, a workstation, a network computer, a hand held computer, or any other computing system. Further, the system can be written as a software program in any appropriate computer language.
- the system 10 may include a processing device, which can be any computer processing unit, and could be a single central processing unit, or a number of processing units configured to operate either in sequence or in parallel.
- the processing device can be configured to execute software processes which implement the steps disclosed herein.
- the system may also include a memory capable of storing the steps necessary for a processing device to implement the steps disclosed herein. This memory could be in the form of memory resident within the processing device or in the form of standalone memory coupled to the processing unit via a communication path, such as a bus or a network.
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Description
- This disclosure relates to a system and method for accessing and managing data related to a plurality of watchlists. More specifically, this disclosure relates to a method and system for accessing and managing data related to a plurality of traveler watchlists utilizing a watchlist table, a watchlist entry table for storing high-level information, and a plurality of detail tables associated with the watchlist entry table for storing detailed information.
- Processing international travelers for immigration and other purposes is a complex risk management function. The vast majority of international travelers are law-abiding citizens, however some travelers present risks for security, illegal immigration, narcotics smuggling, and customs revenue evasion (to name a few). Given the volume of travelers, the finite availability of control authority resources, and the constraints on time available for passenger processing, border agencies face significant challenges in identifying potentially risky travelers without delaying legitimate travel and trade
- The collection of pre-departure electronic data on travelers is emerging as the foundation of modern immigration control and border management. This approach is beneficial because electronic travel records can facilitate the implementation of a variety of automated functions, including watchlist checks and risk analysis, before passengers arrive. The analysis and presentation of this data also enables frontline immigration officers to be more effective during primary and secondary inspections. The combination of identifying risks earlier in the travel cycle and performing more effective primary inspections improves the processing time for arriving flights and facilitates international travel
- Hence, there exists a need in the industry to overcome these problems and provide a method and system for accessing and processing data related to watchlists. Additionally, there exists a need in the industry to allow skilled border protection resources to focus on better assessing travelers rather than on paperwork requirements.
- According to one embodiment of the present disclosure, a system for accessing and storing traveler-related watchlist information is disclosed. In one aspect, a means for storing data related to one or more watchlists in a relational database management system (“RDBMS”) is disclosed. In another aspect, a normalized layout of the tables of the database allows the RDBMS to satisfy queries in a performance-optimized manner, while the minimal number of required attributes allows for the greatest degree of flexibility in its use. Query information may be especially fast when the model is deployed in an enterprise class RDBMS incorporating such features as index-organized tables and partitioning.
- An advantage of one embodiment of the disclosure may be improved performance in using and maintaining watchlist related data.
- Another advantage of one embodiment of the disclosure may be separating detailed watchlist information from high level watchlist information.
- Various embodiments of the disclosure may have none, some, or all of these advantages. Other technical advantages of the present disclosure may also be readily apparent to one skilled in the art.
- For a more complete understanding of the present disclosure and its advantages, reference is now made to the following descriptions, taken in conjunction with the associated drawing, in which:
-
FIG. 1 depicts a model of the system in accordance with the present disclosure. - The disclosed system relates to a
system 10 and method for accessing and managing data related to a plurality of watchlists in a relational database system in a high demand environment. In a preferred embodiment, thesystem 10 comprises a watchlist table 12, a plurality of agency tables 14, a watchlist entry table 16, and plurality of detail tables 18. In a preferred configuration, a hub-and-spoke architecture may be utilized wherein the watchlist entry table 16 serves as the hub with the plurality of detail tables 18 serving as the spokes. - The watchlist table 12 is preferably configured to capture or store metadata about the data stored throughout the
system 10. This metadata may include (for example only) information about when the particular watchlist entry was created, loaded, or received from the respective agency. The metadata may also include temporal information wherein the temporal information may define an effective start and stop time for the particular watchlist. - The watchlist table 12 may also be associated with a plurality of agency tables 14. The agency tables 14 may realize the many-to-many relationship between agencies that produce or maintain watchlists (i.e. FBI, CIA, law enforcement, etc.) and the various watchlists that may be maintained within the
system 10. - The watchlist entry table 16 may be a key component of the present disclosure. This main table may serve as the primary repository for high-level information related to watchlists. High-level information may include the minimal set of watchlist attributes which have been determined to increase system performance. For instance, attributes that are regularly searched in order to identify possible watchlist violations would appropriately be stored in the watchlist entry table 16, while the detailed information about the particular attributes would more preferably be stored in the detail tables 18.
- In one preferred embodiment, the watchlist entry table 16 attributes are defined by the particular business requirements of the
system 10. For example, in a security monitoring situation designed to assist in travel restriction databases (such as management and monitoring of a no-fly list), the watchlist entry table 16 attributes may include name, ethnic code, gender, date of birth, place of birth, height, hair color, eye color, and family information (such as the number of children cohabitating with the individual). - Thus, when the
system 10 is fully populated, fast searches can still be performed to gather individuals that satisfy particular criteria maintained in the watchlist entry table 16. (I.e., thesystem 10 may quickly search for all individuals born in a certain city between a particular time.) Because each of these key attributes is stored in a single table, performance may be improved because the RDBMS is not called upon to perform joins across numerous related tables. - As would be understood to one of skill in the art, the list of key attributes stored in the watchlist entry table 16 may change based upon the particular business requirements. Thus, in the example discussed above, demographic information is a key searching component, and thus demographic information is properly stored in the watchlist entry table 16.
- The watchlist entry table 16 is thus designed to store the attributes that are used for regular and fast searching of the entire data set stored in the
system 10. The detail tables 18 preferably contain the detailed information about the respective high level information contained in the watchlist entry table 16. Once a search has been performed using the watchlist entry table 16, detailed information about the respective watchlist information may then be retrieved from the detail tables 18. Thus, the computationally expensive step of searching across all individuals for particular criteria is optimized by segregating pre-selected criteria into a watchlist entry table 16 and searching across that table. Once the individuals of interest are returned, detailed information about them can be retrieved from the detail tables 18. - The watchlist table 12, agency tables 14, watchlist entry table 16, and detail tables 18 may be centrally located in a single location or remotely located from one another. Additionally, the watchlist table 12 may be a single database table, or may be a combination of tables logically presented to appear as a single table.
- Appendix A is a data model dictionary for one embodiment of the present disclosure for use in the immigration control and identity management space. The contents of Exhibit A is herein incorporated by reference.
- The
system 10 may preferably be implemented in a computing system, which can include a personal computer, a workstation, a network computer, a hand held computer, or any other computing system. Further, the system can be written as a software program in any appropriate computer language. - The
system 10 may include a processing device, which can be any computer processing unit, and could be a single central processing unit, or a number of processing units configured to operate either in sequence or in parallel. The processing device can be configured to execute software processes which implement the steps disclosed herein. The system may also include a memory capable of storing the steps necessary for a processing device to implement the steps disclosed herein. This memory could be in the form of memory resident within the processing device or in the form of standalone memory coupled to the processing unit via a communication path, such as a bus or a network. - Although this disclosure has been described in terms of certain embodiments and generally associated methods, alterations and permutations of these embodiments and methods will be apparent to those skilled in the art. Accordingly, the above description of example embodiments does not define or constrain this disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of this disclosure.
Claims (20)
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/232,412 US8412745B1 (en) | 2011-09-14 | 2011-09-14 | Relational database model optimized for the use and maintenance of watchlist data in a high demand environment |
EP12779187.9A EP2795479A4 (en) | 2011-09-14 | 2012-09-14 | A relational database model optimized for the use and maintenance of watchlist data in a high demand environment |
PCT/US2012/055468 WO2013040382A2 (en) | 2011-09-14 | 2012-09-14 | A relational database model optimized for the use and maintenance of watchlist data in a high demand environment |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/232,412 US8412745B1 (en) | 2011-09-14 | 2011-09-14 | Relational database model optimized for the use and maintenance of watchlist data in a high demand environment |
Publications (2)
Publication Number | Publication Date |
---|---|
US20130066920A1 true US20130066920A1 (en) | 2013-03-14 |
US8412745B1 US8412745B1 (en) | 2013-04-02 |
Family
ID=47089118
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/232,412 Active US8412745B1 (en) | 2011-09-14 | 2011-09-14 | Relational database model optimized for the use and maintenance of watchlist data in a high demand environment |
Country Status (3)
Country | Link |
---|---|
US (1) | US8412745B1 (en) |
EP (1) | EP2795479A4 (en) |
WO (1) | WO2013040382A2 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160155053A1 (en) * | 2013-03-15 | 2016-06-02 | International Business Machines Corporation | Interactive method to reduce the amount of tradeoff information required from decision makers in multi-attribute decision making under uncertainty |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7080062B1 (en) * | 1999-05-18 | 2006-07-18 | International Business Machines Corporation | Optimizing database queries using query execution plans derived from automatic summary table determining cost based queries |
US6567807B1 (en) * | 2000-01-28 | 2003-05-20 | Ccbn.Com, Inc. | Investor relations event scheduling system and method |
US7028018B2 (en) * | 2002-05-14 | 2006-04-11 | Ideal Innovations, Inc. | Cooperative biometrics abnormality detection system (C-BAD) |
AU2003298731A1 (en) * | 2002-11-26 | 2004-06-18 | Digimarc Id Systems | Systems and methods for managing and detecting fraud in image databases used with identification documents |
US7945035B2 (en) * | 2003-02-28 | 2011-05-17 | Siemens Enterprise Communications, Inc. | Dynamic presence proxy for call sessions |
WO2006031302A2 (en) * | 2004-07-29 | 2006-03-23 | Intelli7, Inc. | System and method of characterizing and managing electronic traffic |
US7822775B2 (en) * | 2007-07-20 | 2010-10-26 | Sap Ag | Method and system for managing complex database information |
WO2009105107A1 (en) * | 2008-02-21 | 2009-08-27 | Oberon Associates, Inc. | Systems and methods for secure watchlisting |
US7937385B2 (en) * | 2008-05-05 | 2011-05-03 | International Business Machines Corporation | Obtaining a plan for executing a query in a relational database |
US8239526B2 (en) * | 2008-11-14 | 2012-08-07 | Oracle International Corporation | System and method for performance data collection in a virtual environment |
-
2011
- 2011-09-14 US US13/232,412 patent/US8412745B1/en active Active
-
2012
- 2012-09-14 EP EP12779187.9A patent/EP2795479A4/en not_active Ceased
- 2012-09-14 WO PCT/US2012/055468 patent/WO2013040382A2/en unknown
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20160155053A1 (en) * | 2013-03-15 | 2016-06-02 | International Business Machines Corporation | Interactive method to reduce the amount of tradeoff information required from decision makers in multi-attribute decision making under uncertainty |
US10366331B2 (en) * | 2013-03-15 | 2019-07-30 | International Business Machines Corporation | Interactive method to reduce the amount of tradeoff information required from decision makers in multi-attribute decision making under uncertainty |
Also Published As
Publication number | Publication date |
---|---|
US8412745B1 (en) | 2013-04-02 |
EP2795479A2 (en) | 2014-10-29 |
WO2013040382A3 (en) | 2015-01-08 |
EP2795479A4 (en) | 2019-01-16 |
WO2013040382A2 (en) | 2013-03-21 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US11531717B2 (en) | Discovery of linkage points between data sources | |
US9224007B2 (en) | Search engine with privacy protection | |
US8972387B2 (en) | Smarter search | |
US8296309B2 (en) | System and method for high precision and high recall relevancy searching | |
US20120330959A1 (en) | Method and Apparatus for Assessing a Person's Security Risk | |
US9779172B2 (en) | Personalized search result summary | |
US20220100899A1 (en) | Protecting sensitive data in documents | |
US20140188993A1 (en) | Method and apparatus for analysis of social media | |
US9959326B2 (en) | Annotating schema elements based on associating data instances with knowledge base entities | |
US20180129708A1 (en) | Query processing management in a database management system | |
CN109597843A (en) | Data managing method, device, storage medium and the electronic equipment of big data environment | |
US10915535B2 (en) | Optimizations for a behavior analysis engine | |
CN111913860B (en) | Operation behavior analysis method and device | |
US20110225138A1 (en) | Apparatus for responding to a suspicious activity | |
CN109416684A (en) | The intake manager of analysis platform | |
US20160196310A1 (en) | Cross column searching a relational database table | |
CN106682042A (en) | Relational data cache and inquiry method and device | |
EP3493076B1 (en) | Cognitive decision system for security and log analysis using associative memory mapping in graph database | |
CN113971207A (en) | Document association method and device, electronic equipment and storage medium | |
US8412745B1 (en) | Relational database model optimized for the use and maintenance of watchlist data in a high demand environment | |
CN114003634A (en) | Big data analysis and retrieval system and method based on ES technology | |
CN116894022A (en) | Improving accuracy and efficiency of database auditing using structured audit logs | |
US20160196331A1 (en) | Reconstitution order of entity evaluations | |
Sagi et al. | Multi-source uncertain entity resolution at yad vashem: Transforming holocaust victim reports into people | |
US10262042B2 (en) | System and method for determining that two data records relate to the same subject |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: RAYTHEON COMPANY, MASSACHUSETTS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:WALASCHEK, BRYAN J.;REEL/FRAME:026934/0452 Effective date: 20110913 |
|
FEPP | Fee payment procedure |
Free format text: PAYOR NUMBER ASSIGNED (ORIGINAL EVENT CODE: ASPN); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY Year of fee payment: 8 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 12TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1553); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY Year of fee payment: 12 |