1. A method comprising:
storing at least one of an image data or image information products in a database;
providing a search engine for searching the stored image data products;
if a desired image data or image information product of a requestor exists in the database, automatically generating a data product based on the desired image data product and a predefined attributes of the image specified by a requestor;
if a desired image data or image information product of a requestor does not exist in the database, automatically analyzing the desired image data or image information product and developing an image data or image information product based on the analysis and a predefined attributes of the image specified by a requester; and
automatically sending the generated or developed image data or image information product to the requester;
2. The method of claim 1, wherein generating the image data or image information product includes:
instructing one or more of a plurality of remote sensing data sources to generate one or more images based on the desired image data or image information product and the predefined attributes of the image specified by a requester;
receiving the generated one or more images at a data management facility; and
generating the desired image data or image information product based on an imaging algorithm associated with the desired image data or image information product and stored in an algorithm database.
3. The method of claim 2, wherein developing the image data or image information product includes:
instructing one or more of the plurality of remote sensing data sources to generate one or more images based on the analysis and the predefined attributes of the image specified by a requester;
receiving the generated one or more images at a data management facility;
generating at least one of an imaging or information extraction algorithm based on the analysis; and
generating the desired image data or image information product based on the generated imaging algorithm and the received one or more images.
4. The method of claim 3, further comprising:
when an algorithm is used to generate an image data or image information product, automatically reimbursing an owner of the algorithm that was used based on a reimbursement contract.
5. The method of claim 1, wherein sending includes at least one of electronically sending the image data or image information product to the requestor over a network, printing a hard copy and transporting the hard copy to the requester, and storing on a portable memory device and transporting the portable memory device to the requestor.
6. The method of claim 1, wherein the plurality of remote sensing data sources includes one or more of a LandSat5 system, a LandSat7 system, a MODIS system, aircraft system, ground based system, or a SPOT system.
7. A system comprising:
means for storing image data or image information products in a database;
means for providing a search engine for searching the stored image data or image information products;
means for automatically generating a image data or image information product based on the desired image data or image information product and a predefined attributes of the image specified by a requester, if a desired image data or image information product of a requestor exists in the database;
means for automatically analyzing the desired image data or image information product and developing an image data or image information product based on the analysis and a predefined attributes of the image specified by a requestor, if a desired image data or image information product of a requestor does not exist in the database;
means for sending the generated or developed image data or image information product to the requestor; an
8. The system of claim 7, wherein the means for generating the image data or image information product includes:
means for instructing one or more of a plurality of remote sensing data sources to generate one or more images based on the desired image data or image information product and the predefined attributes of the image specified by a requestor;
means for receiving the generated one or more images at a data management facility; and
means for generating the desired image data or image information product based on an imaging algorithm associated with the desired image data or image information product and stored in an algorithm database.
9. The system of claim 8, wherein the means for developing the image data or image information product includes:
means for instructing one or more of the plurality of remote sensing data sources to generate one or more images based on the analysis and the predefined attributes of the image specified by a requestor;
means for receiving the generated one or more images at a data management facility;
means for generating at least one of an imaging or information extraction algorithm based on the analysis; and
means for generating the desired image data or image information product based on the generated imaging or information extracting algorithm and the received one or more images.
10. The system of claim 9, further comprising:
means for reimbursing an owner of the algorithm that was used based on a reimbursement contract.
11. The system of claim 7, wherein the means for sending performs at least one of electronically sending the image data or image information product to the requestor over a network automatically, printing a hard copy and transporting the hard copy to the requester, and automatically storing on a portable memory device and transporting the portable memory device to the requestor.
12. The system of claim 7, wherein the plurality of remote sensing data sources includes one or more of a LandSat5 system, a LandSat7 system, a MODIS system, aircraft system, ground based system, or a SPOT system.
13. A system comprising:
a first database for storing at least one of an image data or image information products;
a second database for storing at least one of an image data or image information product algorithms; and
a processor coupled to the first and second databases and a network, the processor being configured to generate a graphical user interface,
wherein the graphical user interface includes:
a first component for allowing a requestor to search at least one of the stored image data or image information products or algorithms;
a second component for selecting at least one of the stored image data or image information products or algorithms;
a third component for selecting a predefined attributes of the image specified by a requestor;
the processor including:
a fourth component for generating an image data or image information product based on the selected image data or image information product and the selected geographic location;
a fifth component for receiving a request for an image data or image information product, if a desired image data or image information product can not be found in the first database; and
a sixth component for sending the generated image data or image information product to the requester;
14. The system of claim 13, wherein the fourth component includes:
an eighth component for instructing one or more of a plurality of remote sensing data sources to generate one or more images based on the selected image data or image information product and the selected geographic location;
a ninth component for receiving the generated one or more images; and
a tenth component for generating the desired image data or image information product based on at least one of an imaging or information extraction algorithm associated with the selected image data or image information product and stored in the second database.
15. The system of claim 14, wherein the processor further includes:
an eleventh component for reimbursing an owner of the algorithm that was used to generate the selected image data or image information product based on a reimbursement contract.
16. The system of claim 13, wherein the sixth component performs at least one of electronically sending the image data or image information product to the requestor over the network, printing a hard copy, and storing on a portable memory device.
17. The system of claim 13, wherein the plurality of remote sensing data sources includes one or more of a LandSat5 system, a LandSat7 system, a MODIS system, aircraft system, ground based system, or a SPOT system.
18. A system comprising:
a delivery unit;
a network;
a data management facility including:
a first database for storing image data or image information products;
a second database for storing image data or image information product algorithms; and
a processor coupled to the first and second databases and the network, the processor being configured to generate a graphical user interface,
wherein the graphical user interface includes:
a first component for allowing a requestor to search at least one of the stored image data or image information products or algorithms;
a second component for selecting at least one of the stored image data or image information products or algorithms;
a third component for selecting a predefined attributes of the image specified by a requestor;
the processor including:
a fourth component for generating an image data or image information product based on the selected image data or image information product and the selected geographic location;
a fifth component for receiving a request for an image data or image information product, if a desired image data or image information product can not be found in the first database; and
a sixth component for sending the generated image data or image information product to the requester;
19. The system of claim 18, wherein the fourth component includes:
an eighth component for instructing one or more of a plurality of remote sensing data sources to generate one or more images based on the selected image data or image information product and the selected geographic location;
a ninth component for receiving the generated one or more images; and
a tenth component for generating the desired image data or image information product based on at least one of an imaging or information extraction algorithm associated with the selected image data or image information product and stored in the second database.
20. The system of claim 19, wherein the processor further includes:
an eleventh component for reimbursing an owner of the algorithm that was used to generate the selected image data or image information product based on a reimbursement contract.
21. The system of claim 18, wherein the sixth component performs at least one of electronically sending the image data or image information product to the requestor over the network, printing a hard copy, and storing on a portable memory device.
22. The system of claim 21, wherein the sixth component further performs sending a request to the delivery unit to transport the hard copy or portable memory device to the requestor.
23. The system of claim 18, wherein the plurality of remote sensing data sources includes one or more of a LandSat5 system, a LandSat7 system, a MODIS system, aircraft system, ground based system, or a SPOT system.
24. A method comprising:
storing image data or image information products in a database;
providing a search engine for searching the stored image data or image information products;
receiving payment information from a requestor;
if a desired image data or image information product of a requestor exists in the database, automatically generating an image data or image information product based on the desired image data or image information product and a predefined attributes of the image specified by the requestor;
if a desired image data or image information product of a requestor does not exist in the database, automatically analyzing the desired image data or image information product and developing an image data or image information product based on the analysis and a predefined attributes of the image specified by the requester;
automatically sending the generated or developed image data or image information product to the requestor; and
automatically billing the requestor based on the generated or developed image data or image information product and the received payment information.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of determining variance in heterogeneous data, the heterogeneous data including a time dimension and a magnitude dimension, the method comprising:
storing an electronically accessible database of the heterogeneous data in a system, the system including at least one computing device with a processor and memory, the memory storing executable instructions that are executable by the processor;
determining the magnitude dimension that is associated with the time dimension having distinguishing extreme magnitudes of the heterogeneous data in the electronically accessible database, the distinguishing extreme magnitudes being stored in the memory of the system;
generating a weight of the heterogeneous data of the time dimension having the distinguishing extreme magnitudes in the memory of the system more than the heterogeneous data outside of the time dimension distinguishing extreme magnitudes of the heterogeneous data in the memory of the system; and
generating an estimated risk of the heterogeneous data in the electronically accessible database in the system in reference to the weight in the memory of the system.
2. The method of claim 1, wherein the magnitude dimension further comprises:
a performance parameter comprising at least one of corporate financial data and stock performance metrics.
3. The method of claim 1, wherein the determining the magnitude dimension that is associated with the time dimension having distinguishing extreme magnitudes further comprises:
identifying data of the heterogeneous data having the magnitude dimension that is greater than a predetermined cutoff value.
4. The method of claim 3, wherein the predetermined cutoff value further comprises:
2 standard deviations of the heterogeneous data of the electronically accessible database of the system.
5. The method of claim 1, wherein generating the weight further comprises:
generating a first divider comprising a reverse divider of a 1 year average priceearnings ratio in a historical sample of average priceearnings ratio;
generating a second divider comprising a divider of a 1 year average junk spread;
generating a third divider comprising a reverse divider of 180-day change in average 1-year junk spreads, at the time at which the priceearnings ratio of the heterogeneous data is observed;
summing the first divider, the second divider and twice the third divider;
dividing the sum by 20, yielding a quotient; and
subtracting 1 from the quotient of the dividing, yielding the weight of the heterogeneous data in the electronically accessible database in the system.
6. The method of claim 1, wherein generating the estimated risk of the heterogeneous data in the electronically accessible database in the system in reference to the weight in the memory of the system further comprises:
generating the estimated risk in reference to the weight of the heterogeneous data of the time dimension having the distinguishing extreme magnitudes in the memory of the system, a risk statistic, a scaling based on a confidence level of the risk statistic and a selected extreme period return of an asset.
7. A method of determining variance in heterogeneous data, the heterogeneous data including a time dimension and a performance measurement, the method comprising:
storing an electronically accessible repository of the heterogeneous data in a system, the system including at least one computing device with a processor and memory, the memory storing executable instructions that are executable by the processor;
identifying unstable periods of the performance measurement of the heterogeneous data of the electronically accessible repository in the system;
generating a weight of the heterogeneous data of the time dimension having the unstable periods of the performance measurement of the heterogeneous data of the electronically accessible repository in the memory of the system; and
generating an instability estimator of a risk statistic of the heterogeneous data of the electronically accessible repository of the system in reference to the weight.
8. The method of claim 7, wherein the identifying further comprises:
identifying data of the heterogeneous data having performance measurement that is greater than a cutoff.
9. The method of claim 8, wherein the cutoff further comprises:
2 standard deviations of the heterogeneous data.
10. The method of claim 7, wherein generating the weight further comprises:
generating a first divider comprising a reverse divider of a 1 year average priceearnings ratio in a historical sample of average priceearnings ratio;
generating a second divider comprising a divider of a 1 year average junk spread;
generating a third divider comprising a reverse divider of 180-day change in average 1-year junk spreads, at the time at which the priceearnings ratio of the heterogeneous data is observed;
summing the first divider, the second divider and twice the third divider;
dividing the sum by 20, yielding a quotient; and
subtracting 1 from the quotient of the dividing, yielding the weight of the heterogeneous data in the electronically accessible repository in the system.
11. The method of claim 7, wherein generating the instability estimator of the risk statistic of the heterogeneous data in the electronically accessible repository in the system in reference to the weight in the memory of the system further comprises:
generating the instability estimator in reference to the weight of the heterogeneous data of the time dimension having the unstable periods in the memory of the system, a risk statistic, a scaling based on a confidence level of the risk statistic and a selected extreme period return of an asset.
12. The method of claim 7, wherein the heterogeneous data further comprises:
financial data.
13. A system comprising:
a processor;
a storage device coupled to the processor, operable to store heterogeneous financial data of an item and variance rules;
a weighting engine that is operable on the processor to receive, distinguish and identify extreme heterogeneous financial data and over-weight the extreme heterogeneous financial data; and
an analytical engine that is operable on the processor to receive the over-weighted extreme heterogeneous financial data, the variance rules, and the heterogeneous financial data, and operable on the processor to perform the variance rules on the heterogeneous financial data using the over-weighted extreme financial data to generate or yield an instability estimator.
14. The system of claim 13, wherein the heterogeneous financial data further comprises:
securities data.
15. The system of claim 13, wherein the variance rules further comprise:
value-at-risk variance rules.
16. The system of claim 13, wherein the analytical engine further comprises:
a leading indicator of future periods of extreme activity of the item measured by the heterogeneous financial data.
17. The system of claim 13, wherein identify further comprises:
identify a subset of the heterogeneous financial data having performance measurement that is greater than a cutoff.
18. The system of claim 17, wherein the cutoff further comprises:
2 standard deviations of the heterogeneous financial data.
19. The system of claim 13, wherein generating the weight further comprises:
generating a first divider comprising a reverse divider of a 1 year average priceearnings ratio in a historical sample of average priceearnings ratio;
generating a second divider comprising a divider of a 1 year average junk spread;
generating a third divider comprising a reverse divider of 180-day change in average 1-year junk spreads, at a time at which the priceearnings ratio of the heterogeneous data is observed;
summing the first divider, the second divider and twice the third divider;
dividing the sum by 20, yielding a quotient; and
subtracting 1 from the quotient of the dividing, yielding the weight of the heterogeneous data in the storage device.
20. The system of claim 13, wherein generating the instability estimator of the heterogeneous financial data in the storage device in reference to the weight further comprises:
generating the instability estimator in reference to the weight of the heterogeneous financial data having unstable periods in the storage device, a scaling based on a confidence level of the risk statistic and a selected extreme period return of the item.