# US 8,156,108 B2 · Methods and systems for creation and use of raw-data datastore > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,156,108 B2 - Document ID: US8156108B2 - Status: Granted - Kind: B2 - Application number: 12/405,982 - Filed: 2009-03-17 - Published: 2009-09-24 - Granted: 2012-04-10 - Earliest claimed: 2008-03-19 - Assignees: Intelliscience Corporation - Inventors: Nicholas L. Middleton; Robert Leon Bass, II; Bryan Glenn Donaldson - Web page: https://patentgrep.com/patent/US8156108B2 ## CPC - G06F 16/20: of structured data, e.g. relational data - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A raw-data datastore during data analysis and feature recognition abstracts away and/or reduces dependency upon typically required components of datastore training. The datastore functions to store the original data values of a data set selection, which can represent a known feature. In some embodiments, the original data set is retained as the raw data value set referenced by the raw-data datastore. The use of this raw-data datastore eliminates the need for continued manual retraining of the original data values and patterns, which can be associated with a particular known feature, each time the pluralities of evaluation algorithms and/or the target data area are altered, changed, modified, or reconfigured. ## Claims ### Claim 1 A system for creation and use of a raw data datastore, comprising: a computer having a processor and a memory, the memory containing a database of raw data, the memory further containing stored programming instructions operable by the processor to: create the raw data datastore and store the raw data datastore in memory, the raw data datastore containing references to the database of raw data that are associated with known features within the database of raw data and defects associated with the database of raw data; wherein the defects associated with the database of raw data comprise one or more instances of data confusion present in the database of raw data; and further wherein the one or more instances of data confusion comprise a plurality of locations within the database of raw data in which different data elements produce the same results upon operation by a common algorithm, and further wherein such instances of data confusion are identified within the database of raw data and are stored within the raw data datastore. ### Claim 2 (depends on 1) The system of claim 1, further comprising a display associated with the computer, and wherein the stored programming instructions further enable the processor to present on the display a representation of the instances of data confusion. ### Claim 3 (depends on 2) The system of claim 2, wherein the representation of the instances of data confusion comprises an indication of the actual count of the instances of data confusion. ### Claim 4 (depends on 1) The system of claim 1, wherein the stored programming instructions further enable the processor to modify a trained association between one or more known features and the data elements within the raw data database that are associated with instances of data confusion. ### Claim 5 (depends on 4) The system of claim 4, wherein the modification of the trained association further comprises one or both of modifying a target data area related to the data elements or eliminating the data element as being associated with the known feature. ### Claim 6 (depends on 1) The system of claim 1, wherein the defects associated with the database of raw data further comprise one or more instances of algorithm confusion present in the database of raw data. ### Claim 7 (depends on 6) The system of claim 6 wherein the one or more instances of algorithm confusion comprise a plurality of target data areas that are substantially indistinguishable from one another upon operation by plurality of different algorithms. ### Claim 8 (depends on 7) The system of claim 7, further comprising a display associated with the computer, and wherein the stored programming instructions further enable the processor to present on the display a representation of the instances of algorithm confusion. ### Claim 9 (depends on 8) The system of claim 8, wherein the representation of the instances of algorithm confusion comprises an indication of the actual count of the instances of algorithm confusion. ### Claim 10 (depends on 9) The system of claim 9, wherein the stored programming instructions further enable the processor to modify a trained association between one or more known features and the data areas within the raw data database that are associated with instances of algorithm confusion. ### Claim 11 (depends on 10) The system of claim 10, wherein the modification of the trained association further comprises one or both of modifying the target data area related to the instance of algorithm confusion or eliminating the data area as being associated with the known feature. ### Claim 12 (depends on 1) The system of claim 1, wherein the references to the database of raw data comprise pointers to locations within the database of raw data. ### Claim 13 (depends on 1) The system of claim 1, wherein the references to the database of raw data comprise a subset of values from the database of raw data. ### Claim 14 (depends on 1) The system of claim 1, wherein the raw data datastore is created by training the database of raw data using one or more algorithms operating on a plurality of target data areas within the database of raw data. ### Claim 15 (depends on 1) The system of claim 1, wherein the raw data datastore further comprises an association between one or more algorithms and a plurality of specified portions of the database of raw data upon which the one or more algorithms are operated in order to produce the associations between the database of raw data and at least one of the known features or the defects. ### Claim 16 (depends on 15) The system of claim 15, wherein the stored programming instructions further cause the processor to modify the association of known features by processing an additional algorithm on at least one of the target data areas indicated within the raw data datastore to be associated with the known feature. ### Claim 17 (depends on 16) The system of claim 16, wherein the stored programming instructions further cause the processor to update the raw data datastore with at least one additional association between the additional algorithm and the known feature.