Notice of Pre-AIA or AIA Status
The present application 19/039,357, filed on 1/28/2025 (or after March 16, 2013), is being examined under the first inventor to file provisions of the AIA (First Inventor to File).
In the event the determination of the status of the application as subject to AIA 35
U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application is a CON of 18/239,471 filed on 08/29/2023 is now US PAT 12,235,829, 18/239,471 has DOM PRO 63/402,599 filed on 08/31/2022
DETAILED ACTION
Response to Amendment
Claims 21-42 are pending, claims 1-20 are canceled in this application.
Examiner acknowledges applicant’s preliminary amendment filed on 6/22/2026
Drawings
The Drawings filed on 3/14/2024 are acceptable for examination purpose.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/1/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner, PTO-1449 mailed on 2/20/2026
Priority
Acknowledgment is made of applicant’s claim for domestic priority application
U.S. Provisional Patent application serial number # 63/402,599 filed on 08/31/2022
under 35 U.S.C. 119 (e)
35 USC § 112
In view of applicant’s amendment to the claims 28,38, the rejection under 35 USC § 112 as set forth in the previous office action is hereby withdrawn.
Double Patenting
Applicant may further consider filing terminal disclaimer to overcome double patent rejection
Response to Arguments
Applicant's arguments filed 6/22/2026 with respect to claims 21-42 have been fully considered but they are not persuasive, for examiner’s response, see discussion below:
35 USC § 101
a)At page 9-15, claim 1, applicant argues:
“filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures" and "synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data in the one or more system columns" include limitations that cannot be practically performed in the human mind.(p-11-12)
The preent application claim provides the technical benefits of notional data in large quantities while still capturing the interrelated properties or characteristics within the dataframe(s) as are present in real-world data, is not directed to an abstract idea……(p-12-13). In summary, claim 21 is directed to patent-eligible subject matter because claim 21 recites features that do not fall into one of the enumerated groupings (p-13)
Examiner’s response:
Examiner submits that the pending claims (as amended 6/22/2026) should pass the test set forth in the 2019 Revised Patent Subject Matter Eligibility Guidance published on January 7, 2019 (84 Fed. Reg. 50), as updated October 2019, referred to herein as the PEG 2019. Applicant will focus on Prong Two of Step 2A, in evaluating the pending claims using this section of the test set forth in the PEG 2019
As explained in the 2019 PEG, the evaluation of Prong Two of Step 2A requires the use of the considerations (e.g. improving technology, effecting a particular treatment or prophylaxis, implementing with a particular machine, etc.) identified by the Supreme Court and the Federal Circuit, to ensure that the claim as a whole “integrates [the] judicial exception into a practical application [that] will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception”. These considerations are set forth in the 2019 PEG, MPEP 2106.05(a) through (c), and MPEP 2106.05(e) through (h). Note, a specific way of achieving a result is not a stand-alone consideration in Step 2A Prong Two. However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception. If the claim integrates the judicial exception into a practical application based upon evaluation of these considerations, the additional limitations impose a meaningful limit on the judicial exception, and the claim is eligible at Step 2A.
For example, if the additional limitations as amended 6/22/2025 (filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures;
synthetically generating the notional data associated with the one or more
object types based at least in part on the relationship data in the one or more system
columns) do not provide “improvement to another technology or technical field”, for example associated with the one or more object types……..relationship data…… under broadest reasonable interpretation, cover performance of the limitations mental process user/actor that constitute certain methods of organizing human activity but for the recitation of generic computer component(s) and/or general-purpose computer processor to implement the abstract idea. As discussed, the claims as amended (6/22/2065) the broadest reasonable interpretation of above steps is that those steps fall within the mental process grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgement and opinion. See MPEP 2106.04(a)(2).
Taking the claim 21 (6/6/2025) elements separately, the functions performed in claim 1 by the generically recited object types……….relationship data….. add nothing that is not already present when the limitations are considered separately. For example, claim 1 does not purport to improve the functioning of the data structure including object types, relationship data themselves. Nor does claim 21 effect an improvement in any other technology or technical field. Instead, claim 21 (as amended 6/6/2025) amounts to nothing significantly more than an instruction to apply the abstract idea using generic computer components performing routine computer functions That is not enough to transform an abstract idea into a patent-eligible invention. See Alice, 573 US at 225-26; see also Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372,1378 (Fed.Cir.2017) (sequence of receiving, analyzing, modifying, generating, displaying, and transmitting data recited an abstraction)
At page 14-15, examiner noted claim 41-42 remarks, and applies above arguments of claim 21, 31,39, and claims 22-30,32-42 depend from claim 21, 31, 39 as such, the pending claims fail Prong Two of Step 2A-2B of the PEG 2019. Therefore, examiner maintains rejection under 35 U.S.C. § 101
b)At page 9-10, claim 21, applicant argues:
The prior art of Rehal fails to teach “filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures;
synthetically generating the notional data associated with the one or more
object types based at least in part on the relationship data in the one or more system
columns”, and the prior art fails to teach notional data………
Rehal fails to teach or suggest the generating of such “notional data” because, as asserted in the office action, Rehal teaches data import process………specially, neither the data imported from the source data base nor the metadata……”notional data”…….
Examiner’s response:
As to the above argument (b), as best understood by the examiner, the prior art of Rehal is directed to data management in a large scaled data repository, more specifically defining the data structure, database entities and storing the metadata relationships (Rehal: Abstract, fig 1, 0061-0062). The prior art of Rehal teachers defines hierarchical data structure, defining functional relationship including data type, entity, parent, grandparent relationship satisfying dataframe, particularly instant specification dataframe para 0034,0037 is identical to Rehal’s fig 17)
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Prior art of Rehal teaches add(ing) entries in a given column to the table, defining functional relationship between data in performing statistical function particularly distinct values per column is identified in processing and identifying respective data values for the added column pairs (Rehal: fig 9, 0229-0231), is identical to instant specification 0034, 0037-0038);
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The prior art of Sap is directed to simulation of data behavior, more specifically enterprise data conforming to the metadata, analyze data in accordance with defined enterprise APIs including generate artificial API conforming to the enterprise databases (Sap: Abstract, fig 1). It is however noted that Rehal does not teach “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data in the one or more columns”, although Rehal teaches data tap metadata data structure associated with relationships among data fields particularly defining the data type(s) (Rehal: fig 5A-5B). On the other hand, Sap disclosed “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data (Sap: Abstract, 0015,0052-0057, fig 2, Sap teaches generating artificial enterprise data where processor functionally configure to analyze enterprise data including metadata supported by the artificial API), and synthetically generating the notional data corresponds to Sap’s artificial enterprise data “in the one or more system columns” (Sap: fig 2, 0130-0132, 0134,0140, fig 5,0213-0215), it is further noted that artificial data or synthetic data generated in data analysis containing real-world data using artificial API as detailed in fig 2, fig 5
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It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention simulation of production data behavior particularly generat[ing] artificial enterprise data including metadata of Sap et al., into managing large scale data repository of Rehal because both Rehal, Sap teaches database records including metadata characteristics (Rehal: Abstract, fig 1, fig 5A-5B; Sap: 01020-0121), while Sap teaches artificial sets (fig 2, element 2) in data analysis. it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to generat[ing] artificial datasets having metadata in particularly learn inter-dependencies and/or trends that allows to analyze overall data, generating an enterprise environment similar to the enterprise’s data sets behavior thereby compare the plural of enterprise software products, proof of concept testing (Sap: 0015-0017), thus improves overall quality and reliability of the system.
Examiner applies above arguments to claim 21, 31,39, and claims 22-30,32-42 depend from claim 21, 31, 39
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-42 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application.
Claim 21-42 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the 2019 Revised Patent Subject Matter Eligibility Guidance, Federal Register (84 FR 50) on January 7, 2019 hereinafter 2019 PEG
Step 1. In accordance with Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method of claim 21,31,39, directed to one of the eligible categories of subject matter and therefore satisfy Step 1.
Step 2A. In accordance with Step 2A prong one of the 2019 PEG, the limitations reciting the abstract idea are highlighted, and the limitations directed to additional elements are highlighted, as set forth in exemplary claim 1
claims1 - 20. (Cancelled)
claim 21,31
receiving one or more functional relationships associated with one or more object types in a base dataframe;
adding one or more system columns to one or more data structures in an intermediate dataframe based at least in part on the one or more functional relationships;
filling relationship data associated with the one or more functional
relationships in the one or more system columns in the one or more data structures;
synthetically generating the notional data associated with the one or more
object types based at least in part on the relationship data in the one or more system
columns; and
outputting the generated notional data;
wherein the method is performed using one or more processors for data
processing”,
claim 39:
the additional limitation “filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures in the one intermediate dataframe
wherein the method is performed using one or more processors for data processing”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example receiving, adding, generating data, filtering relationship data, these limitations encompasses the user thinking of collection of data
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas set forth in the 2019 PEG. Accordingly, the claim recites an abstract idea.
With respect to Step 2A prong two of the 2019 PEG, the judicial exception is not integrated into a practical application. The additional elements are directed to method steps, however, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular data structure of gallery images collect(ion) that identify particular match, to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Furthermore, although these elements have been fully considered, they are directed to the use of generic computing elements (fig 4, 0086-0087,0097-0100 of the instant specification make it clear that the disclosed functionality is implemented on well-known computing systems and general purpose computing devices) to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the 2019 PEG) and is amount to simply saying "apply it" using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment computer based operating environment) by using the computer as a tool to perform the abstract idea.
Since the analysis of Step 2A prong one and prong two results in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional method limitations are directed to a generic computer, at a very high level of generality and without imposing meaningful limitations on the scope of the claim. In addition, fig 4, 0086-0087,0097-0100 of the instant specification describe generic off-the-shelf computer-based elements for implementing the claimed invention which does not amount to significantly more than the abstract idea and is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. Further, See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to 'implement[ing] the abstract idea of intermediated settlement on a generic computer', it cannot save O/P's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). See also, Affinity Labs of Texas LLC v. DirecTV LLC, 838 F.3d 1253, 1257-1258 (Fed. Cir. 2016) (mere recitation of a GUI does not make a claim patent-eligible); Intellectual Ventures I LLC v. Capital One Bank, 792 F.3d 1363, 1370 (Fed. Cir. 2015) ("the interactive interface limitation is a generic computer element".)
The additional elements are broadly applied to the abstract idea at a high level of generality ("similar to how the recitation of the computer in the claims in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer,") as explained in MPEP § 2106.05(f)) and they operate in a well-understood, routine, and conventional manner.
MPEP § 2106.05 (d)(II) sets forth the following:
The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec...; TLI Communications LLC v. AV Auto. LLC...; OIP Techs., Inc., v. Amazon.com, Inc... ; buySAFE, Inc. v. Google, Inc...;
Performing repetitive calculations, Flook ... ; Bancorp Services v. Sun Life...;
Electronic recordkeeping, Alice Corp...; Ultramercial... ;
Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc...;
Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank...; and
A web browser's back and forward button functionality, Internet Patent Corp. v. Active Network, Inc...
Courts have held computer-implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking).
Claim 22,32 further elaborates The method of claim 21, wherein the intermediate dataframe is different from the base dataframe”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 23,33 The method of claim 22, wherein the synthetically generating the notional data comprises:
synthetically generating the notional data in a notional dataframe by removing the one or more system columns in the intermediate dataframe;
wherein the notional dataframe is different from the base dataframe and the intermediate dataframe”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 24,34 The method of claim 21, wherein the one or more functional relationships include at least one selected from a group consisting of hierarchical relationship, time-series relationship, geographic movement relationship, and trend relationship”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 25,35, The method of claim 21, wherein the one or more data structures include one or more data tables”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 26,36. The method of claim 21, “generating the relationship data in one of the one or more system columns based at least in part on a trend relationship including changes in a trend, the trend relationship being one of the one or more functional relationships”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 27,37, “generating the relationship data in one of the one or more system columns based at least in part on a hierarchical relationship indicating a statistical data property of a dataset for an entity, the hierarchical relationship being one of the one or more functional relationships”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 28,38, The method of claim 21, wherein the one or more functional relationships includes a change relationship defining a function applicable to data in the base dataframe”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 29, The method of claim 21, wherein the one or more functional relationships includes a change relationship including one or more randomized changes applicableto data in the base dataframe”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 30, The method of claim 21, wherein the one or more functional relationships includes a change relationship including increments or decrements by a percentage within a predetermined range”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim 40, The method of claim 39, wherein the one intermediate dataframe is a first intermediate dataframe;
wherein the data is one or more first data sequences;
wherein the one or more functional relationships include a time-based relationship;
the method further coprising:
generating one or more second data sequences in a second intermediate dataframe of the plurality of intermediate dataframes, the second intermediate dataframe being subsequent to the first intermediate dataframe, by at least:
adding, in the second intermediate dataframe, the one or more data structures based at least in part on the one or more functional relationships;
filling the relationship data in the one or more data structures in the second intermediate dataframe based at least in part on the one or more functional relationships; and
generating the one or more second data sequences in the second intermediate dataframe based at least in part on the one or more first data sequences in the first intermediate dataframe and the one or more functional relationships”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
As to Claim 41, “applying one or more changes to seed data of the one or more object types in the base dataframe according to the one or more functional relationships such that the synthetically generated notional data maintains the statistical data property indicated by the hierarchical relationship”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
As to Claim 42, “applying one or more changes to seed data of the one or more object types in the base dataframe based at least in part on the relationship data in the one or more system columns such that the synthetically generated notional data maintains one or more interrelated properties or characteristics within the intermediate dataframe according to the one or more functional relationships”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 21-42 of US Application No. 19/039,357 (as amended 6/22/2026) are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 12,235,829. Although the claims at issue are not identical, they are not patentably distinct from each other because the patented claims perform the same steps as the claims in the instant application.
Instant US application: 19/039,357
US Patent No. 12,235,829
Claim 21,31,39, A method for generating notional data for data processing, the method comprising:
receiving one or more functional relationships associated with one or more object types in a base dataframe;
adding one or more system columns to one or more data structures in an intermediate dataframe based at least in part on the one or more functional relationships;
filling relationship data associated with the one or more functional
relationships in the one or more system columns in the one or more data structures;
synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data in the one or more system columns; and
outputting the generated notional data;
wherein the method is performed using one or more processors for data processing.
Claim 1,9,17, A method for generating notional data for data processing, the method comprising:
receiving seed data of one or more object types in a base dataframe;
defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types;
synthetically generating intermediate data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships by at least:
adding one or more system columns to one or more data structures in an intermediate dataframe corresponding to the one or more object types based at least in part on the one or more functional relationships; and
generating the intermediate data by filling relationship data in the one or more system columns in the one or more data structures based at least in part on the one or more functional relationships;
synthetically generating the notional data based at least in part on the generated intermediate data of the one or more object types and the one or more system columns; and
outputting the generated notional data to one or more memories that store the generated notional data;
wherein the method is performed using one or more processors for data processing
It would have been obvious to a person of ordinary skill was made to modify and/or to omit the additional elements of claim 1-18 of U.S. Patent No. 12,235,829 to arrive at the claims 21-40 of the instant application 18/604,868 because the ordinary skilled person would have realized that the remaining element(s) would perform the same function as before and the only difference particularly claim 23,33 instant application 18/604,868 filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures while claim 1 of U.S. Patent No. 12,235,829, synthetically generating intermediate data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships generating the intermediate data by filling relationship data in the one or more system columns in the one or more data structures based at least in part on the one or more functional relationships limitation(s) is/are absent of the limitation from instant application 18/604,868 claim 23,33, Omission and/or addition of elements and its function in combination is obvious expedient if the remaining elements perform same functions as before, as such instant application claim 21,31 are broader
It would have been obvious to a person of ordinary skill in the art at the time the invention was made to modify, add or omit the additional elements of claims 1,9,17 to arrive at the claims 21,31,39 of the instant application because the person would have realized that the remaining element would perform the same functions as before. "Omission of element and its function in combination is obvious expedient if the remaining elements perform same functions as before." See In re Karlson (CCPA) 136 USPQ 184, decide Jan 16, 1963, Appl. No. 6857, U. S. Court of Customs and Patent Appeals.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 21-42 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rehal, US Pub. No. 2018/0095952 published Apr, 2018 in view of SAPOZHNIKOV et al., (hereafter Sap), US Pub. No. 2019/0114251 published Apr, 2019.
Claims 1 - 20. (Cancelled)
As to claim 21,31. (New) Rehal teaches a system which including “A method for generating notional data for data processing, the method comprising (Rehal: Abstract, fig 1 – Rehal teaches data processing, managing data in a data repository)
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“receiving one or more functional relationships associated with one or more object types in a base dataframe”” (Rehal: fig 17, 0349,0351 Rehal defines hierarchical data structure defining functional relationship including data type, entity, parent, grandparent relationsip satisfying dataframe, particularly instant specification dataframe para 0034,0037 is identical to Rehal’s fig 17)
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“adding one or more system columns to one or more data structures in an intermediate dataframe based at least in part on the one or more functional relationships” (Rehal: fig 9, 0229-0231 – Rehal teaches add(ing) entries in a given column to the table, defining functional relationship between data in performing statistical function particularly distinct values per column is identified in processing and identifying respective data values for the added column pairs, is identical to instant specification 0034, 0037-0038);
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“filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures” (Rehal : fig 3, 0126-0139, 0152-0155, fig 3-4 – Rehal teaches data lake schema that including generating metadata schema changes that affecting the data lake data particularly adding column to a table, change in column length and/size thereby filling set of schema changes, thus provides extensible schema that affects functional relationships such as index change, list of tables and like);
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“outputting the generated data” (Rehal: 0236 – Rehal output identified data schema information);
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“wherein the method is performed using one or more processors for data processing” (Rehal: fig 26-27, 0027,0457-0459 – Rehal teaches system configured both hardware and software).
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It is however noted that Rehal does not teach “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data in the one or more columns”, although Rehal teaches data tap metadata data structure associated with relationships among data fields particularly defining the data type(s) (Rehal: fig 5A-5B). On the other hand, Sap disclosed “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data (Sap: Abstract, 0015,0052-0057, fig 2, Sap teaches generating artificial enterprise data where processor functionally configure to analyze enterprise data including metadata supported by the artificial API), and synthetically generating the notional data corresponds to Sap’s artificial enterprise data “in the one or more system columns” (Sap: fig 2, 0130-0132, 0134,0140, fig 5,0213-0215), it is further noted that artificial data or synthetic data generated in data analysis containing real-world data using artificial API as detailed in fig 2, fig 5
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It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention simulation of production data behavior particularly generat[ing] artificial enterprise data including metadata of Sap et al., into managing large scale data repository of Rehal because both Rehal, Sap teaches database records including metadata characteristics (Rehal: Abstract, fig 1, fig 5A-5B; Sap: 01020-0121), while Sap teaches artificial sets (fig 2, element 2) in data analysis. it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to generat[ing] artificial datasets having metadata in particularly learn inter-dependencies and/or trends that allows to analyze overall data, generating an enterprise environment similar to the enterprise’s data sets behavior thereby compare the plural of enterprise software products, proof of concept testing (Sap: 0015-0017), thus improves overall quality and reliability of the system.
As to Claim 22,32, the combination of Rehal, Sap disclosed “ wherein the intermediate dataframe is different from the base dataframe” (Rehal: 0014,0061,0070, fig 1-2).
As to Claim 23,33, the combination of Rehal, Sap disclosed:
“generating the data in a dataframe by removing the one or more system columns in the intermediate dataframe” (Rehal: fig 5A,0167-0168);
“wherein the dataframe is different from the base dataframe and the intermediate dataframe” (Rehal: fig 5A-B, 0167-0168,0176,0178). On the other hand, Sap disclosed “synthetically generating the notional data” (Sap: Abstract, 0015,0052-0057, fig 2)
As to Claim 24,34, the combination of Rehal, Sap disclosed “wherein the one or more functional relationships include at least one selected from a group consisting of hierarchical relationship, time-series relationship, geographic movement relationship, and trend relationship” (Rehal: 0349,0352-0353,0358)
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As to Claim 25,35, the combination of Rehal, Sap disclosed “wherein the one or more data structures include one or more data tables” (Rehal: fig 5A, 6A, fig 8)
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As to Claim 26,36, the combination of Rehal, Sap disclosed:
“generating the relationship data in one of the one or more system columns based at least in part on a trend relationship including changes in a trend, the trend relationship being one of the one or more functional relationships” (Rehal: fig 13-14, 0262-0266,0273, 0290)
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As to Claim 27,37, the combination of Rehal, Sap disclosed:
“generating the relationship data in one of the one or more system columns based at least in part on a hierarchical relationship indicating a statistical data property of a dataset for an entity (Rehal: 0231, 0297-0298)the hierarchical relationship being one of the one or more functional relationships” (Rehal : 0349,0352-0353,0358).
As to Claim 28,38, the combination of Rehal, Sap disclosed: “wherein the one or more functional relationships includes a change relationship defining a function applicable to data in the base dataframe” (Rehal: fig 9, 0229-0231)
As to Claim 29,39, the combination of Rehal, Sap disclosed “wherein the one or more functional relationships includes a change relationship including one or more randomized changes applicable to data in the base dataframe” (Rehal: 0129-0142)
As to Claim 30, the combination of Rehal, Sap disclosed “wherein the one or more functional relationships includes a change relationship including increments or decrements by a percentage within a predetermined range” (Rehal: fig 9, 0234-0236).
As to Claim 39. (New) Rehal teaches a system which including “A method for generating notional data for data processing, the method comprising: (Rehal: Abstract, fig 1 – Rehal teaches data processing, managing data in a data repository)
“receiving an input indicating one or more functional relationships associated with one or more object types in a base dataframe” (Rehal: fig 17, 0349,0351 Rehal defines hierarchical data structure defining functional relationship including data type, entity, parent, grandparent relationship satisfying dataframe, particularly instant specification dataframe para 0034,0037 is identical to Rehal’s fig 17)
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“adding, in one intermediate dataframe of a plurality of intermediate dataframes, one or more system columns to one or more data structures based at least in part on the one or more functional relationships” (Rehal: fig 9, 0229-0231 – Rehal teaches add(ing) entries in a given column to the table, defining functional relationship between data in performing statistical function particularly distinct values per column is identified in processing and identifying respective data values for the added column pairs, is identical to instant specification 0034, 0037-0038);
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“filling relationship data associated with the one or more functional relationships in the one or more system columns in the one or more data structures in the one intermediate dataframe of the plurality of intermediate dataframes” (Rehal: fig 10-14A, 0176-0178,0288-0292,0297-0299)
“generating the data associated with the one or more object types based at least in part on the relationship data in the one or more system columns” (Rehal: fig 2A-2B, 0082-0084, 0089-0090 – Rehal teaches data import process from a source database table(s) and involves schema changes to the table(s), changes to the metadata)
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outputting the generated data” (Rehal: 0236 – Rehal output identified data schema information);
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“wherein the method is performed using one or more processors for data processing” (Rehal: fig 26-27, 0027,0457-0459 – Rehal teaches system configured both hardware and software).
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It is however noted that Rehal does not teach “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data in the one or more columns”, although Rehal teaches data tap metadata data structure associated with relationships among data fields particularly defining the data type(s) (Rehal: fig 5A-5B). On the other hand, Sap disclosed “synthetically generating the notional data associated with the one or more object types based at least in part on the relationship data (Abstract, 0015,0052-0057, fig 2, Sap teaches generating artificial enterprise data where processor functionally configure to analyze enterprise data including metadata supported by the artificial API), and synthetically generating the notional data corresponds to Sap’s artificial enterprise data “in the one or more system columns” (Sap: 0130-0132, 0134,0140)
It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention simulation of production data behavior particularly generat[ing] artificial enterprise data including metadata of Sap et al., into managing large scale data repository of Rehal because both Rehal, Sap teaches database records including metadata characteristics (Rehal: Abstract, fig 1, fig 5A-5B; Sap: 01020-0121), while Sap teaches artificial sets (fig 2, element 2) in data analysis. it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to generat[ing] artificial datasets having metadata in particularly learn inter-dependencies and/or trends that allows to analyze overall data, generating an enterprise environment similar to the enterprise’s data sets behavior thereby compare the plural of enterprise software products, proof of concept testing (Sap: 0015-0017), thus improves overall quality and reliability of the system.
As to Claim 40, the combination of Rehal, Sap disclosed
“wherein the data is one or more first data sequences” (Rehal: 0137-0138);
“wherein the one or more functional relationships include a time-based relationship” (Rehal : 0060,0111); the method further comprising:
“generating one or more second data sequences in a second intermediate dataframe of the plurality of intermediate dataframes, the second intermediate dataframe being subsequent to the first intermediate dataframe” (Rehal: fig 6A, 0193-0194, 0266-0268, 0493), by at least:
“adding, in the second intermediate dataframe, the one or more data structures based at least in part on the one or more functional relationships” (Rehal: fig 9, 0229-0231);
filling the relationship data in the one or more data structures in the second intermediate dataframe based at least in part on the one or more functional relationships (Rehal: fig 10-14A, 0176-0178,0288-0292,0297-0299)
and
“generating the one or more second data sequences in the second intermediate dataframe based at least in part on the one or more first data sequences in the first intermediate dataframe and the one or more functional relationships” (Rehal: 0112-0122, 0268-0269).
As to claim 41-42, the combination of Rehal, Sap disclosed:
applying one or more changes to seed data of the one or more object types in the base dataframe according to the one or more functional relationships such that the generated data maintains the Rehal: fig 9, 0229-0231) statistical data property indicated by the hierarchical relationship (Rehal: fig 18A-18B,0352-0353). On the other hand, Sap disclosed “synthetically generated notional data” (Sap: Abstract, 0015,0052-0057, fig 2)
Conclusion
The prior art made of record
a. US Pub. No. 2018/0095952
b. US Pub. No. 2019/0114251
Examiner's Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
SEE MPEP 2141.02 [R-5] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984) In re Fulton, 391 F.3d 1195, 1201,73 USPQ2d 1141, 1146 (Fed. Cir. 2004). >See also MPEP §2123.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant's disclosure
Authorization for Internet Communications
The examiner encourages Applicant to submit an authorization to communicate with the examiner via the Internet by making the following statement (from MPEP 502.03):
“Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.”
Please note that the above statement can only be submitted via Central Fax (not Examiner's Fax), Regular postal mail, or EFS Web using PTO/SB/439.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Srirama Channavajjala whose telephone number is 571-272-4108. The examiner can normally be reached on Monday-Friday from 8:00 AM to 5:30 PM Eastern Time.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gorney, Boris, can be reached on (571) 270- 5626. The fax phone numbers for the organization where the application or proceeding is assigned is 571-273-8300 Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free)
/Srirama Channavajjala/Primary Examiner, Art Unit 2154
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