Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in response to the communication filed on June 22, 2026.
Response to Amendment
Applicants’ amendment filed on June 22, 2026, with respect to claims 21-40 has been received, entered into the record and considered.
As a result of the amendment filed on June 22, 2026, claim 21, 32 and 40 have been amended.
Claims 21-40 remain pending in this office action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on June 22, 2026, has been entered.
Double Patenting
7. 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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) 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 www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 21-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of U.S. Patent No. 12,008,006 B1. Although the claims at issue are not identical, they are not patentably distinct from each other because the current application 18/659193 and the patent 12,008,006 B1 both directed to versioned of datasets changes in different time retroactively. The current application just omitted some limitations from the patented claims. Such omitting does not change the scope the invention and can perform same functionality. Therefore, the current application is not patentable over the patent 12,008,006 B1.
"A later patent claim is not patentably distinct from an earlier patent claim if the later claim is obvious over, or anticipated by, the earlier claim. In re Longi, 759 F.2d at 896, 225 USPQ at 651 (affirming a holding of obviousness-type double patenting because the claims at issue were obvious over claims in four prior art patents); In re Berg, 140 F.3d at 1437, 46 USPQ2d at 1233 (Fed. Cir. 1998) (affirming a holding of obviousness-type double patenting where a patent application claim to a genus is anticipated by a patent claim to a species within that genus). " ELI LILLY AND COMPANY v BARR LABORATORIES, INC., United States Court of Appeals for the Federal Circuit, ON PETITION FOR REHEARING EN BANC (DECIDED: May 30, 2001).
Claim Rejections - 35 USC § 101
8. 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.
9. Claims 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 This part of the eligibility analysis evaluates whether the claim falls within any statutory category, see MPEP 2106.03.
Step 2A Prong One This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04(II) and the October 2019 Update, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
Step 2A Prong 2 This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application, see 2019 PEG.
Step 2B This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim, see MPEP 2106.05.
Step 1 Statutory Category:
Claims 21-31 are recited as being directed to a “method”. Claims 32-39 are recited as being directed to a “system, comprising: one or more memories having instruction stored thereon”.
Claim 40 is recited as being directed to a “non-transitory computer-readable storage medium storing instructions that, when executed by one or more processor”. Thus claims 21, 32 and 40 have been identified to be directed towards the appropriate statutory category. Below is further analysis related to step 2.
a). In analyzing under step 2A Prong One, Does the claim recite an abstract idea law of nature or natural phenomenon? Yes.
claims 21, 32 and 40 recites, obtaining a first derived dataset associated with a first set of actions, wherein the first derived dataset is determined by applying a first version of data transformation logic to a first version of a dataset; obtaining a second version of the dataset, the second version of the dataset comprises added data not included in the first version of the dataset; generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset; determining one or more first differences between the first derived dataset and the second derived dataset by at least comparing the first derived dataset and the second derived dataset; and determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more second differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions, wherein at least a part of the method is performed by one or more processors.
As claim texts drafted by a set of very minimal limitations (or elements) of each of the three claim categories, generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset; determining one or more first differences between the first derived dataset and the second derived dataset by at least comparing the first derived dataset and the second derived dataset; and determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, are merely a process that, under its broadest reasonable interpretation, covers mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion), but for the recitation of processing unit, memory and a computer readable medium which are explicitly generic computing components, including:
“generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example: a set of data which existed before (i.e., historical data) a user can call it the first version of data. A user can access such historical data and do some insertion, or addition or deletion or change or modification or any other data transformation logic on that data will create a second version of data. If the user accesses the same data at a later date and time and does some more interaction with that data, it eventually will create second or third or fourth version of data and second or third or fourth version or transformation logic.
Therefore, generating limitation is a mental process (including an observation, evaluation, judgment, opinion).
Similarly, determining one or more first differences between the first derived dataset and second derived dataset by comparing the first derived dataset to the second derived dataset; and determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions. These limitations also can be performed using the human brain alone or with the aid of pen and paper. Examiner Broadest reasonable interpretation
Let’s look at a real-life scenario. Say for example a user has a table with 5 columns in it, Name, address, DOB, SSN and Phone number, respectively. The user created this table in January of 2026. This is the first version of data with first interaction logic. Two months later in April of 2026, the user accesses this table (now this the users previous or historical data) and added two more columns named as department and salary. This addition of these two columns will produce a second version of table which was created in January. And this addition of two columns is the second data transformation logic because I interacted on the first version of the table.
Then, when the user presents these two tables on a piece of paper or on a computer screen, the user can see the difference clearly between the first and second version of table. The user can compare it with first version and second version and see the difference in that first version of the table has 5 columns, and second version of the table has 7 columns. Second version of the derived from first version of the table, etc...
This can easily be done using the human brain alone or with the aid of pen and paper.
Therefore, these limitations can be performed in human mind. Therefore, generating limitation is a mental process (including an observation, evaluation, judgment, opinion).
The claim recites two additional; elements: obtaining a first derived dataset associated with a first set of actions, wherein the first derived dataset is determined by applying a first version of data transformation logic to a first version of a dataset; obtaining a second version of the dataset, the second version of the dataset comprises added data not included in the first version of the dataset.
The obtaining step as recited amounts to mere data gathering for use in the generating, determining and comparing step, which is a form of insignificant extra-solution activity, (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information)). Further obtaining step as recited also amounts to mere data gathering which is a form of insignificant extra-solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea
b) In analyzing under step 2A Prong Two, Does the claim recite additional elements that integrate the judicial exception into a practical application? NO.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – “system comprising one or more computers”, “one or more non-transitory computer readable storage medium”, and “training machine learning model”. The additional components are generic computer components even being recited as additional limitations, however, do not preclude the claims from reciting an abstract idea. For instance, as the above detailed analysis on the minimal limitations as abstract ideas that can be performed mentally in mind by human, without reciting any “additional element” to integrate the judicial exception into a practical application.
The processes of receiving necessities for performing an action and providing indication of completed such that it amounts no more than mere instructions to apply the exception using a generic computer component, processing unit(s), memory and computer readable medium for the processes. That is, the limitations represent well-understood, routine, conventional activity (See MPEP 2106.05(g) or 2106.05(d) for receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp). Accordingly, even considering all the elements as additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As such, the claim is directed to an abstract idea.
c) In analyzing under step 2B, does the claim recite additional elements that amount to significantly more than the judicial exception? NO
Claims 2, 12 and 21 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, there are simply no additional elements adding to the already analyzed very few minimal steps of performing action. The steps represent well-understood, routine, conventional activity previously known to the industry and are specified at a high level of generality, and in the context of the limitations reciting performing action that can be practically performed in the human mind and may be considered to fall within the mental process and mathematical concepts groupings.
As such, the limitations represent well-understood, routine, conventional activity (See MPEP 2106.05(g) or 2106.05(d) for receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp). The claims are not patent eligible.
Further the limitations in the dependent claims 3-11 and 13-20 are an extension of the abstract idea of claim 21, 32 and 40 above.
Claim Rejections - 35 USC § 103
10. 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.
11. Claims 21- 22, 25-26, 29-30, 32-33, 35-36, 38 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over “Schema versioning and database conversion techniques for bi-temporal databases”, Han-Chieh Wei and Ramez Elmasri; Department of Computer Science and Engineering, The University of Texas at Arlington, 200, herein after “Han”, in view of Wang et al (US 2014/0178886 A1).
As per claim 21, Han discloses:
- a method comprising: obtaining a first derived dataset associated with a first set of actions, wherein the first derived dataset is determined by applying a first version of logic to a first version of a dataset (employee relation table at time 10 (i.e., first derived dataset associated with first action), Figure 1-2, Page 26, Example 1, applying first change (i.e., first version of logic) to first version of dataset, Fig. 12, Page 26, Example 1),
- obtaining a second version of the dataset, the second version of the dataset comprises added data not included in the first version of the dataset (Fig. 1-4, in Fig.2 part (a) second version of table (i.e., second version of dataset) obtained, this second version of table comprises Bonus data (i.e., added data) in Part (a), and Bonus 5% (i.e., added data) in part (b) in different time t1 to t12, which is not included in first version of the table in Fig. 1, (i.e., first version of dataset), see also in section 4, Specially Fig. 6, line 9-25, in page 31-32, Fig. 7 (a) –(c), Fig. 8),
- generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset (second version of the dataset by adding Bonus, Phone (i.e., second set of action by applying second version of data transformation logic) which is the added data not included in the first version of the dataset, Fig. 1-4, Page 26-27, Example 1), Page, 23, line 1-10, Page 24, line 6-24, Page 30, section 4), Examiner Broadest reasonable interpretation: a data transformation logic is just input/output or any interaction with the data. For example: a set of data which existed before (i.e., historical data) we can call it the first version of data. A user can access such historical data and do some insertion, or addition or deletion or change or modification or any other data transformation logic on that data will create a second version of data. If the user accesses the same data at a later date and time and do some more interaction with that data, it eventually will create second or third or fourth version of data and second or third or fourth version or transformation logic.
Han does not explicitly disclose determining one or more first differences between the first derived dataset and second derived dataset by comparing the first derived dataset to the second derived dataset; and determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions, wherein at least a part of the method is performed by one or more processors. However, in the same field of endeavor Wang in an analogous art disclose determining one or more first differences between the first derived dataset and second derived dataset by comparing the first derived dataset to the second derived dataset (comparing first set of result and second set of result (i.e., first derived dataset and second derived dataset), Fig. 7, item 52, 55, 56, 57, Fig. 8, item 58-63, Fig. 10, item 206, Para [0009], [0151]), determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions (by comparing the first and second datasets and evaluating the differences between datasets and actions, Para [0163], [0164], [0170], [0202], [0203]), differences includes action on different sets of tissue samples (i.e., different version of dataset) which not in the first set of action or second set of action, Para [0476] – [0477], [0458]), wherein at least a part of the method is performed by one or more processors (Para [0439] – [0441], method performed by processor).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the action and dataset comparison output and determining the difference in different action as taught by Wang as the means to determine dataset and changes (i.e., logic) in first version and second version in various first time and second times in Han, (Han Fig. 1-2, section 3 and 4, Wang, Para [0009], Fig. 7, 10). Han and Wang are analogous prior art since they both dealing with changing historical versions of datasets in various times. A person of the ordinary skill in the art would have been motivated to make aforementioned modification to improve cost effective and flexible way to access temporal data. This is because one aspect of Han publication is to use bi-temporal database to make retroactive changes in versions of dataset in various time, (Han, Page 4, line 16-20). Comparing derived output of different versions of dataset and seeing the difference is part of this process. However, Han doesn’t specify any particular manner in which derived output of different first and second datasets and their associated actions are compared. This would have lead one of the ordinary skill in the art to seek and recognize the multiple dataset output and associated actions comparisons as taught by Wang. wang describes identifying the effect of different actions and evaluating that action in different dataset, Wang, Fig. 7, item 57, Fig. 21, Para [0469], item 907, to reduce experimental errors as desired by Han.
As per claim 22, rejection of claim 21 is incorporated, and further Han discloses:
- wherein the added data comprise one or more retroactive changes applied to the dataset via a data pipeline, wherein the data pipeline includes the second version of the logic (retroactive and proactive update to database schema, Page, 30, section 4, line 1-20).
As per claim 25, rejection of clam 21 is incorporated and further Wang discloses:
- determining one or more modifications to the first version of the logic based on the one or more second differences between the first set of actions and the second set of actions (determining a set of changes (i.e., logic) in data set and determine differences between first and second set, Para [0163] – [0164]).
As per claim 26, rejection of claim 21 is incorporated, and further Han discloses:
- wherein the dataset comprises: a stateful dataset, the first version of the dataset comprising a state of the first version of the logic (state of a data (i.e., stateful dataset), section 2, line 1-15, example 2).
As per claim 29, rejection of claim 21 is incorporated, and further Han discloses:
- receiving a first user input identifying the first version of the dataset and the first version of the logic via a user interface, the first user input enabling selection of the first version of the dataset from a data store and selection of the first version of the logic from a logic store, wherein data stored in the data store is immutable such that a modification to the dataset causes a new version of the dataset to be generated without affecting a prior version of the dataset (receiving input identifying a particular version and generating new version by modifying identified version, Page 24, line 6-20, section 4, page 30, Fig. 1-12),
- receiving, via the user interface, a second user input identifying the second version of the dataset and the second version of the logic (modified version or another derived version (i.e., second version) of the one or more data set, Page 27, section 3, Page 30, section 4, Fig. 1-12).
As per claim 30, rejection of clam 21 is incorporated and further Han discloses:
- determining a first action of the first set of actions performed in connection with the first derived dataset (adding phone to the table (i.e., performed first set of action) Fig. 3, which is in connection with derived version of schema table in Fig. 1-4, Page 26-27, Example 1),
- determining a second action of the second set of actions performed in connection with the first derived dataset (adding bonus to the table (i.e., performed second set of action) Fig. 3, which is in connection with derived version of schema table in Fig. 1-4, Page 26-27, Example 1).
As per claims 32-33, 35-36 and 38,
Claims 32-33, 35-36 and 38 are system claims corresponding to method claims 21-22, 25-26 and 29-30 respectively and rejected under the same reason set forth to the rejection of claims 32-33, 35-36 and 38 above.
As per claim 40,
Claim 40 is the computer readable medium claim corresponding to method claim 21 respectfully and rejected under the same reason set forth to the rejection of claim 21 above.
12. Claims 23-24, 27-28, 34 and 37 are rejected under 35 U.S.C. 103 as being unpatentable over “Schema versioning and database conversion techniques for bi-temporal databases”, Han-Chieh Wei and Ramez Elmasri; Department of Computer Science and Engineering, The University of Texas at Arlington, 200, herein after “Han”, in view of Wang et al (US 2014/0178886 A1), as applied to claim 21 and 32 above and further in view of Dye et al (US 2018/0285976 A1).
As per claim 23, rejection of claim 21 is incorporated, and further Han discloses:
- determining one or more performed actions in connection with the first derived dataset (adding phone to the table (i.e., performed action) Fig. 3, which is in connection with derived version of schema table in Fig. 1-4, Page 26-27, Example 1),
Combined method of Han and Wang does not explicitly disclose determining whether the one or more performed actions correspond to one or more suggested actions based on the first derived dataset. However, in the same field of endeavor Dye in an analogous art disclose determining whether the one or more performed actions correspond to one or more suggested actions based on the first derived dataset (recommended action based on changes (i.e., derived dataset) of a customer insurance coverage (i.e., suggested action based on derived dataset), Fig. 3, item 304, Para [0021]).
Therefore, it would have been obvious to a person of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Han, as previously modified with Wang, with the teaching of Dye by modifying Han/Wang such that suggesting user to take appropriate action when a change in the previous or stored data is changed. The motivation for doing so would be to detect more specific information from a data provider in an efficient manner, (Dye, Para [0010]).
As per claim 24, rejection of claim 21 is incorporated,
Combined method of Han and Wang does not explicitly disclose the first set of actions comprises a first set of suggested actions; and the second set of actions comprises a second set of suggested actions. However, in the same field of endeavor Dye in an analogous art disclose the first set of actions comprises a first set of suggested actions; and the second set of actions comprises a second set of suggested actions (set of action (i.e., changes to the data in the data sources) and provide one or more recommendations (i.e., first and second recommendation), Para [0021], Fig. 3).
Therefore, it would have been obvious to a person of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Han, as previously modified with Wang, with the teaching of Dye by modifying Han/Wang such that suggesting user to take appropriate action when a change in the previous or stored data is changed. The motivation for doing so would be to detect more specific information from a data provider in an efficient manner, (Dye, Para [0010]).
As per claim 27, rejection of claim 26 is incorporated,
Combined method of Han and Wang does not explicitly disclose wherein the state of the first version of the logic comprises one or more alerts that had already been generated prior to a first time, wherein the first derived dataset comprises one or more additional alerts to be generated, and wherein the first derived dataset excludes the one or more alerts that had already been generated prior to the first time. However, in the same field of endeavor Dye in an analogous art disclose wherein the state of the first version of the logic comprises one or more alerts that had already been generated prior to a first time, wherein the first derived dataset comprises one or more additional alerts to be generated, and wherein the first derived dataset excludes the one or more alerts that had already been generated prior to the first time (notifying the customer (i.e., generating alert) when source data changes or updated (i.e., first version of the logic), Para [0021], Fig. 3).
Therefore, it would have been obvious to a person of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Han, as previously modified with Wang, with the teaching of Dye by modifying Han/Wang such that suggesting user to take appropriate action when a change in the previous or stored data is changed. The motivation for doing so would be detecting more specific information from a data provider in an efficient manner, (Dye, Para [0010]).
As per claim 28, rejection of claim 21 is incorporated,
Combined method of Han and Wang does not explicitly disclose generating an alert comprising a notification of the one or more second differences between the first set of actions and the second set of actions. However, in the same field of endeavor Dye in an analogous art disclose generating an alert comprising a notification of the one or more second differences between the first set of actions and the second set of actions (triggering alert when a change is detected, Para [0021], [0028]).
Therefore, it would have been obvious to a person of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Han, as previously modified with Wang, with the teaching of Dye by modifying Han/Wang such that suggesting user to take appropriate action when a change in the previous or stored data is changed. The motivation for doing so would be detecting more specific information from a data provider in an efficient manner, (Dye, Para [0010]).
As per claims 34 and 37,
claims 34 and 37are system claims corresponding to method claims 23-24 and 28 respectively and rejected under the same reason set forth to the rejection of claims 23-24 and 28 above.
13. Claims 31 and 39 are rejected under 35 U.S.C. 103 as being unpatentable over “Schema versioning and database conversion techniques for bi-temporal databases”, Han-Chieh Wei and Ramez Elmasri; Department of Computer Science and Engineering, The University of Texas at Arlington, 200, herein after “Han”, in view of Wang et al (US 2014/0178886 A1), as applied to claim 21 and 32 above and further in view of Schneider et al (US 10,956,132 B1).
As per claim 31, rejection of claim 21 is incorporated,
Combined method of Han and Wang does not explicitly disclose displaying, via a graphical user interface (GUI), a first graphical representation of a first scenario that provides an association between the first version of the datasets, the first version of the logic and the first derived dataset, the first graphical representation comprising a first graph that includes a first node representing the first version of the dataset, and a second node representing the first derived dataset; and displaying via the GUI, a second graphical representation of a second scenario that provides an association between the second version of the dataset, the second version of the logic and the second derived dataset, the second graphical representation comprising a second graph that includes a third node representing the second version of the dataset, and a fourth node representing the second derived dataset. However, in the same field of endeavor Schneider in an analogous art disclose displaying, via a graphical user interface (GUI), a first graphical representation of a first scenario that provides an association between the first version of the datasets, the first version of the logic and the first derived dataset, the first graphical representation comprising a first graph that includes a first node representing the first version of the dataset, and a second node representing the first derived dataset (association between first and derived version in a tree structure with node, Page 48, Page 49, Fig. 16-17), displaying via the GUI, a second graphical representation of a second scenario that provides an association between the second version of the dataset, the second version of the logic and the second derived dataset, the second graphical representation comprising a second graph that includes a third node representing the second version of the dataset, and a fourth node representing the second derived dataset (association between different versions of dataset in a tree structure with plurality of nodes, Page 48, Page 49, Fig. 16-17).
Therefore, it would have been obvious to a person of the ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Han, as previously modified with Wang, with the teaching of Schneider by modifying Han/Wang such that versions of data are displayed as a graph with nodes. The motivation for doing so would be detecting a dataset and transform it with the new set of data for optimization and cost minimization, (Schneider, column 15, line 40-50).
As per claim 39,
Claim 39 is the system claims corresponding to method claim 31 respectively and rejected under the same reason set forth to the rejection of claim 31 above.
Response to Arguments
14. Applicant’s arguments, filed on June 22, 2026, with respect to the rejection(s) of claim 21-40 have been fully considered but they are not deemed to be persuasive.
In response to applicant’s argument in page 8-12, regarding 101 rejections, applicant argued that, amended claim 21 is directed to a technical solution to solve the technical problem of how to analyze and operate on datasets … Claim 21 recites, in part, "generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset". At least the above limitations cannot be practically performed in the human mind.
Examiners disagree and respectfully response that, amended limitation of claim 1, generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset can be done using a human mind alone or with aid of pen and paper. Examiner Broadest reasonable interpretation: a data transformation logic is just input/output or any interaction with the data. For example: a dataset or a table in a database which existed before (i.e., historical data) we can call it the first version of data. A user can access such historical dataset or table and do some insertion, or addition or deletion or change or modification or any other data transformation logic on that data, will create a second version of data. If the user accesses the same dataset or table at a later date and time and do some more interaction with that data, it eventually will create second or third or fourth version of data and second or third or fourth version or transformation logic. This kind of interaction with the data or dataset can easily be done using human brain or with aid of pen and paper. Therefore, this limitation can be performed in human mind. Therefore, amended claim 21 fall into the grouping of mental process.
Claim 21 have 2 additional limitation determining one or more first differences between the first derived dataset and second derived dataset by comparing the first derived dataset to the second derived dataset; and determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions. These limitations also can be performed using the human brain alone or with the aid of pen and paper. Examiner Broadest reasonable interpretation
Let’s look at a real-life scenario. Say for example a user has a table with 5 columns in it, Name, address, DOB, SSN and Phone number, respectively. The user created this table in January of 2026. This is the first version of data with first interaction logic. Two months later in April of 2026, the user accesses this table (now this the users previous or historical data) and added two more columns named as department and salary. This addition of these two columns will produce a second version of table which was created in January. And this addition of two columns is the second data transformation logic because I interacted on the first version of the table.
Then, when the user presents these two tables on a piece of paper or on a computer screen, the user can see the difference clearly between the first and second version of table. The user can compare it with first version and second version and see the difference in that first version of the table has 5 columns, and second version of the table has 7 columns. Second version of the derived from first version of the table, etc...
This can easily be done using the human brain alone or with the aid of pen and paper.
Therefore, these limitations can be performed in human mind. Therefore, amended claim 21 fall into the grouping of mental process.
In response to applicant’s argument in page 12-13, regarding 103 rejections, applicant argued that cited references collectively or individually do not disclose, teach or suggest at least some limitations recited in claim 21. … Han further fails to disclose "generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset" as recited in claim 21.
Examiners disagree and respectfully response that, Both Han and Wang alone or in combination teaches every limitation of claim 21. Please see the response analyzation in section 101 response above.
Han teaches generating a second derived dataset associated with a second set of actions by at least applying a second version of the data transformation logic to the second version of the dataset (second version of the dataset by adding Bonus, Phone (i.e., second set of action by applying second version of data transformation logic) which is the added data not included in the first version of the dataset, Fig. 1-4, Page 26-27, Example 1), Page, 23, line 1-10, Page 24, line 6-24, Page 30, section 4), Examiner Broadest reasonable interpretation: a data transformation logic is just input/output or any interaction with the data. For example: a set of data which existed before (i.e., historical data) we can call it the first version of data. A user can access such historical data and do some insertion, or addition or deletion or change or modification or any other data transformation logic on that data will create a second version of data. If the user access the same data at a later date and time and do some more interaction with that data, it eventually will create second or third or fourth version of data and second or third or fourth version or transformation logic.
Wang teaches determining one or more first differences between the first derived dataset and second derived dataset by comparing the first derived dataset to the second derived dataset (comparing first set of result and second set of result (i.e., first derived dataset and second derived dataset), Fig. 7, item 52, 55, 56, 57, Fig. 8, item 58-63, Fig. 10, item 206, Para [0009], [0151]), determining one or more second differences between the first set of actions and the second set of actions based on the one or more first differences, wherein the one or more differences include an action applied to the second version of the dataset being in the second set of actions and the action not in the first set of actions (by comparing the first and second datasets and evaluating the differences between datasets and actions, Para [0163], [0164], [0170], [0202], [0203]), differences includes action on different sets of tissue samples (i.e., different version of dataset) which not in the first set of action or second set of action, Para [0476] – [0477], [0458]),
Please see the response analyzation in section 101 response above.
Examiner broadest reasonable interpretation: Fig. 7, item 57 teaches evaluating the effect of the action on the subject based on the set of changes between the first and second sets of results. Here, Wang teaches evaluating the effect of action on the set of changes (i.e., differences between more than one actions). When a user or a person evaluates two or more sets of data samples or two or more set of data result, that user obviously see the differences in action and results on those datasets or data sample. See also Fig. 8, item 58-63, Fig. 11A, 12A, Fig. 21, item 901-907, Para [0009].
Beside Wang, Dye reference cited for dependent claim also reasonably teaches this argues limitation. According to applicant’s specification Para [0021], [0052] and [0053], applicants described at hand dataset, which is used to apply logic to determine suggested action or notification. This at hand dataset changes or updates retroactively (note: retroactive data is a past or previous or historical data which can change many times as needed). Accordingly, Dye also teaches changes to a party’s or customer insurance profile (i.e., dataset) which changes retroactively as need or as required, (Para [0029] – [0030], Fig. 3. Examiner broadest reasonable interpretation: Whenever a change made to the customer profile, a second or third version of data is created and whatever changes is made to the profile (i.e., first action, second action) can evaluate or compare with different version and different action (i.e., logic). For example, adding a new child to their existing coverage will be an action taken to first dataset where new child is not in the first dataset (i.e., existing coverage). (Para [0022], [0041]), or elimination of a coverage will be another action to the profile or initial dataset, and the customer can determine the differences (i.e., first difference, second difference based on the action taken, such as addition elimination) in their quote.
Therefore, examiner firmly believe that Han in view of Wang or Dye alone or in combination reasonably teaches the argued limitation and claim 21, 32 and 40 as claimed.
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/MOHAMMED R UDDIN/Primary Examiner, Art Unit 2167
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