DETAILED ACTION
This office action is in response to the application filed on November 27, 2023.
Claims 1-20 are pending and have been examined. Claims 1-20 are rejected.
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 .
Claim Rejections - 35 USC § 102
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 (i.e. changing from AIA to pre-AIA ) 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 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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 4-9, 11-16, and 18-20 are rejected under 35 U.S.C. 103 as being anticipated by Doddi et al., (Patent Application No. US10262271B1 filed on February 14, 2018, hereinafter “Doddi”).
With respect to Claims 1, 8, and 15:
Doddi teaches:
“A computer-implemented method, comprising: presenting, on a display of a computing device, a graphical user interface for creating a pipeline to transform data from a first format to a second format, (Column 2, Lines 32-40 recite a graphical user interface implementing a workflow module system. Column 4, Lines 66-67 and Column 5, Lines 1-3 recite the existence of multiple layers (a pipeline) within the workflow platform. Column 2, Lines 19-27 further recite how the workflow module processes the data from the collector module before the training module trains one or more data analytics models using the inputted processed data, akin to data being transformed from a first format to a second format.)
wherein the graphical user interface comprises an interactive workspace and a logical entity library, (Column 6, Lines 26-30 recite a graphical user interface in which a user can build out a project work flow for a project, where the interface includes a toolbar consisting of a variety of buttons used to initiate various functional modules represented by different processing nodes within the project workflow (interactive workspace and a logical entity library).)
wherein the pipeline comprises two or more logical entities, (Column 6, Lines 33-37 lists eight different types of processing nodes available within the workflow system (pipeline comprises two or more logical entities).)
and wherein each logical entity in the logical entity library comprises at least one of a data processing node, a debugging node, or an administrative node;” (Column 2, Lines 32-35 recite how the workflow system implements a series of tasks through processing nodes (logical entities) available as options from the toolbar of selectable node types (logical entity library) through the graphical user interface, where each node performs a discrete operation on the data, akin to at least one of a data processing node.)
“for each logical entity in the pipeline: receiving, via the graphical user interface of the computing device, information identifying a logical entity from the logical entity library;” (Column 6, Lines 26-30 recite a graphical user interface in which a user can build out a project work flow for a project, where the interface includes a toolbar consisting of a variety of buttons used to initiate various functional modules represented by different processing nodes within the project workflow. Column 7, Lines 34-39 further recite an example of the graphical user interface receiving information when a logical entity from the logical entity library is identified, where selecting the trainer button from the toolbar initiates a trainer node that trains model parameters based on the imported processed data.)
“receiving, via the graphical user interface of the computing device, information identifying a location within the interactive workspace for the logical entity;” (Column 2, Lines 35-40 recite a graphical user interface used to construct and present a directed acyclic graph (DAG) that includes tasks represented by vertices from the DAG and possible paths of data represented as edges in the DAG, meaning the user can arrange and organize processing nodes within an interactive workspace to create a workflow process, which inherently involves the system’s graphical user interface receiving information identifying where each processing node (logical entity) is positioned (location) within the workspace.)
“and receiving, via the graphical user interface of the computing device, information identifying a configuration corresponding to the logical entity;” (Column 4, Lines 50-55 recite how the workflow platform contains a collector node (logical entity) which when selected from the toolbar displayed through the graphical user interface, can implement data collection tasks connecting to one or more data sources. Column 7, Lines 34-39 further recite a trainer node from the toolbar that initiates training of model parameters based on the imported processed data. These are examples of how each processing node (logical entity) has a specific function or configuration it performs, which inherently means the appropriate configuration information must be sent to the specific node, such as a collector node requiring data source information.)
“visually representing, via the graphical user interface of the computing device, a graphical connection between each logical entity in the pipeline and at least one additional logical entity in the pipeline, wherein the graphical connection indicates a flow of data in the pipeline;” (Column 2, Lines 35-40 recite a graphical user interface used to construct and present a directed acyclic graph (DAG) that includes tasks represented by vertices from the DAG and possible paths of data represented as edges in the DAG (graphical connection between each logical entity in the pipeline and an additional logical entity in the pipeline, indicating a flow of data).)
“transforming, by the computing device, data from the first format to the second format to produce transformed data based at least in part on the two or more logical entities comprising the pipeline.” (Column 2, Lines 32-35 recite how the workflow module system implements a series of tasks which each perform a discrete operation on the data, include data filtering, data aggregation, and data normalization before the data is transformed into processed data to be inputted into an analytics model (transforming data from a first format to a second format to produce transformed data.) Column 2, Lines 59-67 and Column 3, Lines 1-11 further recite the workflow steps (pipeline) and processing nodes (logical entities) that are used to facilitate the transformation of the data.)
With respect to Claim 2, 9, and 16:
Doddi teaches:
“wherein visually representing the graphical connection between each logical entity further comprises: visually representing, via the graphical user interface of the computing device, two or more graphical connections between a logical entity in the pipeline and at least two additional logical entities.” (Column 2, Lines 35 – 40 recite a graphical user interface used to construct and present a directed acyclic graph (DAG) that includes tasks represented by vertices from the DAG and possible paths of data represented as edges in the DAG. Column 6, Lines 27 – 30 further recite an interface including a toolbar having a series of button to initiate various functions represented by processing nodes which are organized as a DAG. Overall, this creates a visual representation of two or more graphical connections (DAG’s paths of data represented as edges) between workflow nodes (logical entities in the pipeline).)
With respect to Claims 4, 11, and 18: Doddi teaches:
“wherein presenting the graphical user interface comprises: accessing, by the computing device, the logical entity library;” (Column 6, Lines 26-30 recite a graphical user interface in which a user can build out a project work flow for a project, where the interface includes a toolbar consisting of a variety of buttons that can be used to access various functional modules represented by different processing nodes within the project workflow (accessing a logical entity library).)
“and registering, by the computing device, the logical entity library with the graphical user interface.” (Column 6, Lines 26-30 recite a graphical user interface in which a user can build out a project work flow for a project, where the interface includes a toolbar consisting of a variety of buttons that can be accessed to initiate various functional modules represented by different processing nodes within the project workflow. It would be inherently understood that making the processing nodes within the project workflow available through a toolbar presented through the graphical user interface means the logical entity library connection would have to be acknowledged (registered) by the graphical user interface.)
With respect to Claims 5, 12, and 19:
Doddi teaches:
“wherein the first format comprises unprocessed data and the second format comprises input to a machine learning model.” (Column 5, Lines 3-17 recite the implementation of data collection tasks by connecting to one or more data sources using a collector service, where the data sources may be static, historical data (first format comprises unprocessed data). Column 2, Lines 19-27 recite how the workflow module processes the data from the collector module before the training module trains one or more data analytics models using the inputted processed data (second format comprises input to a machine learning model).)
With respect to Claim 6:
Doddi teaches:
“training, by the computing device, a machine learning model on the transformed data in the second format.” (Column 2, Lines 19-27 recite how the workflow module processes the data (transformed data in the second format) from the collector module before the training module trains one or more data analytics models (training a machine learning model) using the inputted processed data.)
With respect to Claim 7:
Doddi teaches:
“storing, by the computing device, the transformed data in a memory of the computing device.” (Column 4, Lines 66-67 and Column 5, Lines 1-3 recite the existence of multiple layers within the data platform, including a storage layer. Column 6, Lines 1-2 recite how the system stores its data within the storage layer, which inherently includes any transformed data (storing the transformed data in a memory of the computing device.)
With respect to Claims 13 and 20:
Due to containing similar claim language as Claim 6, refer to the 102 rejection for Claim 6 above.
With respect to Claim 14:
Due to containing similar claim language as Claim 7, refer to the 102 rejection for Claim 7 above.
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 non-obviousness.
Claims 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Doddi et al., (Patent Application No. US10262271B1 filed on February 14, 2018, hereinafter “Doddi”), in view of Altintas et al., (Non-patent literature published on June 21, 2004, hereinafter “Altintas”).
With respect to Claims 3, 10, and 17:
Doddi teaches:
“wherein the at least two additional logical entities comprise a data processing node and a debugging node.” (Column 6, Lines 31 – 37 recite a project workspace in which processing nodes are arranged as an acyclic directed graph according to the desired workflow process, comprised of a variety of node types that perform operations on data akin to data processing nodes.)
Doddi does not appear to explicitly disclose:
“wherein the at least two additional logical entities comprise a data processing node and a debugging node.”
However, Altintas teaches:
“wherein the at least two additional logical entities comprise a data processing node and a debugging node.” (Page 1, Section 2 recites how the Kepler scientific workflow system builds upon the Ptolemy II system, which means Kepler can perform static and dynamic type checking on workflow and data before and during runtime execution, akin to a debugging node.)
It would have been obvious to a PHOSITA before the effective filing date of the present application to implement Claims 3, 10, and 17 that utilized the teachings of Doddi and the teachings of Altintas, which are both in the same field of invention. A PHOSITA would have been motivated to build Altinta’s debugging functionality (debugging node) into Doddi’s workflow data system in order to improve the overall debugging process and create the ability to identify workflow errors and troubleshoot them, which in turn improves the maintainability and reliability of the workflow data system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Vibha Bhat whose telephone number is (571)-272-7091. The examiner can normally be reached on Monday – Thursday from 8:00 AM to 5:00 PM EST and every other Friday from 8:00 AM to 4:00 PM EST.
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/Vibha Bhat/Examiner
Art Unit 2142
/Mariela Reyes/Supervisory Patent Examiner, Art Unit 2142
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