DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed on 06/03/2026 has been entered. Claim(s) 1-20 is/are now pending in the application. Applicant's amendments have addressed all informalities as previously set forth in the non-final action mailed on 03/12/2026.
Claim Rejections - 35 USC § 103
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.
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.
Claim(s) 1-3, 5-9, 12-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over BOWEN ET AL. (US 20140164444 A1) (hereinafter “BOWEN”) in view of ZBILJIC (US 20170318119 A1).
With respect to Claim(s) 1, 13, 20, BOWEN teaches ‘systems and software that provide a high-performance, extensible file format and web API for remote data access and a visual interface for data viewing, query, and analysis. The described system supports can support storage of raw spectroscopic data such as neural recording data, MSI data, metadata, and derived analyses in a single, self-describing format that may be compatible by a large range of analysis software.’ and the BRI of:
A support apparatus for a scientific instrument (See, e.g., ¶ ABSTRACT; See also, e.g., Fig(s). 17),
the support apparatus comprising logic configured to:
transfer portions of a data structure acquired with one or more detectors of the scientific instrument to a client device (See, e.g., ¶ 0040, 0043, 0049; See also, e.g., Fig(s). 1B, 17, 18),
the data structure being stored in a first data repository connected to the first logic via a network (See, e.g., ¶ 0040, 0043, 0049; See also, e.g., Fig(s). 1B, 17, 18),
the portions being identified to the first logic in a sequence of data requests received from the client device (See, e.g., ¶ 0040, 0043, 0049; See also, e.g., Fig(s). 1B, 17, 18);
identify parts of the data structure based on at least one of a data-access pattern in the sequence of data requests and a buffer size for a second data repository locally connected to the first logic (See, e.g., ¶ 0071, 0077, 0081, 0112, 0125, 0268, 0284; See also, e.g., Fig(s). 6A-6C);
and
download the parts from the first data repository to the second data repository (See, e.g., ¶ 0040, 0043, 0049; See also, e.g., Fig(s). 1B, 17, 18),
accessing a requested portion of the data structure in the parts downloaded to the second data repository (See, e.g., ¶ 0040, 0043, 0049; See also, e.g., Fig(s). 1B, 17, 18).
However, BOWEN is lacking the explicit language of:
switch a data transfer path for the client device from being end-connected to the first data repository to being end-connected to the second data repository when requested.
ZBILJIC teaches ‘A method for stream-processing biomedical data includes receiving, by a file system on a computing device, a first request for access to at least a first portion of a file stored on a remotely located storage device. The method includes receiving, by the file system, a second request for access to at least a second portion of the file. The method includes determining, by a pre-fetching component executing on the computing device, whether the first request and the second request are associated with a sequential read operation. The method includes automatically retrieving, by the pre-fetching component, a third portion of the requested file, before receiving a third request for access to least the third portion of the file, based on a determination that the first request and the second request are associated with the sequential read operation’ and the BRI of:
switch a data transfer path for the client device from being end-connected to the first data repository to being end-connected to the second data repository when requested (See, e.g., ¶ 0034, 0038; See also, e.g., Fig(s). 1A-3B).
It would have been obvious to one ordinary skill in the art, at the time before the effective filing date of the claimed invention, to modify BOWEN to include switch a data transfer path for the client device from being end-connected to the first data repository to being end-connected to the second data repository when requested.
One of ordinary skill in the art would have been motivated to modify BOWEN because it would be beneficial to stream-process scientific data. Further, it would be obvious to combine prior art elements according to known methods to yield predictable results, simply substitute one known element for another to obtain predictable results, use known techniques to improve similar devices in the same way, and/or apply a known technique to a known device ready for improvement to yield predictable results.
With respect to Claim(s) 2, 14, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the scientific instrument comprises at least one of
a mass spectrometer and a chromatography system (See, e.g., ¶ 0007).
With respect to Claim(s) 3, 15, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
identify the parts of the data structure using a predictive algorithm configured to detect the data-access pattern in a space defined by one or more attributes selected from the group of attributes consisting of:
a scan order in a sequence of mass-spectrometer scans, a sequence of mass ranges, relative timing of a mass-spectrometer scan and a chromatographic peak in a corresponding chromatogram, and a chemical compound library (See, e.g., ¶ 0058, 0086).
With respect to Claim(s) 5, 16, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
ZBILJIC further teaches the BRI of:
perform a background download to download the parts, the background download occurring concurrently with a transfer via the first logic of one or more of the portions of the data structure from the first data repository to the client device (See, e.g., ¶ 0096).
It would have been obvious to one ordinary skill in the art, at the time before the effective filing date of the claimed invention, to modify BOWEN to include perform a background download to download the parts, the background download occurring concurrently with a transfer via the first logic of one or more of the portions of the data structure from the first data repository to the client device.
One of ordinary skill in the art would have been motivated to modify BOWEN because it would be beneficial to stream-process scientific data. Further, it would be obvious to combine prior art elements according to known methods to yield predictable results, simply substitute one known element for another to obtain predictable results, use known techniques to improve similar devices in the same way, and/or apply a known technique to a known device ready for improvement to yield predictable results.
With respect to Claim(s) 6, 17, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
dynamically select a suitable data reader from a plurality of data readers based on the data transfer path (See, e.g., ¶ 0032, 0051, 0070, 0075, 0081, 0101, 0112, 0272, 0276).
With respect to Claim(s) 7, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the plurality of data readers
includes:
a first data reader suitable for reading from the first data repository (See, e.g., ¶ 0032, 0051, 0070, 0075, 0081, 0101, 0112, 0272, 0276);
and
a different second data reader suitable for reading from the second data repository (See, e.g., ¶ 0032, 0051, 0070, 0075, 0081, 0101, 0112, 0272, 0276).
With respect to Claim(s) 8, 18, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the plurality of data readers is implemented as a plurality of application plugins (See, e.g., ¶ 0032, 0051, 0070, 0075, 0081, 0101, 0112, 0272, 0276).
With respect to Claim(s) 9, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the first data repository is selected from the group consisting of:
a web-based object storage, an enterprise data-storage platform, a micro service platform, a network-attached storage, and a storage area network (See, e.g., ¶ ABSTRACT;).
With respect to Claim(s) 12, 19, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the data structure has a binary format suitable for recording, packaging, and transfer of experimental data acquired via multiple ones of the detectors of the scientific instrument (See, e.g., ¶ 0070).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over the cited reference(s) of the parent claim(s) in view of COHN ET AL. (US 20230161743 A1) (hereinafter “COHN”).
With respect to Claim(s) 4, the cited reference(s) of the parent claim(s) teaches the BRI of the parent claim(s).
BOWEN further teaches the BRI of:
the data structure has a size in a range between 1 GB and 100 GB (See, e.g., ¶ 0099)
and
includes data from pluralities of mass spectrometer scans and detector channels (See, e.g., ¶ 0007).
However, BOWEN is lacking the explicit language of:
data corresponding to a single analyte injection.
COHN teaches ‘Exemplary embodiments provide computer-implemented methods, mediums, and apparatuses configured to upload data stored in a data storage ecosystem to a cloud-based storage service. A database in the data storage ecosystem may store results sets from an analytical chemistry system. The results sets may be stored in a first model structure implemented by a library structure. An uploader may incorporate the library structure and may include logic to use the library structure to transform the results sets from first model structure into a second model structure suitable for use in a relational data store in the cloud-based storage system. By implementing the library structure in the uploader, the uploader can be decoupled from the data storage ecosystem. This allows the uploader to function without some of the overhead used by the data ecosystem, provide faster data uploads, and to automatically generate derived information for the results sets’ and the BRI of:
data corresponding to a single analyte injection (See, e.g., ¶ 0007).
It would have been obvious to one ordinary skill in the art, at the time before the effective filing date of the claimed invention, to modify BOWEN to include data corresponding to a single analyte injection.
One of ordinary skill in the art would have been motivated to modify BOWEN because it would be beneficial to improve an analytical ecosystem. Further, it would be obvious to combine prior art elements according to known methods to yield predictable results, simply substitute one known element for another to obtain predictable results, use known techniques to improve similar devices in the same way, and/or apply a known technique to a known device ready for improvement to yield predictable results.
Allowable Subject Matter
Claim(s) 10, 11 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Allowable Subject Matter (over Prior Art)
The following is a statement of reasons for the indication of allowable subject matter over prior art:
None of the cited prior art alone or in combination provides motivation to explicitly teach:
in response to a subsequent data request received from the client device,
obtain an availability status for a subsequent portion of the data structure specified in the subsequent data request;
transfer the subsequent portion of the data structure to the client device from the second data repository when the availability status is “available”;
and
transfer the subsequent portion of the data structure to the client device from the first data repository when the availability status is “not available.”
of claim(s) 10;
switch the data transfer path in response to a message from the third logic reporting a download completion event
of claim(s) 11.
Response to Arguments
Applicant's argument(s)/remark(s), see page(s) 8, filed 06/03/2026, with respect to the 112 rejection(s) has/have been fully considered.
-Applicant states
“III. Rejections under 35 U.S.C. & 112
In the Office action dated March 12, 2026 (the "Office Action"), claims 1-20 stand rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or joint inventors regards as the invention. Specifically, the Examiner contends that "it is unclear what the structural difference between 'a data storage device' and 'a data storage' is." (Office Action, p. 3).
Applicant has amended the claims in the present response to recite a "first data repository" and a "second data repository" to distinguish between a "data storage" and a "data storage device," respectively. Withdrawal of this rejection is respectfully requested.”.
Examiner agrees with the underlined argument(s)/remark(s).
Said rejection(s) has/have been withdrawn.
Applicant's argument(s)/remark(s), see page(s) 8-11, filed 06/03/2026, with respect to the art rejection(s) has/have been fully considered.
-Applicant states
“IV. Rejections under 35 U.S.C. & 102
In the Office Action, claims 1-20 stand rejected under 35 U.S.C. § 102 as allegedly being anticipated by U.S. Publication No. 2023/0161743 ("Cohn").
a. Independent Claim 1
Independent claim 1 recites, in part, "second logic configured to identify parts of the data structure based on at least one of a data-access pattern in the sequence of data requests and a buffer size for a second data repository locally connected to the first logic; and third logic configured to download the parts from the first data repository to the second data repository." In rejecting each claim element of independent claim 1, the Examiner cites to FIGS. 1-4 and 10- 12 of Cohn without providing specific citations for any individual claim element (Office Action, p. 5).
Applicant respectfully disagrees with this rejection of claim 1. FIGS. 1-4 and 10-12 of Cohn describe a system in which data is uploaded from a local data source to a cloud-based storage system. Cohn does not teach or suggest downloading identified parts of a data structure.
For example, FIG. 3 of Cohn illustrates a system architecture in which data flows from a local data service 326 through an uploader 314 to a cloud storage service 332 for visualization.
The depicted system provides no mechanism for returning or downloading portions of the stored data back to a locally connected data storage repository for subsequent access and instead treats the cloud storage system as the primary repository for accessing and analyzing the data.
Further, in FIG. 10 of Cohn, an uploader transfers "part of the one or more results sets to the cloud-based storage service" (at block 1014) and subsequently stores the results sets (i.e., data) with the cloud-based storage service (at block 1024). In addition, FIG. 11 of Cohn illustrates client interaction with the data, where data is received (at block 1102), automatically uploaded (at block 1104), and used to generate visualizations (at block 1114). Neither FIG. 10 nor FIG. 11 teach or suggest downloading identified portions of data to a locally connected data storage repository. The remaining figures do not provide any additional evidence to support any downloading of relevant parts of a data structure. For example, FIGS. 2A-2B depict a data ecosystem that enables uniform access and processing of heterogeneous instrument data. FIG. 4 depicts data being transferred from a local data source or backup system to a cloud storage service via an uploader. FIG. 12 illustrates a system architecture in which client devices access data stored on a data server via the web server using network communications.
Accordingly, any "data structures" in discussed in Cohn are not processed to identify parts to download to a locally connected data storage repository. Therefore, Cohn fails to teach or suggest logic "configured to identify parts of the data structure based on at least one of a data-access pattern in the sequence of data requests and a buffer size for a second data repository locally connected to the first logic; and third logic configured to download the parts from the first data repository to the second data repository," as recited in independent claim 1.
Similarly, Cohn does not teach or suggest "wherein the first logic is configured to switch a data transfer path for the client device from being end-connected to the first data repository to being end-connected to the second data repository when a requested portion of the data structure is in the parts downloaded to the second data repository via the third logic," also recited in independent claim 1.
Cohn is fundamentally directed to eliminating dependence on local data ecosystems by uploading analytical instrument data into a centralized, cloud-based storage and analytics environment for subsequent access. As explained in Cohn, "because the data is stored in a relational data store at the cloud-based storage service, it may be faster to access the data stored in the cloud service. Relational databases are generally optimized to perform data reads, and in this context the system will typically be performing a large number of reads from the database for a given piece of data. By using a relational database, data access can be optimized across the large amounts (e.g., many petabytes) of data that may need to be analyzed in an analytical chemistry experiment" (Cohn, paragraph [001S]). Cohn treats local access through a data ecosystem as something to be avoided and frames cloud-resident storage as the optimized and authoritative access point for clients. Therefore, switching between data storage repositories would run counter to Cohn's objective of eliminating local ecosystem dependency and would undermine Cohn's intended purpose of providing a centralized cloud-based system for data storage and access.
Therefore, Cohn fails to teach or suggest the above noted limitations of claim 1. Thus, claim 1 and the claims that depend from claim 1 are allowable for at least the above noted reasons. Claim 13 recites similar subject matter as claim 1. Therefore, claim 13 and the claims that depend from claim 13 are also allowable for at least the same reasons as claim 1.”.
Examiner agrees with the underlined argument(s)/remark(s).
Said rejection(s) has/have been withdrawn.
After further search and consideration, Examiner is making new rejection(s) not necessitated by amendment(s). Therefore, this will be a 2nd non-final.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAYMOND NIMOX whose telephone number is (469)295-9226. The examiner can normally be reached Mon-Thu 10am-8pm CT.
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RAYMOND NIMOX
Primary Examiner
Art Unit 2857
/RAYMOND L NIMOX/Primary Examiner, Art Unit
Prosecution Insights