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 Objections
Claim 14 is objected to because of the following informalities: Claim 14 recites "The non-transitory computer-readable storage medium of claim 3...;" however claim 3 does not recite a non-transitory computer-readable storage medium. Instead, claim 3 is directed to a method. Claim 14 as written must depend on a claim directed to a non-transitory computer-readable storage medium. Appropriate correction is required.
Claim 16 objected to because of the following informalities: Claim 16 recites "...wherein parsing the geospatial data wherein parsing the geospatial data further..." Claim 16 has a typ twice in a row. Appropriate correction is required.
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.
Claims 1-4, 7-14, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Shipes et al. (US 20230024459 A1; hereinafter Shipes) in view of Peng et al. (US 20240037823 A1; hereinafter Peng).
Regarding claim 20, Shipes teaches a system comprising: one or more processors (“Data image generation system 100 includes processors and/or servers,” (page 2, para [0041]-[0043]).);
a non-transitory computer-readable storage medium storing computer program instructions ("FIG. 29 illustrates a block diagram of one embodiment of an encompassing computing environment. FIG. 29 illustratively comprises a general-purpose computing device configured as a computer 2910. Computer 2910 may include a variety of components that are configured to facilitate the functionality of a distribution system, for example. Computer 2910 may include a processing unit 2920, a system memory 2930 and a communication bus 2921 that may facilitate communication between the various components," (page 10, para [0129]; Fig 29).
"Computer 2910 may comprise a variety of computer readable media... computer readable media may comprise computer storage media and communication media. Computer storage media is different from, and does not include, a modulated data signal or carrier wave. It includes hardware storage media including both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data," (page 10, para [0130] - [0131]; Fig 29).) for providing a structured data transmission comprising a plurality of structured geospatial data tiles, the computer-program instructions, when executed by one or more processors, causing the one or more processors ("Interface 10, as shown, includes a plurality of tiles 12 that segment the data across the larger area of interface 10. Additionally, tiles 12 can include the data for sub areas defined by a respective tile. The resolution of tiles 12 can be determined based on the geographic granularity of the data available or data requested.
In one example, tiles 12 are pre-generated images from a server. These images are generated based on a display scheme to illustrate a variety of weather characteristics. For example, an image for precipitation can include white for snow, blue for light rain, and purple for heavy rain, while areas without precipitation could be transparent or include a rendering of the geographic area to simulate transparency. In operation, a user device receives these pre-generated images (corresponding to tiles 12) and displays them as generated with minimal, if any, processing. If a user requests a different set of data, then a different set of tiles 12 are generated by the server and delivered to the user device for display. For example, colored-coded high pressure and low-pressure images are generated at the server and sent to the user device. A disadvantage to this approach is that the server generates images for each characteristic, and the user device that displays the image generated by the server is limited for zooming by the resolution of the image. This consequently increases the amount of data sent to the user, which can be problematic based on the bandwidth of the network," (page 2, para [0037]-[0039]; page 3, para [0054]). The tiles 12 read on structured data tiles.) to:
access geospatial data from one or more network systems ("Data image generation system 100 communicates with other components in environment 200 through communication component 150. Communication component 150 can communicate with computing device 460, data sources 202, and other components 201 using a variety of different protocols on a variety of different networks including wide area network, a local area network, Bluetooth, Wi-Fi, near field location, etc. Data image generation system 100 also receives the request for data from computing device 460 through communication component 150. Specifically, request validation component 110 receives the request for data and validates the request. Request validation can include a variety of different factors, including syntax and format checking, user authentication, payment of processing fees, etc.," (page 2, para [0041]- [0044]).
"...the request of data may include temperature for a particular region (e.g., the Midwest)....," (page 2-3, para [0045]). Geospatial data includes temperature for a particular region.);
encode the geospatial data into structured geospatial data tiles ("...a method of generating and delivering environmental data includes receiving a request for requested data corresponding to a first environmental characteristic and a second environmental characteristic. The method includes retrieving a first set of data corresponding to the first environmental characteristic. The method includes retrieving a second set of data corresponding to the second environmental characteristic. The method includes generating an image having a first channel and a second channel. The values of the first channel correspond to the first set of data. The values of the second channel correspond to the second set of data," (page 1, para [0005]).
"...in a case where temperature and wind are requested, then temperature and wind data will be in the response. As indicated by block 342, the data can be stored in image pixel channels...," (page 4, para [0062]).
Encoding the geospatial data includes storing data in channels. Geospatial data includes temperature and wind data. The geospatial data tile comprises the generated image.) by:
parsing the geospatial data into a plurality of data types (“FIG. 3 is a flow diagram showing an example operation of requesting, generating, and delivering a data image. Operation 300 begins at block 310 where a request for environmental data is generated. As indicated by block 311, characteristics are included in the request. Some examples of characteristics can include temperature, wind, wind direction, precipitation, humidity, barometric pressure, wind chill, heat index, Ultraviolet (UV) index, etc,” (pages 3-4, para [0056]).
"Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (page 7, para [0089]).
“…data image generation system 100 accesses data sources 202 to retrieve the data that is to be incorporated in the data image. Some examples of data sources 202 include government agencies, commercial entities, user mobile devices, and other data sources 202. For example, U.S. Pat. No. 10,437,814 describes examples of various data sources 202,” (page 2, para [0041]).
“Request parsing component 112 receives the validated request from request validation component 110 and parses the request for information. The information can include, for example, the requested characteristics, requested time, requested location, requested resolution, and/or requested data source, such as that described below with respect to FIG. 10. Additionally, it is expressly contemplated that different types of information can be acquired as well. Data retrieval component 114 retrieves the data that request parsing component 112 parsed from the request. Data retrieval component 114 can utilize communication component 150 to receive the data from the various data sources 202,” (page 2, [0044]).
The data types include temperature, wind, wind direction, precipitation, etc. Shipes characteristics correspond to data types. Parsing includes organizing data into different data types and / or characteristics and / or assigning data into separate channels according to its characteristic / data type.);
for each data type of the plurality of data types, generating one or more data bands of a plurality of data bands, each data band comprising the parsed geospatial data corresponding to the data type ("Characteristic channel generation component 120 generates the channels utilizing the characteristic range definition component 116 and characteristic resolution definition component 118 output(s). For example, if a computing device 460 requests the weather for North and Central America, the temperature values can range from negative twenty-two degrees F. to one-hundred and six degrees F. In this example, each unit (e.g., 0-255 possible units in a 8-bit depth channel) in the channel is indicative of a step of 0.5° F. Characteristic channel generation component 120 generates each channel that corresponds to the characteristic that computing device 460 requests," (page 3, para [0049]).
"Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (page 7, para [0089]; Fig 9).
"...each channel represents its own characteristic...," (page 4, para [0062]).
The data types include temperature, wind, wind direction, precipitation, etc. Shipes’ characteristics correspond to data types. The data bands include Shipes’ channels.),
generate data pixels for each data band of the plurality of data bands, each data pixel of a plurality of data pixels comprising a defined number of bits of the parsed geospatial data ("Operation 300 proceeds at block 340 where the response to the request is generated. As indicated by block 341, the reciprocal data from the request is included in the response. For example, in a case where temperature and wind are requested, then temperature and wind data will be in the response. As indicated by block 342, the data can be stored in image pixel channels. For example, in a 32 bit-depth PNG image, the data can be stored as integer values in each of the red, green, blue, and alpha channels of the image, where the values in each channel can be between zero and two-hundred and fifty-five. In some examples, each channel represents its own characteristic. Additionally, in some examples, the values of a single characteristic are distributed across multiple channels. As indicated by block 343, the data can be distributed across sub images in an overall larger data image. These sub images allow for additional data to be included in the image without being limited by the number of channels in the image. As indicated by block 344, metadata corresponding to the response is generated. In some examples, the metadata is used by the client device to interpret the values in the data image. For example, the metadata can indicate which channel contains which characteristic, what range the 0-255 values cover, etc. As indicated by block 346, the response can be generated in other ways or include other data as well," (page 4, para [0062]).
"an image having 8 bits per channel can store a number in the range of 0-255 per channel," (page 6, para [0078]; Fig 9).
The data pixel comprises four channels (red, green, blue, and alpha); therefore, in the case that each channel has 8 bits, each data pixels takes up 32 bits. 32 is a defined number.),
generating a plurality of data blocks, each data block of the plurality of data blocks comprising data pixels of one or more of the data bands of the plurality of data bands ("Sub image generation component 124 generates sub images that corresponds to additional data that is requested by computing device 460, "(page 3, para [0051]-[0052]).
"...image 550 only has four color channels which by themselves cannot represent seven characteristics. Accordingly, to represent these seven characteristics, four available color bands in sub image 522-1 are used to store four of the seven characteristics (e.g., temperatures, dew point, humidity, and pressure). Then, the remaining three characteristics (e.g., wind speed latitude, wind speed longitude, and radar) can be stored in three color channels of sub image 522-2... Any combination of channels and sub-images can be utilized to increase the amount of data that the image contains," (page 5, para [0073]-[0074]).
Data block includes a sub image. Sub images 522-1 and 522-2 comprise a plurality of data blocks.), and
generating a plurality of structured geospatial data tiles (“In one example, tiles 12 are pre-generated images from a server. These images are generated based on a display scheme to illustrate a variety of weather characteristics. For example, an image for precipitation can include white for snow, blue for light rain, and purple for heavy rain, while areas without precipitation could be transparent or include a rendering of the geographic area to simulate transparency. In operation, a user device receives these pre-generated images (corresponding to tiles 12) and displays them as generated with minimal, if any, processing. If a user requests a different set of data, then a different set of tiles 12 are generated by the server and delivered to the user device for display. For example, colored-coded high pressure and low-pressure images are generated at the server and sent to the user device…," (page 2, para [0037]-[0039]).),
each structured geospatial data tile of the plurality of structured geospatial data tiles comprising one or more of the data blocks ("In one example described herein, tiles 12 include images that represent more than one characteristic or a characteristic in more than one dimension. For instance, the image can utilize the Red-Green-Blue-Alpha (RGBA) channels to store data indicative of four different characteristics. In other examples, the RGBA channels store values indicative of temperature values at several (e.g., four) different times, temperatures at different elevations, etc," (page 2, para [0037]- [0039]).
"Image generation component 130 combines the sub images (or single image) into an image of a given format..." (page 3, para [0051]- [0053]).
Data block includes a sub image. Tiles 12 include Shipes' images that comprise one or more sub images.) and
a header identifying a location of each data pixel for each data type in the one or data blocks in the structured geospatial data tile ("Metadata generation component 122 generates metadata corresponding to the data image. The metadata can include, for example, the image characteristic data format in the image, such as identifiers of the characteristics, the range of values, the geographic locations of the values, the temporal location of the values, sub image layout, etc. In one example, the metadata includes information that allows another system to interpret the values of the image. In one example, metadata generation component 122 can incorporate the metadata into the image. However, in other examples, metadata generation component 122 can generate the metadata as a separate file or package the metadata in other ways as well. FIG. 11, described below, shows an example response that also contains examples of metadata," (page 3, para [0050]; Fig 11).
"FIG. 11 is a diagram showing an example response header 1100..." (para [0087]-[0089]).
A header includes Shipes' response header and / or metadata. The location of each data pixel for each data type in the one or data blocks includes Shipe's geographic locations of values, temporal location of values, characteristic definitions, and sub image layouts.); and
provide the plurality of structured geospatial data tiles to a client device as a structured data transmission ("Image delivery component 132 packages and delivers the generated image to the requesting computing device 460. Image delivery component 132 can utilize communication component 150 through one or more networking interface protocols to deliver the image. In some examples, image delivery component 132 compresses or otherwise processes the image," (pages 3-4, para [0054]-[0056]; Fig 3).
"tiles 12 are generated by the server and delivered to the user device for display," (page 2, para [0037]-[0039]).
Client device includes user device/ requesting computing device.);
wherein the client device comprises a processing unit configured to generate visualizations of geospatial data tiles using the defined number of bits of the data pixels ("FIG. 4 is a block diagram showing an example computing device 400... Computing device 400 includes processors 402,..., a data processing component 416, ...,"(page 4, para [0064]).
"Data processing component 416 uses the parsed metadata to extract and/or interpret the raw data in the data image. Data processing component 416, in some examples, can complete decompression of the data images...
User interface generation component 418 utilizes the raw data to generate a user interface. A user interface can include a map that plots the characteristic values across a geographic area. In some examples, user interface generation component 418 includes WebGL components....," (page 5, para [0068]-[0069]).
"FIG. 13 is a flow diagram showing an example operation 1300 of receiving and rendering a data image. At block 1302, the server response is received. In this example, a data image with six sub images is shown as being received. At block 1304, the server response is processed. As illustratively shown, the six sub images are processed into 6 images. These images include a number of channels that correlate to different characteristics. The channel values are used to determine the characteristic values. At block 1306, an interface is generated. As illustratively shown, the interface represents temperatures. These temperatures were extracted from one or more of the channels from one or more of the sub images in block 1302. A graphics processing unit (GPU) of the user device creates the rendering by binding the data (e.g., from the sub image) to a texture/color palette. In some examples, the data image generation system provides any other relevant information to the GPU at the same time that is required for rendering the data, such as the color scale to map values to, matrix information about how to transform the data (map projections, positioning the output on a map, etc), and any other information of relevance," (page 7, para [0097]).
Generate visualizations includes creating a rendering. The geospatial data tile comprises a data image.).
Shipes is not relied upon teaching the data transmission is a data stream. Peng teaches data transmission is a data stream ("Various computer applications may use geospatial map data provided to a user device via streaming from a server. To reduce a data size for streaming the map data and/or for storing the map data locally on the user device, vector tiles or raster tiles of the map data may be pre-generated and upon request streamed to the user device," (page 1, para [0002])).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Peng to Shipes. The motivation would have been to “reduce a data size for streaming the map data and/or for storing the map data locally on the user device,” (page 1, para [0002]).
Regarding claims 1 and 11, they are rejected using the same citations and rationales described in the rejection of claim 20.
Regarding claim 12, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 11, wherein the defined number of bits is thirty two bits (Shipes; "Operation 300 proceeds at block 340 where the response to the request is generated. As indicated by block 341, the reciprocal data from the request is included in the response. For example, in a case where temperature and wind are requested, then temperature and wind data will be in the response. As indicated by block 342, the data can be stored in image pixel channels. For example, in a 32 bit-depth PNG image, the data can be stored as integer values in each of the red, green, blue, and alpha channels of the image, where the values in each channel can be between zero and two-hundred and fifty-five. In some examples, each channel represents its own characteristic. Additionally, in some examples, the values of a single characteristic are distributed across multiple channels. As indicated by block 343, the data can be distributed across sub images in an overall larger data image. These sub images allow for additional data to be included in the image without being limited by the number of channels in the image. As indicated by block 344, metadata corresponding to the response is generated. In some examples, the metadata is used by the client device to interpret the values in the data image. For example, the metadata can indicate which channel contains which characteristic, what range the 0-255 values cover, etc. As indicated by block 346, the response can be generated in other ways or include other data as well," (page 4, para [0062]).
"an image having 8 bits per channel can store a number in the range of 0-255 per channel," (Shipes; page 6, para [0078]; Fig 9).
The data pixel comprises four channels (red, green, blue, and alpha); therefore, in the case that each channel has 8 bits, each data pixels takes up 32 bits. 32 is a defined number.).
Regarding claim 2, it is rejected using the same citations and rationales described in the rejection of claim 12.
Regarding claim 13, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 11, wherein the geospatial data access from the one or more network systems comprises unstructured data representing one or more characteristics of an environment represented by the geospatial data (Shipes; “data image generation system 100 accesses data sources 202 to retrieve the data that is to be incorporated in the data image. Some examples of data sources 202 include government agencies, commercial entities, user mobile devices, and other data sources 202. For example, U.S. Pat. No. 10,437,814 describes examples of various data sources 202,” (page 2, para [0041]).
“Operation 300 begins at block 310 where a request for environmental data is generated. As indicated by block 311, characteristics are included in the request. Some examples of characteristics can include temperature, wind, wind direction, precipitation, humidity, barometric pressure, wind chill, heat index, Ultraviolet (UV) index, etc,” (Shipes; pages 3-4, para [0056]).
The data from data sources 202 reads on unstructured data because the data is from different data sources and the data has not yet been parsed and / or organized into data bands/ channels.).
Regarding claim 3, it is rejected using the same citations and rationales described in the rejection of claim 13.
Regarding claim 14, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 3, wherein each of the one or more characteristics correspond to a data type of the plurality of data types such that each data band comprises geospatial information describing a characteristic of the one or more characteristics using a data type of the plurality of data types (Shipes; “Characteristic channel generation component 120 generates each channel that corresponds to the characteristic that computing device 460 requests," (page 3, para [0049]).
"Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (Shipes; page 7, para [0089]; Fig 9).
"...each channel represents its own characteristic...," (Shipes; page 4, para [0062]).
The data types include temperature, wind, wind direction, etc. Shipes characteristics correspond to data types. The data bands include Shipes’ channels.).
Regarding claim 4, it is rejected using the same citations and rationales described in the rejection of claim 14.
Regarding claim 17, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 11, wherein the plurality of data types in each structured geospatial data tile comprises three data types (Shipes; "Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (page 7, para [0089]; Fig 9).
An image / tile includes three data types (temperature, wind (latitudinal velocity), wind (longitudinal velocity)).).
Regarding claim 7, it is rejected using the same citations and rationales described in the rejection of claim 17.
Regarding claim 18, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 17, wherein: geospatial data for a first data type of the plurality of data types is encoded using a first fraction of the defined number of bits in each data pixel, and geospatial data for a second data type of the plurality of data types is encoded using a second fraction of the defined number of bits in each data pixel different from the first fraction (Shipes; “FIG. 9 is a diagram showing the channels 900 of a pixel in an example data image. In one example, the data image is in a PNG image format. The PNG image format allows data storage in four color channels (red channel 902, green channel 904, blue channel 906, and alpha channel 908). The bit depth of the image can be changed to store a varying range of values per channel. For example, an image having 8 bits per channel can store a number in the range of 0-255 per channel,” (page 6, para [0078]).
"Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (Shipes; page 7, para [0089], [0096]; Fig 9). Each channel is one fraction (8 bits) of a 32-bit RGBA pixel. Each channel corresponds to a data type.).
Regarding claim 8, it is rejected using the same citations and rationales described in the rejection of claim 18.
Regarding claim 19, Shipes in view of Peng teaches the non-transitory computer-readable storage medium of claim 18, wherein: geospatial data for a third type of the plurality of data types is encoded using a third fraction of the defined number of bits in each data pixel different from both the first fraction and the second fraction (Shipes; “FIG. 9 is a diagram showing the channels 900 of a pixel in an example data image. In one example, the data image is in a PNG image format. The PNG image format allows data storage in four color channels (red channel 902, green channel 904, blue channel 906, and alpha channel 908). The bit depth of the image can be changed to store a varying range of values per channel. For example, an image having 8 bits per channel can store a number in the range of 0-255 per channel,” (page 6, para [0078]).
"Characteristic definition portions 1104 contain information indicative of the characteristic corresponding to one of the channels. In this instance, the first characteristic is temperature and is stored in the red channel. The second characteristic is wind (latitudinal velocity) and is stored in the green channel. The third characteristic is wind (longitudinal velocity) and is stored in the blue channel," (Shipes; page 7, para [0089], [0096]; Fig 9).
Each channel is one fraction (8 bits) of a 32-bit RGBA pixel. Each channel (including the red channel, the green channel, and the blue channel) corresponds to a data type (temperature, wind (latitudinal velocity), wind (longitudinal velocity)).).
Regarding claim 9, it is rejected using the same citations and rationales described in the rejection of claim 19.
Regarding claim 10, Shipes in view of Peng teaches the method of claim 1, further comprising rendering each structured geospatial data tile of the plurality of structured geospatial data tiles for visualization on the client device ("FIG. 13 is a flow diagram showing an example operation 1300 of receiving and rendering a data image. At block 1302, the server response is received. In this example, a data image with six sub images is shown as being received. At block 1304, the server response is processed. As illustratively shown, the six sub images are processed into 6 images. These images include a number of channels that correlate to different characteristics. The channel values are used to determine the characteristic values. At block 1306, an interface is generated. As illustratively shown, the interface represents temperatures. These temperatures were extracted from one or more of the channels from one or more of the sub images in block 1302. A graphics processing unit (GPU) of the user device creates the rendering by binding the data (e.g., from the sub image) to a texture/color palette. In some examples, the data image generation system provides any other relevant information to the GPU at the same time that is required for rendering the data, such as the color scale to map values to, matrix information about how to transform the data (map projections, positioning the output on a map, etc), and any other information of relevance," (page 7, para [0097]; Fig 13).
“Interface 10, as shown, includes a plurality of tiles 12 that segment the data across the larger area of interface 10,” (Shipes; page 2, para [0037])
“For example, an image for precipitation can include white for snow, blue for light rain, and purple for heavy rain, while areas without precipitation could be transparent or include a rendering of the geographic area to simulate transparency. In operation, a user device receives these pre-generated images (corresponding to tiles 12) and displays them as generated with minimal, if any, processing. If a user requests a different set of data, then a different set of tiles 12 are generated by the server and delivered to the user device for display,” (Shipes; page 2, para [0038]).
The geospatial data tile comprises a data image and sub images.).
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Shipes in view of Peng in further view of Rohlf et al. (US 8650220 B2; hereinafter Rohlf).
Regarding claim 15, Shipes in view of Peng is not relied upon teaching but Rohlf teaches the non-transitory computer-readable storage medium of claim 11, wherein parsing the geospatial data further causes the one or more processors to: sort the geospatial data based on a location the geospatial data is collected (“…geospatial data is spatially partitioned into a plurality of discrete three-dimensional segments that can be organized and retrieved to facilitate the presentation of data in the geographic information system. As used herein, the term "spatial partitioning" refers to dividing a space into distinct subsets. For instance, geospatial data for a three-dimensional space can be spatially partitioned into a plurality of discrete geospatial volumes…
Each discrete geospatial volume can represent a section of geospatial data within the space defined by the discrete geospatial volume, such as geographic imagery data, data used to render three-dimensional models of buildings and other objects, metadata, and other geospatial data. Each of the discrete geospatial volumes can have particular geographic coordinates (e.g. latitude, longitude, and altitude)…,”(col 4, lines 27-67; col 5, lines 1-2).
Partitioning geospatial data into geospatial volume defined by location reads on sorting geospatial data based on a location the geospatial data is collected.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Rohlf to Shipes in view of Peng. The motivation would have been to “to facilitate processing of the data,” (col 1, lines 40- 51). Additional motivation would have been to break up massive volumes of data into manageable pieces for fetching and rendering data associated only with the visible portion of the geographic area in the user interface for viewing and / or navigating the geographic imagery.
Regarding claim 5, it is rejected using the same citations and rationales described in the rejection of claim 15.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Shipes in view of Peng in further view of Hong (US 20170178376 A1; hereinafter Hong).
Regarding claim 16, Shipes in view of Peng is not relied upon teaching but Hong teaches the non-transitory computer-readable storage medium of claim 11, wherein parsing the geospatial data wherein parsing the geospatial data further causes the one or more processors to: sort the geospatial data based on a time the geospatial data is collected (“The temporal data may indicate a time stamp, frequency, or interval in which the data is received,” (pages 1-2, para [0021]).
“In further example embodiments, the user may specify search criteria, such as temporal constraints (e.g., within the last hour, day, week, month, or the last ten data points from this source) or search terms, in order to identify only those data points received within the specified span of time, frequency, or chronology. The geospatial interface system may then identify data points having temporal data within the specified time frame, or text data matching the search terms to display within the graphical user interface,” (page 2, para [0024]).
“…the geospatial interface system retrieves and buckets and presents each data point by time (e.g., based on the temporal data) in order to convey temporal elements of the data,” (page 2, para [0027]-[0028]).
“Having defined a limit to the temporal constraint, at operation 360 the interface module 204 updates the display of the geospatial data to include a set of data points based on the temporal constraints and the family identifier of the first data point selected. To identify the set of data points, the interface module 204 may provide the temporal constraints to the indexing module 206 which then searches the temporal data of the data points associated with the family identifier. Upon identifying the set of data points which fit with the temporal constraints, the interface module 204 updates the display to include only those data points identified,” (page 4, para [0049]-[0050]).
Sorting includes bucketing and/ or filtering and/ or searching based on temporal data.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Hong to Shipes in view of Peng. The motivation would have been to improve organization, retrieval, and / or presentation / visualization of geospatial information. Additional motivation would have been to improve user experience. Further motivation would have been to improve the management and analysis of geospatial data.
Regarding claim 6, it is rejected using the same citations and rationales described in the rejection of claim 16.
Conclusion
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/ERICA G THERKORN/Examiner, Art Unit 2618
/DEVONA E FAULK/Supervisory Patent Examiner, Art Unit 2618
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