# US 2014/0156806 A1 · Spatio-temporal data processing systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0156806 A1 - Document ID: US20140156806A1 - Status: Published application - Kind: A1 - Application number: 14/095,752 - Filed: 2013-12-03 - Published: 2014-06-05 - Earliest claimed: 2012-12-04 - Assignees: Marinexplore Inc. - Applicants: Marinexplore Inc. - Inventors: Andre Karpistsenko; Rainer Sternfeld; Kalle Kägi; Oleg Mürk; Rando Valt; Roberto Antonio Ferreira De Almeida - Web page: https://patentgrep.com/patent/US20140156806A1 ## CPC - G06F 16/25: Integrating or interfacing systems involving database management systems - G06Q 10/06: Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling - G06Q 10/08: Logistics, e.g. warehousing, loading or distribution; Inventory or stock management - G06Q 50/02: Agriculture; Fishing; Forestry; Mining - H04L 67/2885: Hierarchically arranged intermediate devices, e.g. for hierarchical caching - G01V 99/00: Subject matter not provided for in other groups of this subclass - G01V 2210/70: Other details related to processing - G06Q 10/0637: Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals - H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks - H04N 21/23109: {by placing content in organized collections, e.g. EPG data repository (details of retrieval of video data and associated meta data in video databases G06F16/739)} - H04N 21/84: Generation or processing of descriptive data, e.g. content descriptors {(systems specially adapted for using meta-information in broadcast systems H04H60/73)} - H04N 21/8456: {by decomposing the content in the time domain, e.g. in time segments} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract This disclosure relates to systems and methods for collecting, integrating, processing, distributing, and analyzing spatial and/or spatio-temporal information associated with a variety of data sources and/or locations. In some embodiments, systems and methods described herein allow for collection and integration of information included in one or more spatial and/or spatio-temporal data streams and/or other related information that may be utilized in connection with one or more analytical processes. In certain embodiments, the disclosed embodiments may allow a user to, among other things, interact with spatio-temporal information associated with a variety of diverse data sources, generate visualizations using such data, and/or perform desired analytical queries based on the data. ## Claims ### Claim 1 A method of processing spatio-temporal data performed by a system comprising a processor and a non-transitory computer-readable storage medium storing instructions that, when executed, cause the system to perform the method, the method comprising: receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component; extracting from the plurality of data streams a plurality of metadata segments and a plurality of data segments; generating a response to a user request using an service engine based on the extracted plurality of metadata segments and plurality of data segments; and transmitting the response to a system associated with the user. ### Claim 2 (depends on 1) The method of claim 1, wherein the plurality of data segments comprise measured data information. ### Claim 3 (depends on 1) The method of claim 1, wherein the plurality of data segments comprise modeled data information. ### Claim 4 (depends on 1) The method of claim 1, wherein extracting the plurality of metadata segments and the plurality of data segments further comprises: generating a plurality of intermediate segments based on the plurality of data streams using transformation information included in at least one transformation library; and extracting the plurality of metadata segments and the plurality of data segments from the plurality of intermediate segments. ### Claim 5 (depends on 1) The method of claim 1, wherein the response comprises a visualization based on the plurality of metadata segments and the plurality of data segments. ### Claim 6 (depends on 1) The method of claim 1, wherein the response comprises a computation result from a predictive model based on the plurality of metadata segments and the plurality of data segments. ### Claim 7 (depends on 1) The method of claim 1, wherein the response comprises at least one metric based on the plurality of metadata segments and the plurality of data segments. ### Claim 8 (depends on 1) The method of claim 1, wherein the method further comprises storing the metadata segments in a metadata database and the data segments in a data segment database. ### Claim 9 (depends on 1) The method of claim 1, wherein the metadata segments comprise one or more data samples of the data included in the plurality of data streams. ### Claim 10 (depends on 1) The method of claim 1, wherein the metadata segments comprise aggregated information associated with the data included in the plurality of data streams. ### Claim 11 (depends on 1) The method of claim 1, wherein the method further comprises identifying a portion of the plurality of data segments comprising outlier data based on data associated with the portion exceeding a threshold relative to data associated with other data segments within a particular temporal and spatial range relative to the portion. ### Claim 12 (depends on 11) The method of claim 11, wherein the method further comprises generating the response based on data segments other than the identified portion. ### Claim 13 A non-transitory computer-readable storage medium storing instructions that, when executed by a processor of a computer system, cause the computer system to perform a method comprising: receiving a plurality of data streams associated with a plurality of diverse distributed data sources, the plurality of data streams comprising data having a spatial component and a temporal component; extracting from the plurality of data streams a plurality of metadata segments and a plurality of data segments; generating a response to a user request using an service engine based on the extracted plurality of metadata segments and plurality of data segments; and transmitting the response to a system associated with the user. ### Claim 14 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein extracting the plurality of metadata segments and the plurality of data segments further comprises: generating a plurality of canonical segments based on the plurality of data streams using transformation information included in at least one transformation library; and extracting the plurality of metadata segments and the plurality of data segments from the plurality of canonical segments. ### Claim 15 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the response comprises a visualization based on the plurality of metadata segments and the plurality of data segments. ### Claim 16 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the response comprises at least one analytical metric based on the plurality of metadata segments and the plurality of data segments. ### Claim 17 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the plurality of data segments comprise at least one of measured data information and modeled data information. ### Claim 18 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the metadata segments comprise one or more data samples of the data included in the plurality of data streams. ### Claim 19 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the metadata segments comprise aggregated information associated with the data included in the plurality of data streams. ### Claim 20 (depends on 13) The non-transitory computer-readable storage medium of claim 13, wherein the non-transitory computer-readable storage medium further comprises instructions configured to cause the computer system to perform a method comprising identifying a portion of the plurality of data segments comprising outlier data based on data associated with the portion exceeding a threshold relative to data associated with other data segments within a particular temporal and spatial range relative to the portion and generating the response based on data segments other than the identified portion.