Abstract: An update system may be used to update referenced data objects that are used by multiple applications. In some cases incorrect data may be entered and later corrected. Data consistency techniques are described herein to help avoid use of incorrect data before the data is corrected. A communication from the update system may include updated master data objects and an indication that there are further updates queued. A flag may be set for each of the updated master data objects as they are stored in a database. Then when a request to access those objects is received, the request may be denied when the flag set, thereby preventing access to potentially incorrect or outdated data.

Abstract: A first plurality of replicated state machines may execute a sequence of ordered agreements to make mutations to a data stored in a first data storage service of a first type. A second plurality of replicated state machines may execute the sequence of ordered agreements to make mutations to the data stored in a second data storage service of a second type. First metadata of the mutated data stored in the first data storage service may then be received and stored, and second metadata of the mutated data may be stored in the second data storage service. The stored first and second metadata may then be compared when the data have settled, and a selected action carried out based upon the result of the comparison.

Abstract: In some embodiments, an apparatus includes a memory associated with an instance of a distributed database at a compute device configured to be included within a first group of compute devices. The apparatus is configured to determine an order for each event from the set of events based on different configurations of an event consensus protocol. The different configurations are logically related to different configurations of compute devices that implement the distributed database. The apparatus is configured to determine a current state of the instance of the distributed database based on the order determined for each event from the set of events and generate a signed state associated with the instance of the distributed database based on a hash value associated with the current state. The apparatus sends a signal to post into the instance of the distributed database an event that includes a transaction indicative of the signed state.

Abstract: Techniques related to query execution against an in-memory standby database are disclosed. A first database includes PF data stored on persistent storage in a persistent format. The first database is accessible to a first database server that converts the PF data to a mirror format to produce MF data that is stored within volatile memory. The first database server receives, from a second database server, one or more change records indicating one or more transactions performed against a second database. The one or more change records are applied to the PF data, and a reference timestamp is advanced from a first to a second timestamp. The first database server invalidates any MF data that is changed by a subset of the one or more transactions that committed between the first and second timestamps.

Abstract: Techniques for a context preservation during server restart are described. A restart of a database server having at least one open communications session with a database client is initiated. The database server can be executed by a compute instance hosted by a computer system of a provider network. A restarted database server is launched. The restarted database server obtains session state data to resume the at least one open communications session with the database client, the session state data including one or more session variables. The restarted database server receives a transaction from the database client.

Abstract: A set of both smart contract and off-chain tools is described that enable the management and organization of data so as to enable storage of that data in a distributed ledger according to relational database principles. A cross-distributed-ledger-platform specification plus reusable core components together create a system that may be implemented on distributed ledger platforms to enable storage and retrieval of data to/from the distributed ledger governed by relational principles. A realization of this system enables addition of system chaincode to Hyperledger® Fabric and uses schemas and data represented as JSON. In use, the user may create, update, and query data from code, a console, or a smart contract where every update is a distributed ledger transaction.

Abstract: Embodiments herein describe a hardware accelerator (e.g., a network acceleration engine) for a blockchain machine or node. The hardware accelerator parses packets containing separate components of a block of transactions to generate data to perform a validation process. To avoid the latency that comes with using software, the embodiments herein describe a protocol processor in the hardware accelerator that parses the packets and prepares the data so it can be consumed by downstream components in the accelerator without software intervention. These downstream components can then perform a validation operation to validate one or more transactions before those transactions are committed (i.e., added) to a ledger of a permissioned blockchain.

Abstract: A database system supporting persistent queries, using an enhanced persistent query service and various data sources. On receiving a request to create a persistent query from a client software application, the persistent query service: creates a query virtual table; parses the persistent query; creates a plurality of intermediate virtual tables; establishes listeners for the query virtual table; creates a plurality of data source virtual tables; causes the plurality of data source virtual tables to retrieve initial data from data sources; and propagates data via intermediate virtual tables to the persistent query virtual table.

Abstract: An automated method for search and generation of relevant search results includes: receiving freeform search characters input by a user; simultaneously searching a first freeform entry source and a second freeform entry source to obtain corresponding first suggested freeform entries and second suggested freeform entries; ranking the first suggested freeform entries according to first rules of relevancy to the user, and generating first ranked suggested freeform entries; ranking the second suggested freeform entries according to second rules of relevancy to the user, and generating second ranked suggested freeform entries; combining the first and second ranked suggested freeform entries into a combined set of suggested freeform entries, and ranking the combined set of suggested freeform entries according to combined rules of relevancy to the user, and generating combined ranked suggested freeform entries; and transmitting the combined ranked suggested freeform entries to the user for selection of a desired typ

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, network communications to interface among repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform configured to provide one or more computerized tools that facilitate data projects by providing an interactive, project-centric workspace interface that may include, for example, a unified view in which to identify data sources, generate transformative datasets, and/or disseminate insights to collaborative computing devices and user accounts.

Abstract: In various example embodiments, a system and methods are presented for converting query structures for information retrieval from graph-based data structures. The systems and methods receive a natural language query including a set of terms and generate an intermediate semantic relationship of the set of terms of the natural language query. The systems and methods generate a graph query including graph terms corresponding to the set of terms of the natural language query defined by a graph database. The systems and methods search one or more datasets associated with the graph database using the graph query and return a set of results based on the graph query.

Abstract: Computer-readable media, methods, and systems are disclosed for improving performance when dropping database snapshots in an in-memory database by pruning tree branches in one or more converters associated with a snapshot of an in-memory database. A request to compare at least two database snapshots is received. Physical pages associated with at least one of the two database snapshots are loaded. First and second converter streams are iterated. Physical block numbers of intermediate converter pages to which the first and second converter streams currently point are compared. If the physical page numbers are all non-equal, the physical pages referenced by the second converter stream are set to free. If any of the physical page numbers are equal, subsequent traversal of a corresponding converter subtree in the first and second converter streams may be skipped to improve performance.

Abstract: A method if improving the performance of any SQL query in a Massively Parallel Processing (MPP) database platform replicates a query and breaks the query down into its objects so that iterations of the query components may be analyzed for areas affecting performance. The method builds the query from the lowest part of the query (for example, a single database object may be used in the query) and rebuilds the query by iteratively adding more objects along with their related logic (joins, group by clause, select list, etc.). In each iteration, the process analyzes for the underlying causes of lower performance and fixes them.

Abstract: A computerized-method for reducing wait-time in a multichannel-contact-center is provided herein. For each query that is not resolved by a hot, operating a Channel-Agnostic-Queuing (CAQ) module. The CAQ-module includes: a. selecting a digital-channel-type in a predetermined order; b. operating an aggregator module on the selected digital-channel-type to: (i) identify similar pending queries in a queue-database related to the digital-channel-type: and (ii) aggregate the received query and the identified similar pending queries into a group-of-queries; c. operating a tracker-module on the group-of-queries to identify a query-resolution and to send a notification as to the query-resolution to the customer and to related customers of the identified similar pending queries; and d. when a total-parking-period of the plurality of digital-channel-types is lower than an expected wait-time of the received query and the received query hasn't been resolved, repeating operations a.-c.

Abstract: Apparatus and methods for reconciling data in a big data environment is provided. Methods may receive a first data set and a second data set for reconciliation. Methods may identify a first set of metadata associated with the first data set. Methods may identify a second set of metadata associated with the second data set. Methods may include a data reconciliation algorithm. The algorithm may compare the first set of metadata to the second set of metadata to obtain a subset of data found within the first data set and a subset of data found within the second data set that are joinable. Methods may dynamically construct one or more SQL queries to identify any discrepancies between the first data set and the second data set. Methods may execute the one or more SQL queries that identify any discrepancies between the first data set and the second data set.

Abstract: Apparatus, methods, and computer-readable media facilitating efficiently scaling result caching are disclosed herein. An example method includes generating an index based on a plurality of source data objects in an object storage system. The generated index comprises a manifest, at least one symbol file, and at least one locality file. The example method also includes receiving a search query for the plurality of source data objects stored in the object storage system, and querying the generated index based on the search query and a manifest root file of the manifest. Additionally, the example method includes generating a materialized view of a result set of the search query based on the querying of the generated index. The example method also includes storing a cached manifest file at the generated index, the cached manifest file mapping the search query to a segment of the generated index based on the result set.

Abstract: A plurality of histograms are maintained with respect to a dataset. The dataset includes a plurality of data segments. In response to a query that includes a plurality of conditions ordered in an initial sequence, a plurality of corresponding rejection rates is determined for the plurality of conditions based at least in part on the plurality of histograms. The plurality of conditions are re-ordered according to the plurality of corresponding rejection rates associated with the plurality of conditions to form a reordered sequence for the plurality of conditions. The query is executed according to the reordered sequence of the plurality of conditions.

Abstract: The disclosure describes temporal optimization of data operations using distributed search and server management, including configuring one or more host groups, determining one or more stripes associated with one or more shards distributed among the one or more host groups, receiving a query to retrieve data, evaluating the query to identify a time characteristic associated with the data, identifying a location from which to retrieve the data, and rewriting the query to run on at least one of the one or more host groups at the location using a distributed search platform, the another query being targeted at a host group associated with the class.

Abstract: A system and a method are disclosed for identifying a co-applicant based on proximity to an applicant. In an embodiment, a processor determines a location of the applicant, and identifies a plurality of potential co-applicants that are collocated with the location of the applicant. For each respective potential co-applicant of the plurality of potential co-applicants, the processor determines whether a respective edge exists on a graph that connects the applicant with the respective potential co-applicant, and, responsive to determining that the respective edge exists, identifies the respective potential co-applicant as a candidate co-applicant. The processor generates for display, on a device of the applicant, a selectable option that, when selected, indicates that the applicant would like to use the candidate co-applicant as a co-applicant for an application. Responsive to detecting a selection of the selectable option, the processor activates the application at a device of the candidate co-applicant.

Abstract: A method of processing top-k (k is a natural number) query in array data is described. The method of processing the top-k query is performed in a computing device including at least a processor, and includes dividing an array including a plurality of cells into a plurality of partitions, and finding an ith answer in the array.

Abstract: A distributed event processing system is disclosed that receives a batch of events via a continuous data stream and performs the serialization of data in the batch of events. In certain embodiments, the system identifies a first data type of a first attribute for each event in a batch of events and determines a first type of data compression to be performed on data values represented by the first attribute. The system determines a first type of data compression to be performed on data values represented by the first attribute based on the first data type of the first attribute. The system then generates a first set of serialized data values for the first attribute. The system processes the first set of serialized data values against a set of one or more continuous queries to generate a first set of output events.

Abstract: Systems and methods are disclosed for annotating a metadata catalog in a data intake and query system based on a query received by the data intake and query system. The metadata catalog can store information about datasets associated with the data intake and query system, including dataset configuration records of the datasets, which can be used to process queries for execution by the data intake and query system. The data intake and query system can receive a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system can parse the query to identify datasets and/or data fields associated with the query. Based on the identified datasets and/or fields, the data intake and query system can generate one or more annotations, and use the annotations to update the metadata catalog.

Abstract: A computer system comprises a memory, a network interface, and at least one processor is provided. The memory stores a plurality of user profile records and a plurality of skill profile records. The at least one processor is configured to receive a request to recommend a skill to improve mental health of a user; retrieve, from the plurality of user profile records, a user profile record associated with the user and the skill, the user profile record including a first weight; retrieve, from the plurality of skill profile records, a skill profile record associated with the skill, the skill profile record including a second weight; determine a third weight based on the first weight and the second weight; generate a response to the request, the response including an identifier of the skill and the third weight; and transmit the response to a virtual assistant.

Abstract: A model learning unit learns a prediction model on the basis of learning data, a target setting unit sets a target output parameter value by interpolating between a goal output parameter value and an output parameter value which is the closest to the goal output parameter value in output parameter values in the learning data, a processing condition search unit estimates input parameter values which corresponds to the goal output parameter value and the target output parameter value, a model learning unit updates the prediction model by using a set of the estimated input parameter value and an output parameter value which is a result of processing that a processing device performs as additional learning data.

Abstract: An analysis application utilizes interactivity signals to generate relationships and promote content. One or more interactivity applications, such as a social networking application, are queried to retrieve interactivity signals. Interactivity signals include an interaction pattern that indicates a relationship between a user and relations of the user. A relationship graph is constructed based on the interactivity signals. Content associated with a user is promoted based on the relationship graph. A weight of the interactivity signals is adjusted to improve a ranking of the relationship graph and a ranking of the content.

Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage media for using multiple data structures to correlate information from multiple distributed data sources. The method can include receiving a request to create a report data structure, generating first data representing a digital report template the generated first data including (i) a first digital template defining multiple keyed data fields that are configured to be dynamically populated and (ii) a second digital template defining one or more instances of static data that can each be selectively activated or deactivated based on the request, extracting keyed data and natural language data from files in one or more of the data sources, mapping the extracted data to the multiple keyed data fields of the report template, and generating a report data structure based on (i) the mapped data and (ii) static data that has been selectively activated based on the request.

Abstract: A general purpose blockchain (GPB) providing the capability of native arbitrary computation and storage of any type of digital object with distributed verification technology (DVT) implementation that not only allows scalable arbitrary computational verification of digital objects, but also is agnostic as to the types of object. The GPB platform comprises an interface for interacting with arbitrary objects (“GPB arbitrary objects”). The interface transforms unstructured data into structured, extensible data without loss of fidelity of the underlying data. This is accomplished through a transformation function, which takes as input any arbitrary form of data and provides as output a structured data object upon which cryptographic and other operations necessary to the functions of DVTs can be performed collectively by a plurality of GPB blockchains. One proposed method of creating this structured output uses open-standard, extensible markup language (XML) data.

Abstract: A computer system for behavioral analytics of native Information Technology Service Management (ITSM) incident handling data includes a processor, a memory, a de-normalized target data source for behavioral analysis, a transformation processor, and a statistical processor. The transformation processor reads an identified portion of the ITSM data and creates new normalized fields for the de-normalized target data source by parsing selected text fields from the portion of ITSM data. The created new normalized fields include a working group field and an associated support level field. The transformation processor further creates new de-normalized aggregation fields for the incipient de-normalized target data source based on the newly created normalized fields. The newly created de-normalized aggregation fields include fields characterizing incident handling behavior. A statistical processor further processes target data for behavioral analytics.

Abstract: Described herein are systems, apparatus, methods and computer program products configured for componentized dashboards for data visualization. In certain embodiments, a component may be configured to be integrated within a dashboard. The component may receive data from one or more user database and provide one or more representations of the data. The component may be integrated within the dashboard as a separate component. That is, the component may provide the plurality of representations independent of the dashboard. The component may be maintained independent of the dashboard and, thus, may be updated independent of the dashboard.

Abstract: Systems and methods include causing presentation of a first cluster in association with an event of the first cluster, the first cluster from a first set of clusters of events. Each event includes a time stamp and event data. Based on the presentation of the first cluster, an extraction rule corresponding to the event of the first cluster is received from a user. Similarities in the event data between the events are determined based on the received extraction rule. The events are grouped into a second set of clusters based on the determined similarities. Presentation is caused of a second cluster in association with an event of the second cluster, where the second cluster is from the second set of clusters.

Abstract: Methods, processing units, and computer-readable media in a cloud-based database are described. Redo log records are applied to a page at a database replica only when an updated version of the page is requested at the database replica. A log cache may be used by a replica node of the database to track recent redo log records applicable to a given page. The recent redo log records stored in the log cache may be applied to update the page on-demand when an updated version of the page is requested. By applying only the redo log records applicable to pages that are currently being requested, processing resources may be used only to generate pages that are currently required. Methods for registering redo log records into the log cache by the master or replica server are also described.

Abstract: The disclosed technology relates to a system configured to receive operations data from a content management system, wherein the operations data comprises a log of operations, execute the log of operations, and update, based on execution of the log of operations, a remote tree representing a server state for content items stored on the content management system.

Abstract: A method for converting from one asynchronous data replication technology to another is disclosed herein. In one embodiment, such a method includes utilizing a first asynchronous data replication technology to asynchronously replicate data from a primary volume to a secondary volume. The method initiates, at time T1, tracking of post-T1 changes to the primary volume and waits for all pre-T1 changes to the primary volume to be propagated to the secondary volume. When all pre-T1 changes have been propagated to the secondary volume, the method suspends operation of the first asynchronous data replication technology and replicates all post-T1 changes from the primary volume to the secondary volume. The method further sets up and initiates a second asynchronous data replication technology to asynchronously replicate data from the primary volume to the secondary volume. A corresponding system and computer program product are also disclosed herein.

Abstract: A database system may use a machine learning model creation system to create a machine learning model from data stored in the database system responsive to a request from a client. The database system may obtain an executable version of the machine learning model, based on an uncompiled hardware agnostic version of the machine learning model, according to the hardware configuration of one or more computing resources selected by the database system to perform requests to the database system that invoke the machine learning model to generate predictions.

Abstract: Embodiments include apparatuses, methods, and systems for managing a data warehouse associated with an electronic payment transaction processing network. A first set of stores are active and a second set of stores are inactive in an offer program related to merchandise of a merchant. A first set of transaction records for a first set of transactions from the first set of stores and a second set of transaction records for a second set of transactions from the second set of stores are obtained. A first set of operations on the data warehouse for the first set of transaction records and a second set of operations on the data warehouse for the second set of transaction records may be performed. The second set of operations, different from the first set of operations, includes an update operation on the data warehouse. Other embodiments may also be described and claimed.

Abstract: Disclosed are systems and method of mapping data entries originating in different systems. A plurality of data entries from different systems are normalized such that they can be compared to each other and mapped, even though the data entries are defined by data fields with differing phrases, descriptive details, and lengths of detail. Data entries may be filtered according to data fields before a mapping operation is employed for mapping. The mapping operation evaluates similarity scores based on the data fields using a combination of exact matching algorithms, dictionary matching algorithms, and text mining algorithms. The mapped data entries and data fields are displayed to a user.

Abstract: An apparatus, or corresponding method, for building or updating a map database is described. In one example, the apparatus includes an image correlation module, a training device, and a learned model or neural network. The image correlation module is configured to correlate a first aerial image and terrestrial sensor data collected at a terrestrial vehicle based on at least one control point from the terrestrial data. The learned model training device is configured to define a learned model based using at least one control point from the terrestrial sensor data as ground truth for analysis of the first aerial image. The learned model inference module is configured to receive a second aerial image and apply the learned model on the second aerial image for identification of mapping information for the map data.

Abstract: A system and apparatus for rating accessibility of a number of locations for user and/or members with specific accessibility needs. The user and/or member interacts with a database through his or her communication device or through a website to access locations in a geographic zone that provide accommodations for people with specific accessibility needs in a variety of accessibility categories. The system provides detailed accessibility features within each accessibility category and rates the locations according to the accessibility categories. The member can also input new locations, rate locations already contained in the database, or provide other feedback regarding compliance with legal accessibility guidelines and/or other accessibility standards within the United States and abroad. The system updates the ratings of the accessibility categories and the accessibility features based on input from members.

Abstract: In an embodiment, a system can determine geocoded data from a database of geographic coordinates and metadata. The system correlates metadata, such as invoice data, to geolocation data, such as GPS or cellular data to determine geocoded data. The system further identifies one or more geographic coordinates for one or more location names, which may not have a corresponding metadata entry, by generating clusters of geographic coordinates. The clusters are then matched to one or location names using a matching algorithm. Accordingly, improved geocoded data may be determined.

Abstract: Methods and apparatus for determining aspects of locations based on computing interactions of users that pertain to the locations. In some implementations, an aspect of a location may be determined based on comparing a first computing interaction measure for the location to a second measure. The first computing interaction measure may be determined based on a first group of computing interactions that pertain to the location. In some implementations, the second measure may be determined based on a second group of addition computing interactions. In some implementations, a textual summary may be generated automatically based on the first and/or second computing interaction measure, and/or based on the determined aspect.

Abstract: At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structures for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.

Abstract: A computer system document according to one embodiment includes a generation unit and an update unit. The generation unit performs first machine learning on a target document, as input data, to which a correct path in a tree structure where each node indicates a document category is given, and thereby generates a classification model indicating a right path to a leaf node for the target document. The update unit performs second machine learning that applies, to the classification model, the target document to which the correct path is not given, and when a path from an Nth level node to an (N+1)th level node is different from the correct path, updates the classification model by setting a modified path from the (N+1)th level node to an (N+2)th level node different from a child node of the (N+1)th level node based on the correct path.

Abstract: Methods and apparatuses are described for automatically identifying text sections of a document to generate a searchable hierarchical data structure. A computing device receives a document comprising text entities and converts the document from a first format to a second format, including generating metadata associated with text alignment, text position, text spacing, or fonts. The computing device extracts the text blocks, including determining coordinates associated with each text block using the metadata. The computing device determines document sections using the document metadata by identifying strings in the extracted text blocks that indicate a presence of a bullet point in the document, assigns a hierarchical category to each identified document section, and inserts text of each document section into a hierarchical data structure based upon the assigned hierarchical category.

Abstract: A method and system for identifying social trends are provided. The method includes collecting multimedia content from a plurality of data sources; gathering environmental variables related to the collected multimedia content; extracting visual elements from the collected multimedia content; generating at least one signature for each extracted visual element; generating at least one cluster of visual elements by clustering at least similar signatures generated for the extracted visual elements; correlating environmental variables related to visual elements in the at least one cluster; determining at least one social trend by associating the correlated environmental variables with the at least one cluster.

Abstract: Systems and methods for generating and presenting content recommendations to new users during or immediately after the onboarding process, before any history of the new user's viewed content is available. A machine learning or other model may be trained to determine clusters of content genre values corresponding to genres of content watched by viewers. Clusters are thus associated with popular groupings of content genres viewed by many users. Clusters representing popular groupings of content genres may be selected for new users, and content corresponding to the selected clusters may be recommended to the new users as part of their onboarding process. A sufficient amount of content may be selected to fully populate any content recommendation portion of a new user onboarding page.

Abstract: A method of selecting and presenting content based on learned user preferences is provided. The method includes providing a content system including a set of content items organized by genre characterizing the content items, and wherein the set of content items contains microgenre metadata further characterizing the content items. The method also includes receiving search input from the user for identifying desired content items and, in response, presenting a subset of content items to the user. The method further includes receiving content item selection actions from the user and analyzing the microgenre metadata within the selected content items to learn the preferred microgenres of the user. The method includes, in response to receiving subsequent user search input, selecting and presenting content items in an order that portrays as relatively more relevant those content items containing microgenre metadata that more closely match the learned microgenre preferences of the user.

Abstract: Systems and methods for displaying media files on a device are provided. The device provides a first mode that displays a subset of media files, determined by a user query, from a plurality of media files. Once activated, the first mode persists on the device prior to becoming inactive. A second mode of the device displays the plurality of media files. The second mode is active when the first mode is inactive. An instruction is received from a user. When the instruction specifies the first mode by inclusion of a user query, a corresponding subset of files is obtained from a remote system. The subset of files is sequentially displayed until the period of time has elapsed according to the first mode. When the instruction does not specify a query, the plurality of files is polled for from a remote device and sequentially displayed according to the second mode.

Abstract: Methods, apparatuses, and non-transitory machine-readable media for image location based on a perceived interest are described. Apparatuses can include a display, a memory device, and a controller. In an example, the controller can assign a perceived interest and sort images based in part on the perceived interest. In another example, a method can include the assigning, by a controller coupled to a memory device, a perceived interest of an image of a plurality of images, wherein the perceived interest is assigned based in part on a period of time the image is visible on a display coupled to the memory device, selecting the image from an initial viewing location responsive to the assigned perceived interest; and transferring the image to a different viewing location, wherein the initial viewing location and the different viewing location are visible on the display.

Abstract: A machine may be configured to execute a machine-learning process for identifying and understanding fine properties of various items of various types by using images and associated corresponding annotations, such as titles, captions, tags, keywords, or other textual information applied to these images. By use of a machine-learning process, the machine may perform property identification accurately and without human intervention. These item properties may be used as annotations for other images that have similar features. Accordingly, the machine may answer user-submitted questions, such as “What do rustic items look like?,” and items or images depicting items that are deemed to be rustic can be readily identified, classified, ranked, or any suitable combination thereof.

Abstract: The disclosure is generally directed to optical devices and apparatuses for capturing, structuring, and using interlinked multi-directional still pictures and/or multi-directional motion pictures as well as the related systems and methods, and their applications on computing and/or other devices.