Abstract: An example method of determining geolocations of composite entities based on information retrieved from heterogeneous data sources comprises: identifying, by a computer system, an association of a first object and a second object with a composite object; receiving, from a first data source associated with the first object by an ontology, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the first object; receiving, from a second data source associated with the second object by the ontology, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the second object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the composite object and a corresponding time identifier.

Abstract: A method and apparatus for managing and controlling a resource based on a time series database. The method includes: acquiring metadata of a resource; aggregating the metadata according to an aggregation strategy to obtain aggregated metadata; and managing and controlling the resource in the time series database based on the aggregated metadata. The aggregated metadata may be multiple data sets, each of which may be a type of metadata, so that massive metadata may be aggregated into the multiple sets, thereby realizing categorized storage of the metadata. In addition, the method for managing and controlling the resource is applied to the time series database.

Abstract: A method and system for decontaminating raw yield maps by combining filters with spatial outlier detectors is provided. In an embodiment, the method comprises receiving over a computer network electronic digital data comprising first yield data representing crop yields harvested from an agricultural field; applying one or more filters to the first yield data to identify, from the first yield data, first outlier data; generating first filtered data from the first yield data by removing the first outlier data from the first yield data; identifying, in the first filtered data, second outlier data representing outlier values based on one or more outlier characteristics; generating second outlier data from the first filtered data by removing the second outlier data from the first filtered data; generating and causing displaying on a mobile computing device a graphical representation of the crop yields harvested from the agricultural field using only the second outlier data.

Abstract: Systems and methods for grouping telematics vehicle data in one or more zones are provided herein. Systems and methods for generating zones and providing vehicle information associated with the one or more zones are also provided. Systems and methods for parallelizing zone generation and addressing zones disposed adjacent a boundary of a geographical are also provided.

Abstract: Among a great deal of other disclosure and scope, systems and methods are enclosed that enable for highly efficient labeling of data. For example, in some of many cases, a novel methodology for ranking vectors most useful to label next is disclosed. In such an example, a neural network is trained to predict this ranking methodology upon being given a set of heuristics from which to assess the given problem space. A user can continue the cycle of identifying a set of candidate vectors to label, compiling relevant heuristics from said vectors, ranking vectors via the trained neural network, selecting a subset of the ranked vectors, inquiring an oracle regarding the true labels of the vectors, and then appending the subset of newly labelled vectors to the labelled set of vectors until satisfaction.

Abstract: Disclosed are implementations that include a method for detecting anomalous data, including converting a set of data values representative of a multi-dimensional item into a nodes-and-edges graph representation of the item, applying a graph convolution process to the graph representation to generate a transformed graph representation for the item comprising a resultant transformed configuration of the nodes and edges representing the item, and determining, based on the transformed configuration, a probability that the item is anomalous. Another example method includes receiving input data at a neural network circuit comprising a plurality of node layers, with each of the plurality of node layers comprising respective one or more nodes, with the neural network circuit further comprising adjustable weighted connections connecting at least some nodes in different layers of the plurality of node layers. The method further includes removing one or more of the weighted connections at one or more time instances.

Abstract: A host with a memory, which stores a guest, a filesystem cache, and a proxy cache, has a filesystem manager executing on a processor that receives a first request to locate a file in a first filesystem. In response to receiving the first request, a filesystem proxy in the proxy cache associated with the first filesystem is queried. The first request is responded to based on metadata retrieved from the filesystem proxy. A second request is received to modify the file. In response to receiving the second request, the first filesystem is instantiated in the filesystem cache, where a second filesystem is evicted from the filesystem cache to reclaim storage capacity for the first filesystem. The file in the first filesystem is modified.

Abstract: Techniques are disclosed for evaluating digital map quality. A process includes steps for receiving change data indicating one or more feature discrepancies associated with one or more geographic regions of a digital map, analyzing the change data to determine which of the one or more feature discrepancies resulted in verified updates to the digital map, and generating a quality score for each of the geographic map regions based on the verified updates. Systems and machine-readable media are also provided.

Abstract: A data processing method includes: pulling full data regularly in accordance with a predetermined time, partitioning a DFS by date, and storing the full data in a corresponding partition of the DFS; filtering through the full data to obtain incremental data, sorting the incremental data, and storing the sorted data in a dimension table and an event table of a data warehouse detail layer, the dimension table being associated with the event table through a surrogate key; and associating the dimension table with the event table to generate a report, generating an aggregate table in accordance with a predetermined aggregation demand, and storing the generated aggregate table at a reporting layer.

Abstract: Examples include a blockchain system associated with a distributed file system. Some examples include creating a block in the blockchain system for each action performed while performing a transaction in relation to a file stored in the distributed file system. The created block includes information identifying one or more of a signature of metadata of the file or a signature of data content of the file. Some examples include performing audit on a file, through a blockchain system, to validate consistency of the file.

Abstract: A central database system allows users to access and use data stored in a relational database. In order to ensure that the stored data is not detrimentally impacted and that the security of the stored data is maintained, the central database system generates a sanitized copy of the database. The central database system stores and accesses annotation files associated with data tables of the database and a schema identifying the structure of the database. Based on the schema, for each data table, the central database system validates the annotation file. A copy of the data table is created and sanitized corresponding to the annotation file. The sanitized copies of the data tables are used to generate a sanitized copy of the database. The sanitized copy of the database may then be accessed and used by users of the central database system without impacting the relational database.

Abstract: A first combined key may be generated based on a geographic location, a first time, and a first user that are associated with a first event. The first combined key and first data indicating the first event may be stored in a database, the first combined key configured to identify the first data. A second combined key may be generated based on the geographic location, a second time, and a second user that are associated with a second event. The second combined key and second data indicating the second event may be stored in the database, the second combined key configured to identify the second data. A set of events associated with the geographic location and comprising the first event and the second event may be presented by retrieving the first data and the second data using the first combined key and the second combined key, respectively.

Abstract: A method includes selecting, from content packs in a centralized content management system, a content pack to update in a data intake and query system. The content pack includes utility objects. For each utility object of at least a subset of the utility objects determining whether the utility object already exists in the data intake and query system, and loading the utility object to the data intake and query system when the utility object does not exist to obtain an updated utility object. The method further includes monitoring, by the data intake and query system, an endpoint of an endpoint type using the updated utility object.

Abstract: A transform-by-pattern (TBP) system is configured to proactively suggest relevant TBP programs based on inputted source dataset and target dataset without requiring users typing in examples. The TBP system has access to multiple TBP programs, each of which includes a combination of a source pattern, a target pattern, and a transformation program that is configured to transform data that fits into the target pattern into data that fits into the source pattern. When a source dataset and a target dataset are received from a user, the TBP system identifies a subset of the source dataset and a subset of the target dataset as related data. The TBP system then identifies one or more applicable TBP programs amongst the multiple TBP programs, and suggest or apply at least one of the one or more applicable TBP programs.

Abstract: A digital map based online platform is provided. The online platform comprises an outdoor map server, a data store, a building database, a space database, and a computer program stored in a medium. The data store manages digital files related to buildings including floor plans of buildings and digital files including website source codes related to spaces in individual folders for each building and space. The building database and the space database manage map setting data of buildings and spaces, respectively. The computer program stored in a medium executes a series of stages to integrally display an outdoor map, an indoor map including floor plans of buildings, Internet links, and responsive HTML pages on the view of a digital map. The medium includes a web server and a user terminal.

Abstract: Exemplary systems, implement Distributed Ledger Technology (DLT) in conjunction with a cloud based computing environment. The system operates receives input for adding a plurality of authorized network participants to a declared application, in which the network participants are granted access rights to the declared application. The system further deploys an executable install package to each of the plurality of authorized network participants for the declared application; in which the executable install package retrieves the metadata for the declared application from the blockchain and displays GUIs specific to the declared application which are auto generated by the executable install package based on the retrieved metadata.

Abstract: An apparatus is provided for outputting suggested query items by a group-based communication platform. The apparatus may include at least one memory and at least one processor configured to detect group-based communication platform query data stored in a memory of the apparatus. The processor is also configured to rank suggested query items based on the group-based communication platform query data. The processor is further configured to detect non-keystroke engagement of a search input interface of the group-based communication platform. The processor is further configured to determine a first subset of the suggested query items based on the ranking of the suggested query items and automatically launch a query suggestion interface including a first subset of the suggested query items in response to detecting the non-keystroke engagement of the search input interface. Corresponding methods and computer program products are also provided.

Abstract: Systems and methods for file management by mobile computing devices. An example method, performed by a computer system, may comprise: storing, by a computer system, a first file having a first size, in a memory; storing, in the memory, a second file derived from the first file, the second file having the second size, the second size being less than the first size; determining that the memory is not sufficient to perform a memory write operation; selecting a third file having a fourth file associated with it, the fourth file derived from the third file; and removing the third file from the memory.

Abstract: Compiled portions of code generated to perform a query plan at a query engine may be shared with other query engines. A data store, separate from the query engines, may store compiled portions of query code generated for different queries. If a query engine does not have a locally stored compiled portion of query code, then the separate data store may be accessed in order to obtain a compiled portion of query code, allowing reuse of compiled query code across different queries engines for queries directed to different databases.

Abstract: Systems, devices, methods, and interfaces generally for use with database management systems (DBMSs) and DBMS interfaces (i.e. user interfaces, input interfaces, search interfaces, operating interfaces, etc.). In some aspects, the systems, devices, methods, and interfaces include using artificial intelligence (i.e. machine learning and/or anticipation functionalities, etc.) to learn a user's use of a DBMS or DBMS interface, store this “knowledge” in a knowledgebase, and anticipate the user's future operating intentions. In other aspects, the systems, devices, methods, and interfaces include disassembling user or other input into various types of portions (i.e. text, numbers, etc.) and determining one or more instructions for performing operations on a DBMS or DBMS interface based on the various types of portions. In further aspects, the systems, devices, methods, and interfaces include associative DBMS command construction. Other systems, devices, methods, interfaces, and features are also disclosed.