Abstract: A computing system that includes one or more server computing devices including one or more processors configured to execute instructions for a domain extensibility module that provides software development tools for building domain extensions for a database platform, and a data ingestion module that provides software development tools for defining a metadata schema for extracting metadata from data files. The one or more processors are configured to receive a set of data from a user computing device, define a target metadata schema that includes one or more metadata fields that will be populated during a data ingestion process, define a target domain extension that defines one or more data types for storing the received set of data after performing the data ingestion process, and ingest the received set of data using a metadata extraction pipeline to generate metadata files based on the target metadata schema.

Abstract: A computing system that includes one or more server computing devices including one or more processors configured to execute instructions for a domain extensibility module that provides software development tools for building domain extensions for a database platform, and a data ingestion module that provides software development tools for defining a metadata schema for extracting metadata from data files. The one or more processors are configured to receive a set of data from a user computing device, define a target metadata schema that includes one or more metadata fields that will be populated during a data ingestion process, define a target domain extension that defines one or more data types for storing the received set of data after performing the data ingestion process, and ingest the received set of data using a metadata extraction pipeline to generate metadata files based on the target metadata schema.

Abstract: In examples, streaming data is received from a data source (e.g., by an edge device associated with a data platform) and is queued and aggregated. Batch data may similarly be received from a data source. The batch data and the aggregated streaming data may be processed to generate metadata accordingly. The data and metadata may be provided to the data platform, where the metadata may be used to update an index and the data may be stored in association with the index. In some instances, the data may be stored in chunks to facilitate subsequent retrieval of the data. In response to a request for the data, the index may be used to identify relevant data, which may include data associated with batch and/or streaming data formats, thereby enabling the client device to access data having any of a variety of formats from the data platform.

Abstract: The disclosed technology is generally directed to an audit ledger for externality tracking. In one example of the technology, auditing of a virtual sensor is enabled. The virtual sensor is configured to output an externality value based on received telemetry data. The externality values are associated with the at least one particular type of quantifiable technical externality. Signing of the virtual sensor is enabled. Audit information associated with the signing of the virtual sensor is stored on a ledger. Periodic aggregated externality values based on the externality values output by the virtual sensor are calculated. The periodic aggregated externality values are stored on a distributed ledger. An audit of the periodic aggregated externality values is enabled. The auditing of the periodic aggregated externality values includes verifying the signing of the virtual sensor by the auditor based on the stored audit information.

Abstract: A computing system that includes one or more server computing devices including one or more processors configured to execute instructions for a domain extensibility module that provides software development tools for building domain extensions for a database platform, and a data ingestion module that provides software development tools for defining a metadata schema for extracting metadata from data files. The one or more processors are configured to receive a set of data from a user computing device, define a target metadata schema that includes one or more metadata fields that will be populated during a data ingestion process, define a target domain extension that defines one or more data types for storing the received set of data after performing the data ingestion process, and ingest the received set of data using a metadata extraction pipeline to generate metadata files based on the target metadata schema.

Abstract: One example provides a computing system configured to implement a greenhouse gas (GHG) tracking and auditing platform for tracking GHG emissions associated with a plurality of GHG entities, each GHG entity representing one or more of a GHG source and a GHG sink. The computing system comprises a logic subsystem and a data-holding subsystem comprising computer-readable instructions. The instructions are executable to receive sensor data over time from each sensor of one or more sensors, each sensor configured to sense data related to GHG emissions. The instructions are further executable to, for each time interval of a plurality of time intervals, determine a GHG emission amount based at least in part on the sensor data and store GHG emission data. The instructions are further executable to receive a request for a set of GHG emission data and in response to the request, output the set of GHG emission data.

Abstract: A computing device including a processor is provided. For one or more emissions factors, the processor may be configured to receive respective emissions factor data including sensor data received from one or more sensors and user-specified data received at a user interface. The processor may be further configured to receive a plurality of virtual sensor models. Each virtual sensor model may include one or more respective virtual sensor model parameters. At least in part by applying the virtual sensor models to the emissions factor data, the processor may be further configured to compute a plurality of virtual sensor readouts. The processor may be further configured to generate a greenhouse gas emissions estimate from the virtual sensor readouts. The processor may be further configured to convey an indication of the greenhouse gas emissions estimate to the user interface for output on one or more output devices.