NRT Data are those that are available for use with a specified (small and application dependent) latency, which is typically 3 hours for meteorological applications. See LANCE.

 Difference in intensity between all incoming energy and all outgoing energy carried by both shortwave and longwave radiation.

NetCDF format that uses the HDF5 data storage model.

Collection of products that are generated in response to a user's request. Such products could either be pre-defined or not.

ORRs evaluate the readiness of the program, including its projects, ground systems, personnel, procedures, and user documentation. ORRs also operate the flight system and associated ground systems in compliance with program requirements and constraints during the operations phase.

Operations Agreements are even lower level, more detailed interface documents that are created to help define the operations use of the interfaces, including such things as addresses, phone numbers, and names of responsible personnel. These documents are not intended for project-level development and control.

 A predetermined set of preselected, predefined and prearranged data (granules) organized for distribution.

A color lookup table that specifies which color to associate with each pixel value on the screen. A palette consists of an array of 256 RGB (Red-Green-Blue) colors.

A measurable or derived variable occurring in the physical or digital world. Variable and Parameter are used interchangeably. GCMD uses the term variable and NSIDC DAAC uses the term parameter.

The closest point of an elliptical orbit. For an Earth-centered orbit, this is the point where the orbiting body is closest to the center of the Earth. 

PFARs evaluate how well mission objectives were met during a human space flight mission. PFARs also evaluate the status of the flight and ground systems, including the identification of any anomalies and their resolution.

PLARs evaluate the in-flight performance of the program and its projects. PLARs also determine the program's readiness to begin the operations phase of the life cycle and transfer responsibility to the operations organization.

PDRs evaluate the completeness/consistency of the program's preliminary design, including its projects, in meeting all requirements with appropriate margins, acceptable risk, and within cost and schedule constraints, and to determine the program's readiness to proceed with the detailed design phase of the program.

Preservation covers all processes and operations on individual or multi-mission data sets for ensuring the technical and intellectual survival of space data sets and their metadata through time. It grants dataset integrity, its discoverability and accessibility, and facilitates its use and reuse in the long term. 

Preservation is one of the tasks of data curation. Examples are data record improvement and consolidation.

The processing function generates higher-level products from lower level products and auxiliary products. The processing is performed by core algorithms supplemented by administrative functions (e.g. formatting). The algorithms are version controlled. Processing is able to produce the desired products systematically or on request.

Raw Data 
The physical telemetry payload data as received from the satellite, i.e. a serial data stream without de-multiplexing. 

Level 0 
Reconstructed unprocessed data at full space-time resolution with all available supplemental information to be used in subsequent processing (e.g. ephemeris, health and safety) appended. 

Level 1A 
Reconstructed unprocessed data at full resolution, time-referenced, and annotated with ancillary information, including radiometric and geometric calibration coefficients and geo-referencing parameters (e.g. ephemeris) computed and appended but not applied to the Level 0 data. 

Level 1B 
Radiometrically corrected and calibrated data in physical units at full instrument resolution as acquired. Level 1C L1B data orthorectified, re-sampled to a specified grid 

Level 2 
Derived geophysical parameters (e.g. sea surface temperature, leaf area index) at the same resolution and location as Level 1 source data. 

Level 3 
Data or retrieved geophysical parameters which have been spatially and/or temporally re-sampled (i.e. derived from Level 1 or 2 products), usually with some completeness and consistency. Such re-sampling may include averaging and compositing. 

Level 4 
Model output or results from analyses of lower level data (i.e., variables that are not directly measured by the instruments, but are derived from these measurements; could be derived from multiple instrument measurements).

1.
Electronic data package distributable to users; content is derived from instrument data via processing involving ancillary and auxiliary data. Products may comprise metadata and browse images. 

2.
A product may be part of a collection – a distinction useful for archiving and cataloging purposes. 

3.
The term product may be used to denote a product type, such as e.g. ENVISAT_ASAR_L1B_PRI data. 

4.
End users may distinguish between (input, "raw") data and products, i.e. the derived geophysical parameters.

Useful references to published articles about the use of the data and user feedback received by the science and instrument teams about the products. Includes reports of any peculiarities or notable features observed in the products.

The specific implementation of global attributes, dimensions, groups, variables, and variable-level attributes in a data product, which is specified via the Product Format Specification (PFS) file.

The Product Generation Algorithm, the version of source code used to produce the data products, need to be carefully preserved and recorded, along with version history, as well as:

• The algorithm's theoretical (scientific and mathematical) basis,
• How the algorithm is numerically implemented, including possible issues with computationally intensive operations,
• A description of the outputted data products at a level of detail to determine if the product met specified product requirements,
• A description of all assumptions that have been made concerning the algorithm performance estimates and any limitations,
• A list of various error estimates and the error budget.

Description of the impact to product quality due to issues with computationally intensive operations (e.g., large matrix inversions, truncation and rounding).

A document that provides the technical specifications relating to the formatting and content of a particular data product.

Names of key science team leads and product team members (development, help desk and operations), roles, performing organization, contact information, sponsoring agencies or organizations and comments about the products.

PRRs evaluate the readiness of system developer(s) to produce the required number of systems within defined project constraints for projects developing multiple similar flight or ground support systems. PRRs also evaluate the degree to which the production plans meet the system's operational support requirements.

The project plan contains the technical approaches and management plans to implement the project requirements. It defines, at a high level, the scope of the project, the implementation approach, the environment within which the project operates, and the baseline commitments of the program and project. (From NPR 7120.5D)

The information that documents the history of the content information. This information tells the origin or source of the content information, any changes that may have taken place since it was originated, the inputs responsible for a product, what versions of algorithms used, who has had custody of it since it was originated etc. Examples of provenance information could be the principal investigator who recorded the data, and the information concerning its storage, handling, and migration.

One or more unique variables within a data file that show what data quality assessments have been performed as well as diagnostics on various aspects of quality. A quality flag can be a byte value with each bit representing a pre-defined quality verification criterion provided as a Boolean expression.

1. A quality indicator shall provide sufficient information to allow all users to readily evaluate the “fitness for purpose” of the data or derived product. A Quality Indicator may be a number, set of numbers, graph, uncertainty budget, or a simple “flag”.
2. One or more unique variables within a data file whose numerical value shows the overall quality of a geophysical measurement. The numerical value should be on a predefined numerical scale. For example, uncertainty per pixel (or measurement), percent cloud cover (in a scene).

Secondary data required to assess the primary data set’s fitness for purpose, e.g. calibration and validation data and quality control results.

A data product, usually related to a Level 1 or higher Standard Data Product, which is generated and distributed in near-real time.

See: Processing Levels

Reprocessing is a part of processing where a complete product collection is systematically generated to obtain a new revision using archived lower level products. Reprocessing is normally initiated after an improved processing algorithm is released. Reformatting could be considered or conducted as part of a re-processing exercise.

Requirements documents are detailed requirements allocated from the project to the next lower level of the project.

SMSRs prepare Agency safety and engineering management to participate in program final readiness reviews preceding flights or launches, including experimental/test launch vehicles or other reviews as determined by the Chief, Safety and Mission Assurance. SMSRs also provide the knowledge, visibility, and understanding necessary for senior safety and engineering management to either concur or nonconcur in program decisions to proceed with a launch or significant flight activity.

Subset of an instrument acquisition data segment, cut by time i.e. across-swath.

The SDMP describes how the program will manage the scientific data generated and captured by operational mission. The SDMP also includes descriptions of how data will be generated, processed, distributed, analyzed, and archived.

Science data product generation software and software documentation. Source code used to generate products at all levels in the science data processing system.

Datasets and documentation. Accuracy of products, as measured by validation testing, and compared to accuracy requirements. Description of validation process, including identification of validation data sets, measurement protocols, data collection, analysis and accuracy reporting.

Identify all ancillary data or other data sets used in generation or calibration of the data or derived product at all levels

Product access (reader) tools. Software source code that would facilitate use of the calibration data, ancillary data and the data products at all levels.

Most of the EOS standard products are produced at facilities under the direct control of the instrument Principal Investigators/Team Leaders (PIs/TLs) or their designees. These facilities are referred to as Science Investigator-led Processing Systems (SIPS). SIPS are geographically distributed across the United States and are generally, but not necessarily, collocated with the PIs/TLs’ Scientific Computing Facilities. 

Products produced at the SIPS using investigator-provided systems and software are sent to appropriate DAACs for archival and distribution. Level 0 Data Products and Ancillary Data that begin the processing sequence are stored at the DAACs and retrieved by the SIPS.

The procedure to search an archive based on specific search criteria (search) and to obtain information on available products (discovery). Data search and discovery are made possible by searchable metadata and browse image catalogues, as well as a catalogue service for making the catalogue accessible. 

During discovery, following a data search, the user finds data based on search criteria and evaluates if the data found are suitable for their application ('fit for purpose'). The user may then decide to retrieve the data.

A file that contains metadata thoroughly describing the characteristics and content of the file.

Device which transmits an output signal as voltage in response to a physical input stimulus. In Earth observation a distinction between passives sensors, such as radiometers, and active sensors, such as radars, is common. Earth observation sensors – or instruments – are operated from different ground-/water-based, airborne, or spaceborne platforms.

A grouping of science data that all come from the same source, such as a modeling group or institution. Series/collections have information that is common across all the datasets/granules they contain.

Metadata elements that describe an entire set of data files. Values of series/collection metadata apply to all of the files in a specific aggregate. Series/collection metadata may represent the same release of any given file, sets of data generated during an experiment, a campaign or an algorithm test.

The intensity of solar radiation falling upon a unit area of surface, held at right angles to the Sun's rays at a point outside the Earth's atmosphere.

An area on the surface of the Earth or an altitude range covered by a data set.

Method by which location or coverage is designated (e.g., latitude and longitude).

Standard products are agency-certified key products resulting from missions or projects. They are typically acquired systematically and generated by spatially and temporally extensive systematic processing.