Office of Science Quality and Integrity

Distinctions Between New Research or Interpretive Information Products, Previously Published Interpretive or Noninterpretive Scientific Information Products, and Scientific Data

Updated May 2021

This document provides guidance to U.S. Geological Survey (USGS) employees on distinguishing between the terms "new research or interpretive information products," and "previously published or noninterpretive information products" used by the Bureau and how these often confusing terms relate to levels of Bureau approval for USGS publications, web pages, and scientific data. The USGS considers data as noninterpretive information. These distinctions are important because Survey Manual (SM) chapter SM 205.18 - Authority to Approve Information Products1 specifies different Bureau approval authorities for new research or interpretive information products, (also known as "new interpretive") and previously published or noninterpretive information products. Bureau Approving Officials (BAOs) in the Office of Science Quality and Integrity (OSQI) are responsible for approving all new interpretive information products. The responsibility for approving all other information products rests with the Science Center Director (SCD), who also has discretion to request approval by a BAO for any product under their SCD approval authority.

The responsibility for making the distinction between new interpretive information products and the other products described in this document resides with the SCD. A BAO in the OSQI should be contacted for guidance if there is any doubt in making this distinction. Additional guidance is provided in a related decision workflow Distinguishing Noninterpretive, Interpretive and New Interpretive USGS Information Products.

 

Publications and Web Pages

A USGS scientific information product2 (referred to in this guidance as publications or information products) is the compilation of scientific communication or representation of knowledge such as facts, data, or interpretations in any medium (for example, print, digital, web) or form (includes textual, numerical, graphical, cartographic, and audiovisual forms), for release or dissemination by the USGS or a non-USGS entity to a defined external audience or customer. USGS information products have at least one Bureau-affiliated author (refer to SM 502.4). The term scientific “information product” encompasses other terms used in the Bureau, including but not limited to “publication,” “data product,” and “map product.”

The guidance and the examples below for noninterpretive, interpretive, not new interpretive and new interpretive information products (that are publications and web pages) excludes scientific data. Refer to the separate guidance and examples for scientific data also below.

 

Noninterpretive

Noninterpretive information products contain only statements that are primarily factual or observational in nature. They provide information about who did the research (collected the data), what research was done, and how, when, where, and why the research was done. These products do not provide an interpretation of what the data or observations mean. Noninterpretive information products may provide bibliographic citations and Internet links to interpretive products. Noninterpretive information products may be released in USGS publication series, outside publications, posters and presentation materials, on USGS web pages, or through various other methods.

Examples of Noninterpretive Information Products (Publications and Web Pages):

  • A USGS Fact Sheet summarizing published research findings.
  • A project progress report on continuing research that discusses allocation of funds and effort but does not discuss said results or establish their meaning (refer to frequently asked questions on Reporting of Project Progress).
  • A description of a USGS program, study, or organizational activity that may include the purpose, scope, objectives, and approach but not results.

 

Interpretive

Interpretive information products contain information about the interpretation or meaning of scientific observations or data. These products might test or discuss scientific hypotheses, evaluate scientific methods, extrapolate from observations to predictions, patterns, or explore the consequences of assumptions. An information product, regardless of the venue or form of its dissemination, is treated as interpretive if anything in it is interpretive. Interpretive products may also selectively address the meaning of the work of others. There are two types of interpretive products—interpretive information products based on previously published information (not new) and new interpretive information products based on unpublished information.

 

Not New Interpretive

Not new interpretive information products are a subset of interpretive information products that represent secondary uses of previously published interpretive information. Not new interpretive information may be released in USGS publication series, outside publications, posters and presentation materials, on USGS web pages, or through various other methods.

Examples of Interpretive Information Products (Publications and Web Pages) based on previously published (not new) information:

  • Secondary uses of previously published interpretive information. For example, products that present the information to a new audience or in a new format, or are considered interpretive products that do not contain new information.
  • A USGS publication series Fact Sheet that includes information summarizing previously published interpretive scientific information products.
  • A USGS project website summarizing research results from previously published reports or information products.
  • A previously approved and published model used for simulation of scenarios by revising one or more parameters (such as pumping stresses).

 

New Interpretive

New USGS interpretive information products are a subset of interpretive information products that contain assertions or interpretations or use methods that have not been previously published. A synthesis of previously published information, if new conclusions are drawn, is also considered new interpretive information. New USGS interpretive information products may also be referred to as new research. Note that as stated above, secondary uses of previously published interpretive information products (such as USGS fact sheets) that present the information to a new audience or in a new format, are not considered new interpretive products. New interpretive information products can only be released in the appropriate USGS publication series, in outside publications, or in abstracts and presentation materials.

Examples of New Interpretive Information Products (Publications):

  • Making predictions of future occurrences from a model.
  • Establishing criteria to be used for visual identification of species.
  • Discussion of what caused the changes in oceanographic salinity since 1900.
  • Argument for a new method of calculating salinity from basic measurements, with a dataset of values calculated using the new method.
  • Maps of predicted habitats for particular species that use salinity as a delimiting parameter.
  • Initial development of a scientific model.
  • Original creation of a classification system for soil or biota.
  • Journal and other original articles based upon new science.
  • USGS publications series information products based upon new science.
  • Review of the work of others (including book reviews, literature reviews, synthesis reports, and book chapters).
  • Response to criticism of work by self or others (rebuttals and responses to critiques).
  • Revisions of previously published new interpretive information.
  • Maps or datasets derived from extrapolated methods such as geologic structure maps.
  • Age assignment to a sample based on a set of published criteria or analytical methodologies to create a data point, or a collection of such data.

 

Scientific Data

Scientific Data3 are observations or measurements represented as text, numbers, or multimedia. USGS does not consider scientific data to be interpretive. Data are created by using either a citable standard process or method, a newly developed process, or a process that is interpretive. The data creation processes must be documented in the metadata record for that data. When data are created by using a newly developed process or an interpretive process, that process must be fully documented in a peer reviewed publication (e.g., USGS series product, journal article). This could be a USGS techniques and methods report if the process is repetitive. Likewise, for a geologic map represented as a geographic information systems (GIS) coverage or for uniquely interpretive data (such as a contour line) from a groundwater model simulation, an associated peer reviewed information product is required to explain how these data are derived. In all cases the methods used to create data must be included as part of the complete metadata record. For data resulting from an interpretive process this is achieved by including a Digital Object Identifier (DOI) in the metadata that resolves to the peer-reviewed publication documenting the methods or interpretations used to create the data. All USGS data approved for release must contain complete metadata records; that is, the examples given below would be accompanied by a complete metadata record.

Examples of Scientific Data That Can Stand Alone:

Measurements

  • Field measurements, such as stream stage, temperature, conductivity, pressure, or simple chemical analysis, with metadata providing information about 'who, where, when, how, and why' the measurements were made (i.e., standard field-form data).
  • Streamflow or other surface-water measurements derived from published or industry standard methods or guidelines.
  • Data acquired from remote sensors; electrical signals transformed to numeric values.
  • Analytical geochemistry concentrations collected directly from in situ instrumentation.
  • Raw geophysical well logs.
  • Locational data, in point or map form, including data acquired from GPS, lidar, or other surveying techniques.

Observations

  • Direct observations of weather parameters.
  • Field recognition, such as of rock types or bird calls, based on experience and skill at classification, preferably accompanied by a naming reference used.
  • Indirect observational data, such as Landsat images that are acquired regularly.
  • Images of organisms as records of which taxa were present at a particular place and time.
  • Photographic records of natural phenomena, including floods, earthquake damage, landslides, phenology, and other landscape-scale events.
  • Lab-based visual identification of taxa by using published criteria.

Derived Data

  • Movement tracks of radio-tagged animals, converting a dataset consisting of space-time coordinates into distance, speed, and direction values.
  • Data transformations that use a well-documented or published, calibrated model or algorithm (for example, transforming stage or velocity data from USGS stream-gaging stations into flow data).
  • Calculated values based on an algorithm involving other data (metadata describes source data, calculations and procedures); examples include calculated 'water depth' using gaged water-level heights and ground-elevation, calculated parameter 'loading' using 'concentration x streamflow x correction factor', and calculated 'whole-sample' water-quality parameters and metrics (salinity, hardness, alkalinity, conductivity, ion balance).
  • Simple visualizations of data, either as original values or in simple derived forms, such as time-series graphs of earthquake data, or aggregate population maps based on census data.
  • Salinity data transformed into two- and three-dimensional visualizations, using standard or well-described procedures for the interpolation among calculated point values (metadata provides original salinity values and interpolation and visualization methods).
  • A compilation of visualizations showing changes in salinity since 1900, with metadata providing information about the sources of the information and the change calculation.

Acquired Data

  • Data acquired from access points provided by the data owner and from web services or systems such as:
    • National Water Information System (NWIS)
    • BioData Retrieval
    • Ocean Biogeographic Information System (OBIS)
    • Biodiversity Information Serving Our Nation (BISON)
    • Breeding Bird Survey (BBS)

 

Examples of Scientific Data That Must Reference an Associated Interpretive Information Product:

Modeled and Generated Data

  • Maps of species distributions based on habitat models and tag-and-recapture survey data (habitat model used must be referenced).
  • Data shared as a GIS coverage file associated with or derived from a geologic map (published geologic map must be referenced).
  • Model-generated datasets, such as from a climate model, in which the model is available and citable (metadata includes model citation and the configuration details used to generate the dataset).
  • Estimated streamflow load data calculated by using regression or other models (publication describing the process must be referenced in metadata).

1SM 205.18 - Authority to Approve Information Products makes a distinction related to approval authority between New Research or Interpretive Information Products and Previously Published or Noninterpretive Information Products.
2Scientific information product definition as stated in SM 502.1 – Fundamental Science Practices: Foundation Policy.
3Data Administration and Management Association (DAMA) definition of "data": Facts represented as text, numbers, graphics, images, sound or video. Data are the raw material used to create information. The DAMA definition of "model": An abstract representation of how something is built or how it works. A data model (a model that defines how data are connected to each other and processed and stored within the model system) is a static model. Process models and financial models can be dynamic, used as a means to simulate the real world. The DAMA definition of "information": Data in context. The interpretation of data based on its context, including the (1) the business meaning of data elements and related terms, (2) the format in which the data are presented, (3) the timeframe represented by the data, and (4) the relevance of the data to a given usage. Note: Information is being used inclusively to include data. (Refer to https://www.dama.org).

 

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