Best Practice: Describe

Select a Best Practice below to learn more about the “Describe” stage in the Data Life Cycle.

What is the “Describe” stage?

Document data by describing the why, who, what, when, where, and how of the data. Metadata, or data about data, are key to data sharing and reuse, and many tools such as standards and software are available to help describe data.

More information can be found in the Best Practices Primer.

Assign descriptive file names


File names should reflect the contents of the file and include enough information to uniquely identify the data file. File names may contain information such as project acronym, study title, location, investigator, year(s) of study, data type, version n... (click for more)

Tags: access   describe   discover   format

Choose and use standard terminology to enable discovery


Terms and phrases that are used to represent categorical data values or for creating content in metadata records should reflect appropriate and accepted vocabularies in your community or institution. Methods used to identify and select the proper termin... (click for more)

Tags: controlled vocabulary   describe   documentation   metadata   ontologies   preserve   standards

Confirm a match between data and their description in metadata


To assure that metadata correctly describes what is actually in a data file, visual inspection or analysis should be done by someone not otherwise familiar with the data and its format. This will assure that the metadata is sufficient to describe the da... (click for more)

Tags: assure   data consistency   describe   documentation   metadata   quality

Create a data dictionary


A data dictionary provides a detailed description for each element or variable in your dataset and data model. Data dictionaries are used to document important and useful information such as a descriptive name, the data type, allowed values, units, and ... (click for more)

Tags: controlled vocabulary   describe   documentation   metadata   terminology   units

Define the data model


A data model documents and organizes data, how it is stored and accessed, and the relationships among different types of data. The model may be abstract or concrete. (click for more)

Tags: access   data model   describe   plan

Define the parameters


The parameters reported in the data set need to have names that clearly describe the contents. Ideally, the names should be standardized across files, data sets, and projects, in order that others can readily use the information. (click for more)

Tags: describe   documentation   metadata   parameter

Describe format for spatial location


Spatial coordinates should be reported in decimal degrees format to at least 4 (preferably 5 or 6) significant digits past the decimal point. An accuracy of 1.11 meters at the equator is represented by +/- 0.00001. This does not include uncertainty intr... (click for more)

Tags: access   describe   format   geospatial   location

Describe formats for date and time


For date, always include four digit year and use numbers for months. For example, the date format yyyy-mm-dd would appear as 2011-03-15 (March 15, 2011). (click for more)

Tags: date   describe   format   standards   time

Describe measurement techniques


Data measurement descriptions should: (click for more)

Tags: access   calibration

Describe method to create derived data products


When describing the process for creating derived data products, the following information should be included in the data documentation or the companion metadata file: (click for more)

Tags: analyze   data processing   describe   provenance

Describe the contents of data files


A description of the contents of the data file should contain the following: (click for more)

Tags: describe   documentation   format   metadata   parameter   units

Describe the overall organization of your dataset


Data sets or collections are often composed of multiple files that are related. Files may have come from (or still be stored in) a relational database, and the relationships among the data tables or other entities are important if the data are to be reu... (click for more)

Tags: data model   database   describe   documentation   metadata

Describe the research project


The research project description should contain the following information: (click for more)

Tags: annotation   data creators   describe   geography   geospatial   measurement

Describe the sensor network


If your project uses a sensor network, you should describe and document that network and the instruments it uses. This information is essential to understanding and interpreting the data you use, and should be included as a part of the metadata generate... (click for more)

Tags: calibration

Describe the spatial extent and resolution of your dataset


The spatial extent of your data set or collection as a whole should be described. The minimum acceptable description would be a bounding box describing the northern most, southern most, western most, and eastern most limits of the data. (click for more)

Tags: describe   documentation   geospatial   location   measurement   metadata

Describe the temporal extent and resolution of your dataset


The temporal extent over which the data within your dataset or collection was acquired or collected should be described. Normally this is done by providing (click for more)

Tags: date   describe   documentation   measurement   metadata   time

Describe the units of measurement for each observation


The units of reported parameters need to be explicitly stated in the data file and in the documentation. We recommend SI units (The International System of Units) but recognize that each discipline has its own commonly used units of measure. The critica... (click for more)

Tags: describe   measurement   units

Document and store data using stable file formats


File formats are important for understanding how data can be used and possibly integrated. The following issues need to be documented: Does the file format of the data adhere to one or more standards? Is that file standard an open (i.e. open source... (click for more)

Tags: documentation   format   metadata   preserve   storage   tabular

Document steps used in data processing


Different types of new data may be created in the course of a project, for instance visualizations, plots, statistical outputs, a new dataset created by integrating multiple datasets, etc. Whenever possible, document your workflow (the process used to c... (click for more)

Tags: analyze   data processing   describe   integrate   provenance   replicable data

Describe the overall organization of your dataset


Identification of any species represented in the data set should be as complete as possible. (click for more)

Tags: describe   metadata   standards   taxonomy   terminology

Document your data organization strategy


The following are strategies for effective data organization: Sparse matrix: Optimal data models for storing data avoid sparse matrices, i.e. if many data points within a matrix are empty a data table with a column for parameters and a column for val... (click for more)

Tags: data management plan   data model   data normalization   database   describe

Ensure flexible data services for virtual datasets


In order for a large dataset to be effectively used by a variety of end users, the following procedures for preparing a virtual dataset are recommended: (click for more)

Tags: data archives   data services   describe   preserve

Identify and use relevant metadata standards


Many times significant overlap exists among metadata content standards. You should identify those standards that include the fields needed to describe your data. In order to describe your data, you need to decide what information is required for data us... (click for more)

Tags: controlled vocabulary   describe   documentation   format   metadata   preserve

Maintain consistent data typing


Choose the right data type and precision for data in each column. As examples: (1) use date fields for dates; and (2) use numerical fields with decimal places precision. Comments and explanations should not be included in a column that is meant to inclu... (click for more)

Tags: database   describe   documentation   format   metadata

Provide a citation and document provenance for your dataset


For appropriate attribution and provenance of a dataset, the following information should be included in the data documentation or the companion metadata file: (click for more)

Tags: citation   data creators   data source   describe   preserve   provenance

Provide capabilities for tagging and annotation of your data by the community


People have different perspectives on what data means to them, and how it can be used and interpreted in different contexts. Data users ranging from community participants to researchers in different domains can provide unique and valuable insights into... (click for more)

Tags: annotation   controlled vocabulary   describe   documentation   metadata

Provide identifier for dataset used


In order to ensure replicable data access: (click for more)

Tags: access   data consistency   describe   preserve   provenance   replicable data

Separate data values from annotations


A separate column should be used for data qualifiers, descriptions, and flags, otherwise there is the potential for problems to develop during analyses. Potential entries in the descriptor column: (click for more)

Tags: annotation   describe   documentation   flag   format   metadata

Sharing data: legal and policy considerations


All research requires the sharing of information and data. The general philosophy is that data are freely and openly shared. However, funding organizations and institutions may require that their investigators cite the impact of their work, including sh... (click for more)

Tags: access   citation   data creators   data source

Use appropriate field delimiters


Delimit the columns within a data table using commas or tabs; these are listed in order of preference. Semicolons are used in many systems as line end delimiters and may cause problems if data are imported into those systems (e.g. SAS, PHP scripts). Avo... (click for more)

Tags: access   collect   describe   format

Use consistent codes


Be consistent in the use of codes to indicate categorical variables, for example species names, sites, or land cover types. Codes should always be the same within one data set. Pay particular attention to spelling and case; most frequent problems are wi... (click for more)

Tags: coding   collect   controlled vocabulary   describe   ontologies