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DIY metadata

Government portals, libraries, and other data repositories often use slightly different metadata standards for powering discovery of their data resources.

If you are creating your own data, or reshaping data you have found so it is easier to work with for some purpose, you might not always know the exact contextual information to provide so the data can be the most widely discovered, understood, and used.

This guide provides a template for creating documentation for GIS data projects that well-positions them for discovery and use.

Tips

Completeness

Incomplete context is always better than no context. If you don’t know the answers to everything included in this template, try to populate as much as you can.

Documentation elements

Originator(s)

The name(s) of the organization(s) or individual(s) who developed the dataset.

Publication Date

The date when the dataset is published or otherwise made available for release.

Calendar Date(s) of the Content

The date, dates or date range describing the content of the dataset.

Title

A title for the dataset.

Geospatial Data Presentation Form

The mode in which the geospatial data are represented.

Examples: “vector digital data”

Abstract

A brief narrative description of the dataset.

Motivations

The reason why the dataset was developed or intentions for its use. If you created the data yourself, or augmented existing data, how does the work add value to the current data landscape. In other words, what are the project’s successes?

Data sources

If you obtained data from elsewhere and edited it, the source of the original datasets and date accessed.

Process steps and methods

A sequential explanation of the step-by-step process for creating or editing the data.

Challenges

Challenging aspects of working with the data, or words-to-the-wise for someone else endeavoring to work with it.

Relationships

If there are multiple datasets in the project, processing scripts, or other resources, the filenames and how the materials relate to or were used with one another.

Data integrity

If values are missing, or fields are blank, instructions for future users for making sense of possible reasons why.

Codebooks

If you cleaned data, deleted, renamed, mathematically calculated or inferred fields from other fields, the filename and link to a plain-text codebook with field name definitions, including units of measurement.

Maintenance and Update Frequency

How often you intend to update or maintain the data layers.

Examples: “annually”, “never updated”

Point of contact

Contact information for an individual or organization that is knowledgeable about the dataset (person/organization, e-mail, etc.).

Access Constraints

Restrictions on access to the data.

Use Constraints

Restrictions on the use of the data.