Metatab and Metapack

Metatab is a way of writing and storing metadata in the same spreadsheet as a dataset. Because it uses a tool every user already has — a spreadsheet — it is much simpler than documenting metadata in XML or JSON, resulting in more public datasets being properly documented. Metadata is easily read by people and can be programmatically converted to machine formats like JSON, so, with a spreadsheet extension, metadata can be validated while users enter it, and the metadata allows for sophisticated automatic processing.

Metatab is a core part of Metapack, a data packaging format that uses Metatab formatted metadata files for building ZIP, Excel and Directory based data packages.

The Metatab/Metapack system includes:

• A specification for how to write standard metadata elements in a tabular format
• CLI Programs for building metadata files and data packages
• Code libraries for parsing and manipulating Metatab data

We also have demonstrations of:

• Spreadsheet extensions that help users create valid metadata
• A web service that supports the spreadsheet extensions

The core of the project is the Metatab data format, which allows complex information to be represented in a simple, readable way in a spreadsheet. Using Metatab, a data producer can open a dataset in a spreadsheet, and quickly create valid metadata that conforms to standards. After publication, Data consumers can read and understand the metadata with no training and no additional tools.

Here are two examples, one in a Google spreadsheet and another in Excel.

Get Metatab

The Metatab project is just getting started, and we need your help.

• Data Producers. We’re looking for government agencies who produce public data to provide input on their data workflows and other requirements.
• Data Consumers. If you use public data and would like better metadata, knowing what you need will help us get the project funded.

For more information, contact: Eric Busboom.

Tabular Metadata

property	value
Title	An Example Data bundle
Title.language	en
Description	This data bundle is an example of how simple a data bundle can be.

RDF Metadata

<?xml version="1.0"?>
<!DOCTYPE rdf:RDF SYSTEM 
 "http://dublincore.org/2000/12/01-dcmes-xml-dtd.dtd">
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
         xmlns:dc="http://purl.org/dc/elements/1.1/">
  <rdf:Description >
    <dc:title>An Example Data bundle</dc:title>
    <dc:description xml:lang="en">This data bundle is an 
    example of how simple a data bundle can be.</dc:creator>
  </rdf:Description>
</rdf:RDF>

Workflow

Using Metatab is simple. A typical public data workflow with Metatab would involve:

• A user opens a spreadsheet of data, then adds the Metatab extension to the spreadsheet.
• The Metatab extension creates new worksheets for metadata and a schema, also known as  a data dictionary. Metatab reads the data and automatically generates the data dictionary.
• As the user types, the Metatab extension validates the user’s entries, ensuring the metadata is always valid.
• When the user is finished, the file can be saved directly to a data repository like Socrata or CKAN.

Always Correct

The Metatab spreadsheet extension — for both Excel and Google Docs — validates metadata as the user types to ensure that it is always correct. By including a ConformsTo element, users can set the standard used to validate the metadata. By creating a ConformsTo document (which is also a Metatab format file) and making it available on the web, organizations can create their own extensions to metadata elements.