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An Introduction to Metadata. Tammy Walker Beaty Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, TN beatytw@ornl.gov Data Management Practices for Early Career Scientists NASA Terrestrial Ecology Science Team Meeting May 2, 2013. An Introduction to Metadata.
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An Introduction to Metadata Tammy Walker Beaty Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, TN beatytw@ornl.gov Data Management Practices for Early Career Scientists NASA Terrestrial Ecology Science Team Meeting May 2, 2013
An Introduction to Metadata • What is Metadata? • Why do we need Metadata? • Who uses Metadata? • Where does Metadata come from? • When do you prepare Metadata? • How do I prepare Metadata and how will it be used?
What is Metadata? Who Who collected the data? Who processed the data? Who wrote the metadata? Who to contact for questions? Who to contact to order? Who owns the data? What What are the data about? What project were they collected for? What is the quality? What parameters were measured? What format are the data in? What are appropriate uses? Where Where were the data collected? Where were the data processed? Where are the data located? When When were the data collected? When were the data processed? How How were the data collected? How were the data processed? How do I access the data? How much do the data cost? How was the quality addressed? Why Why were the data collected? 3
Why do we need Metadata? Metadata is the language of Data Metadata Forms Documentation Metadata enables Management of the data including: Discovery Access Use The adjectives adverbs of data Who, What, Where, When, Why, and How Which one, What kind, How many/how much, Whoes
Who uses Metadata? Everyone uses metadata We use metadata without knowing it We use metadata to “know” data Coke? Tuna or Cat food?
Where does Metadata come from? Here is a data file Here is the same data file with metadata Which one is useful? Metadata comes from knowing the data
How do I prepare Metadata and how will it be used? Ideally you prepare metadata while you are working with, collecting, and preparing data Document your research as you conduct it Use an xml editor (oxygen, morpho, etc) Best Practices, http://daac.ornl.gov/PI/BestPractices-2010.pdf Multiple Metadata Standards Exist (see additional slides for examples) FGDC, ISO 19115, EML, Darwin Core, etc .: - Choose one and go for it Metadata is used to identify, locate, understand and explain the data (Google, custom viewers, etc)
What does Metadata look like? Ideally you prepare metadata while you are working with, collecting, and preparing data Document your research as you conduct it Best Practices, http://daac.ornl.gov/PI/BestPractices-2010.pdf Multiple Metadata Standards Exist (see additional slides for examples) FGDC, ISO 19115, EML, Darwin Core, etc .: - Choose one and go for it Metadata is used to identify, locate, understand and explain the data (Google, custom viewers, etc)
Metadata Examples One set of Metadata displayed 3 ways
Multiple metadata standards exist Content Standard for Digital Geospatial Metadata (CSDGM) Federal Geographic Data Committee (FGDC) Emphasis on geospatial data; environmental sciences Includes: Biological Data Profile (BDP) Darwin Core Emphasis on taxa - observations, specimens, and samples Dublin Core Element Set Emphasis on describing resources for discovery (video, images, web pages, and physical resources books, objects) Ecological Metadata Language (EML) Emphasis on documentation of ecological data ISO 19115 Geographic information: Metadata Emphasis on geospatial data and services 11
Multiple metadata editors exist CatMDEdit – ISO 19115, open source FGDC Metadata Editor for ArcGIS 10 DCMI Tools & Software – Dublin Core oXygen – ISO 19115, commercial Morpho – EML Editor Many others 12
Metadata is the language of data • Metadata are the descriptors of data that make it useful (the adverbs and adjetives) • Metadata enables data to speak to us so that we can understand and use it. • Who, What, Where, When, How, and Why • Metadata transforms data into a data set • (Metadata + Data) = Data Set • (Data Set – Metadata) = Mystery
Data Collection CC image by CIMMYT on Flickr CC image by SEDAC on Flickr CC image by Justin See on Flickr CC image by acordova on Flickr CC image by ISAS on Flickr CC image by kukkurovaca on Flickr