Presentation on theme: "Writing Metadata. First records are the hardest. Not all fields may need to be filled in. Tools are available. Training classes can be taken. Can often."— Presentation transcript:
First records are the hardest. Not all fields may need to be filled in. Tools are available. Training classes can be taken. Can often be produced automatically. Can (and should) be reviewed for updates. It’s not so bad!
Writing Metadata Organize your information Write your metadata file Review your file Have someone else review ReviseRevise PublishPublish Six Steps for Writing Quality Metadata.
Before you begin writing, get organized. Document your data as you go. Write so others can understand. Always review your document. Writing Metadata
Items required Sense of Humor! Chocolate FGDC Workbook Metadata entry tool Coffee
Write simply but completely. Document for a general audience. Be consistent in style and terminology. Keep your readers in mind. Writing Metadata
Define all acronyms. Avoid using jargon. Clearly state data limitations. Keep your readers in mind. Writing Metadata
Write a complete title that includes: What Where When Scale Who Writing Metadata
The title is critical in helping others find your data. Which is better? Greater Yellowstone Rivers from 1:126,700 Forest Visitor Maps ( ) Rivers Writing Metadata
Be specific. Quantify when you can. Vague: We checked our work and it looks complete. Specific: We checked our work using 3 separate sets of check plots reviewed by 2 different people. We determined our work to be 95% complete based on these visual inspections. Writing Metadata
Select your key words wisely. Do not use ambiguous words. Use descriptive words. Fully qualify geographic locations. Writing Metadata
Have someone else read it. If you’re the only reviewer, put it away and read it again later. Check for clarity and omissions. Review your final product. Writing Metadata
Can a novice understand what you wrote? Are your data properly documented for posterity? When you review your work, ask: Writing Metadata
Does the documentation present all the information needed to use or reuse the data? Are any pieces missing? When you review your work, ask: Writing Metadata
Your audience may be very diverse. Consider writing your metadata to reflect this diversity.
Summary Metadata gets easier as you go along Start with a dataset (or 2) that you are familiar with Follow up with data sets that you/your organization use for many applications Gain momenum and keep it.
Metadata Creation and Validation Tool Time
Tools for metadata creation NOAA CSC MetaScribe Allows you to create a template record that can be used to create large numbers of similar records. NOAA CSC ArcView Metadata Collector Extension for ArcView 3.x that allows user to capture metadata specific to a particular ArcView data set. TKME Straightforward text editor for metadata. Good tool for making structural corrections to a record. ESRI ArcGIS metadata tool Found within the new ArcGIS application, this tool allows you to generate metadata for any ArcGIS data set.
Metadata Creation Tools TKME An editor for formal metadata, TKME is intended to simplify the process of creating metadata that conform to the standard.
NOAA CSC ArcView ® Metadata Collector The ArcView® Metadata Collection Tool was developed by the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center. This tool collects and compiles Federal Geographic Data Committee (FGDC)- compliant metadata for ARC/INFO coverage's, shapefiles, grids and supported image formats. Metadata Creation Tools (add-on to ArcView 3.x)
MetaScribe This new tool was also developed by the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center to aid in the creation of multiple sets of metadata that exhibit a high degree of redundancy. Metadata Creation Tools
ArcGIS metadata collector Found in ArcCatalog, this tool allows the user to write metadata within the Arc environment. This is what we will be using to support the development of metadata for the Virginia Metadata Clearinghouse….
CNS (“Chew ‘n Spit”) A pre-parser for formal metadata designed to assist metadata managers convert records that cannot be parsed by mp into records that can be parsed by mp. Metadata Validation Tools MP (Metadata Parser) A compiler to parse formal metadata, checking the syntax against the FGDC Content Standard for Digital Geospatial Metadata and generating output suitable for viewing with a web browser or text editor.
TKME, CNS, and MP are available as free downloads from the United States Geological Survey (USGS) Website. (geology.usgs.gov/tools/metadata) TKME will run from a shortcut on the desktop, but both MP and CNS must be run from a command line in MS-DOS or UNIX. Metadata Validation Tools
Finally... Remember, metadata is an integral component of your data, and is vital for data sharing between organizations. Metadata can also provide many benefits at various levels within organizations by making the process of data management more streamlined and efficient.
Institutionalizing Metadata in Your Organization
Approach metadata development from a business perspective Build administrative support Preserves data investment Limits liability Helps manage data resources Aids in external data acquisition Facilitates data access and transfer Provides for efficient data distribution Make metadata part of the process
Stress the individual benefits of metadata Build technical support Reduces workload over the long term Field fewer data inquiries Provides a means of documenting personal contributions Facilitates sharing of reliable information Make metadata part of the process
Develop strong staff support Incorporate metadata expectations into job descriptions and performance standards Build technical support Provide staff development opportunities The three “T’s” Training Tools Time Make metadata part of the process
Develop templates to facilitate efficient and consistent metadata creation Build organizational support Identify pertinent fields within the metadata structure Populate fixed fields Use standardized language Define distribution methods Cite standards used Build source and contact libraries Make metadata part of the process
Map metadata fields to the work flow Distribute the effort Technicians – lineage Analysts – process and methodology Field Scientists – accuracy assessments I.T. Managers – tools, automated collection methods, information management Make metadata part of the process Establish and assign responsibilities
Mandate the use of standards and templates Develop boilerplate metadata-deliverable language for data contractors Require publication of metadata Create and publish standard operating procedures to document metadata policies and procedures Establish standard policies Make metadata part of the process