0. Tutorials on Data Management
Lesson 7: Metadata
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1. Lesson Topics Explanation of metadata
Illustrate the value and utility of metadata to data users, data providers, and organizations
Examine information included in a metadata record
Examples of metadata standards and how to choose
Preparing to write metadata
Tips for writing a quality metadata record
In this segment of the course we will cover:
What is metadata?
What are examples of metadata in our daily lives?
And what information needs to be included in a metadata record?
CC image by Alec Couros on Flickr

2. Learning Objectives
After completing this lesson, the participant will be able to:
Identify and list the types of information typically included in metadata records for environmental datasets
Identify 3 reasons metadata is of value to data users, data developers, and organizations
List 3 uses for metadata, beyond discovery of data
Identify and describe factors that may determine which metadata standards are most appropriate for a given dataset
List steps to prepare to write metadata
Explain how to write good metadata

3. The Data Life Cycle Plan Collect Assure Describe Preserve Discover
Integrate
Analyze
Writing metadata falls within the “Describe” portion of the Data Life Cycle.

4. What is Metadata? Metadata is: Data ‘reporting’ WHO created the data?
WHAT is the content of the data?
WHEN were the data created?
WHERE is it geographically?
HOW were the data developed?
WHY were the data developed?
Photo by Michelle Chang. All Rights Reserved
Metadata is data about data. It describes the content, quality, condition, and other characteristics of a dataset.
Metadata records answer questions such as:
Why was the dataset created?
What processes were used to create the dataset?
What projection are the data in?
When were the data last updated?
Who created the data?
What scale was used?
What fields are in the table?
What do the values in those fields mean?
Who do I contact about getting more information about the data?
How do I obtain a copy of the data?
Do the data cost anything?
Are there any limitations to the data?
Metadata is a valuable tool. Metadata records preserve the usefulness of data over time by detailing methods for data collection and dataset creation. Metadata greatly minimizes duplication of effort in the collection of expensive digital data and fosters the sharing of digital data resources.

5. Metadata in Real Life Metadata is all around…
CC image by Mskadu on Flickr
CC image by USDAgov on Flickr
Author(s) Boullosa, Carmen.
Title(s) They're cows, we're pigs /
by Carmen Boullosa
Place New York : Grove Press, 1997.
Physical Descr viii, 180 p ; 22 cm.
Subject(s) Pirates Caribbean Area Fiction.
Format Fiction
Metadata is all around us. . .from Mp3 players, to nutrition labels, to library card catalogues.
For example, a card catalogue tell us more information than just the title of the book, they also tells the user:
Who is the author?
Who published the book?
What subject area does the book fall in?
And finally, where is it located in the library?
Another example of metadata that we see in our daily lives is the nutrition and ingredient information on food labels.
Nutrition labels answer questions such as:
What ingredients were used?
Who made the food?
How many calories per serving?
How many servings in the can?
What percentage of daily vitamins are in each serving?

6. Metadata: What are they good for?
Data Discovery
DataONE: enables exchange
Metadata are essential for capturing information and data discovery. For example, a metadata record submitted to a catalog, such as the USGS Science Data Catalog, enables discovery of data; subsequently, the same metadata can be exchanged with broader data catalogs with services such as DataONE.
Elements such as Title, Description, and Keywords enable users to discover data based on topical searches. Spatial and temporal elements allow users to discover data based on the geographical location or the time period of the data.
USGS Science Data Catalog: enabling discovery
Metadata: captures information

7. Metadata: Why are they important?
Scientific Understanding and Reuse
Information Content
Time
Time of data development
Specific details
General details
Retirement or
career change
Accident
Metadata are also very important for understanding and reusing scientific data. At the time of data development, scientists know the most about their dataset and the steps that were taken to create it. Over time, memory of the details begins to fade. Circumstances in life can intervene, and eventually the knowledge about the dataset is gone. Without a metadata record, information about the dataset could be lost forever, therefore, making the data unusable.
This graph illustrates the phenomenon of “information entropy”, associated with research. At the time of the research project, a scientists memory is fresh. Details about the development of the dataset are easily recalled, and it is a good time to document information about the process. Over time, memory of the details begins to fade. A variety of circumstances can intervene, and eventually detailed knowledge about the dataset fades. Without a metadata record, this data might be unusable. A dataset it not considered complete without a metadata record to accompany it.
Death
(modified from Michener et al. 1997)

8. Metadata: Why are they important?
Defending policy decisions based on data
Regulatory decisions based on undocumented data are not defensible
Metadata accuracy and details are important as supporting evidence for the science and policy
Controversies arise when metadata are incomplete and/or absent
Regulatory agencies depend on metadata to defend the science behind decisions. If regulatory decisions are based on data that have no associated metadata or poor quality metadata, those decisions will not hold up in court. It is important to have accurate and detailed metadata records for supporting claims and policies. For example, the date when data are collected should be as specific as possible. In many situations, simply including the year that data were collected may not be sufficient.
Controversies can arise when metadata are incomplete or absent. For example, the USGS is the research arm of the Department of the Interior (DOI). They are tasked with providing sound and unbiased data, and data interpretation, for resource management decisions made by their sister agencies in the Department. Those decisions can be controversial and often, they are challenged in court. The data used to make those management decisions must be sufficiently documented so as to be transparent and reproducible to a third party attempting to connect the dots and reach a similar conclusion. If USGS data lack sufficient documentation, they cannot be used towards decision making.
It is difficult to find real-world examples of the costs of poor metadata. Agencies don’t like to admit these shortcomings; however, Tom Chatfield, a data management expert with the Bureau of Land Management (BLM) bravely shared one real example from his own agency. A particular BLM field office developed an overall resource management plan for its region which included a map of oil and gas potential for its area. Naturally, this is an issue that registers strong opinions both for and against oil and gas recovery on public lands. When reviewed in the advent of litigation, BLM discovered that no Data Quality information existed for the map. No data sources could be identified, nor was there any discussion of the analysis methodology by which the oil and gas potential information was developed for the map. No geologic or geographic data were identified.
This was potentially disastrous in terms of defending the resource management plan. BLM was forced to develop a brand new map and closely document the provenance of the source data and methodology used to determine the potential ratings on the map. The cost exceeded several thousands of dollars in staff time and production costs, not to mention the intangible costs of loss of trust in the agency by partners and the public.

9. The Value of Metadata Metadata helps… Data developers Data users
Metadata is useful to Data Users, Data Developers, and Organizations. In this era of data sharing, collaboration, and need for information organization, metadata can serve multiple purposes.
Organizations

10. What is the Value to Scientists, Researchers, and other Data Creators ?
Metadata allows data developers to:
Avoid data duplication
Share reliable information
Publicize efforts – promote the work of a scientist and his/her contributions to a field of study
Metadata reuse saves time and resources in the long-run
What value does metadata have to Scientists, Researchers, and other Data Creators?
Metadata records will help avoid data duplication because researchers can determine if data already exist. Scientists are able to share reliable information about a dataset by creating metadata and passing it along with the dataset. Scientists wishing to reuse a dataset can be confident of its origins, data quality, and other valuable information about the data. Metadata also allow data creators to publicize the valuable data they have collected by making the metadata available on clearinghouses and other publically available venues. Metadata can be used in citation practices, thus increasing the visibility of the data.
CC image by US Embassy Guyana on Flickr

11. What is the Value to Data Users?
Metadata gives a user the ability to:
Search, retrieve, and evaluate dataset information from both inside and outside an organization
Find data: Determine what data exists for a geographic location and/or topic
Determine applicability: Decide if a dataset meets a particular need
Discover how to acquire the dataset identified; process and use the dataset
Understand the dataset, including definitions of column names, or expected numerical ranges found in the data
CC image by ASEE on Flickr
Metadata allows the user to search for and access data from a variety of sources. A search for metadata can be constricted to a geographic boundary, thus showing the user what data has been collected in a particular region. Metadata records help users determine whether the data will be applicable for use in a particular study. Finally, metadata records are of value to data users because they determine how a dataset can be acquired, and if there are any restrictions on how the data can be used.

12. What is the Value to Organizations?
Metadata helps ensure an organization’s investment in data:
Documentation of data processing steps, quality control, definitions, data uses, and restrictions
Ability to use data after initial intended purpose
Allows organization to track data use and facilitates publication
Transcends people and time:
Offers data permanence
Creates institutional memory
Advertises an organization’s research:
Creates possible new partnerships and collaborations through data sharing
CC image by mambol on Flickr
An organization that keeps current metadata can benefit in many ways. Metadata records help ensure the organization’s investment in the data by retaining information about how the data was collected, processed, and quality controlled. This creates a permanent record of the dataset –which is critical institutional memory. When researchers leave or retire, metadata allows the dataset to “live on” for the organization. The data may be reused in another research project in the future, and future researchers in the organization will need to know how the dataset was created. Finally, metadata advertises an organization’s research, creating new potential partnerships and collaboration through data sharing.

13. The Utility of Metadata
Metadata can support:
data distribution
data management
Metadata is beneficial because it can be used to support data distribution, data management, and project management. To be best utilized, metadata should be considered a component of the data, created during the development of the data, and populated with rich content.

14. Data Distribution: Discovery
The descriptive content of the metadata file can be used to identify, assess, and access available data resources.
online access
order process
contacts
ACCESS
use constraints
access constraints
data quality
availability/pricing
ASSESS
keywords
geographic location
time period
attributes
IDENTIFY
Metadata serves data discovery at multiple levels:
initial identification by query of keywords, location, time, and attributes
a quick assessment can be made by the scientist as to how useful the data are for a project by reading the access and use constraints; data quality measures of positional and attribute accuracy and sources used; and statements as to data availability, format and pricing
a user can find out how to access the by reading access instructions, any standard order process instructions, and contact information for the dataset.

15. Data Distribution: Catalogs
Examples of metadata search catalogs:
DataONE
Data discovery, knowledge, community…for a sustainable future
Data.gov
Federal e-gov geospatial data portal
Metacat
Repository for data and metadata
US Geological Survey
USGS Science Data Catalog
ArcGIS Online
ESRI sponsored national geospatial data portal
CC image by RGB12 on Flickr
Data portals are plentiful, and contain easily accessible metadata collections from a variety of institutions.

16. Data Distribution Example: DataONE
DataONE is an example of a metadata repository, available to all researchers.

17. Data Management: Maintenance and Update
Metadata records can be used to track data provenance accurately
Data Maintenance:
Are the data current?
Are the data in a reliable format?
Where are the data stored?
Data Update:
Contact information
Distribution policies, availability, pricing, URLs
New derivations of the dataset
For data management, metadata records can be queried to determine:
do we have data older than 10 years?
do we have data that was before some political or geophysical event resulted in significant change?
do we have data that used some older or now invalid data as a source?
do we have data that used older or now invalid methods?
Are the data still stored where the metadata indicates?
Global edits to contacts, policies, URLS, and information about new derivations of the dataset can be included in metadata records, thus assisting the data management process.

18. Data Management: Accountability
Metadata allows you to repeat a scientific process if:
methodologies are defined
variables are defined
analytical parameters are defined
Metadata allows you to defend your
scientific process:
demonstrate process
increasingly data savvy public requires metadata for consumer information
INPUT
Metadata allows you to repeat a scientific process (reproducibility) if methodologies, variables, and analytical parameters are well defined. It allows you to defend and demonstrate scientific process. A defensible process enables you to demonstrate the methodologies that led to decisions using the data. Increasingly, the savvy public demand metadata with datasets for consumer information purposes.
RESULTS

19. Data Management: Liability
Metadata is a declaration of:
Purpose – the originator’s intended application of the data
Use Constraints - inappropriate applications of the data
Completeness - features or geographies excluded from the data
Distribution Liability - explicit liability of the data producer and assumed liability of the consumer
What to do…
What not to do…
Metadata is invaluable for data liability. For example, a record will indicate the purpose – why the data were collected, any use constraints that are associated with the data, how complete the dataset is, and who is liable once the data are distributed and reused.

20. Concerns About Creating Metadata
Even if the value of data documentation is recognized, researchers are often concerned about the effort required to create metadata that effectively describe their data.
CC image by waterlilysage on Flickr
Even if the value of data documentation is recognized, concerns remain as to the effort required (i.e. time) to create metadata that effectively describes the data.

21. Concerns About Creating Metadata
Solution
workload required to capture accurate robust metadata
incorporate metadata creation into data development process – distribute the effort
time and resources to create, manage, and maintain metadata
include in grant budget and schedule
readability / usability of metadata
use a standardized metadata format
discipline specific information and ontologies
Use a standard ‘profile’ that supports discipline specific information
Metadata does require time and effort to create. The workload, however, is reduced when metadata creation is incorporated into the data development process and the effort is distributed among data contributors. Metadata creation and management should be treated as a standard data development procedure and resources for staff and time should be included in project and proposal work plans and budgets. The use of a standardized metadata format and the development of discipline specific ‘profiles’ of metadata can enable data users to quickly find needed information and address data developer concerns about metadata use and comprehension.
Definition of a profile:
“A modification of an existing metadata standard to adapt to data issues, cultural issues, or both. A profile is typically a subset of a base standard that tailors the metadata elements in the base standard to better describe the data to the community that uses it. Metadata profiles allow communities to follow a metadata standard, while at the same time enhancing the standard so that it is more appropriate for a particular use or locale.

22. What is a Metadata Standard?
A Standard provides a structure to describe data with:
Common terms to allow consistency between records
Common definitions for easier interpretation
Common language for ease of communication
Common structure to quickly locate information
In search and retrieval, standards provide:
Documentation structure in a reliable and predictable format for computer interpretation
A uniform summary description of the dataset
An established standard provides common terms, definitions, and structure that allow for consistent communication. The use of standards also supports search and retrieval in automated systems.
CC image by ccarlstead on Flickr

23. What does a metadata standard include?
Components of metadata:
A metadata standard is made up of defined elements, including the type of information the user should enter (e.g. text, numbers, date).
Examples of elements include Title, Abstract, Keyword, Online Link
An established standard provides common terms, definitions and structure that allow for consistent communication. The use of standards also support search and retrieval in automated systems.
Image: an example of a metadata editor in ArcGIS where entity and attribute information may be entered to generate a metadata record (source:

24. What Does a Metadata Record Look Like?
CC image by I like on Flickr
This is an example of a metadata record using the Federal Geographic Data Committee (FGDC) standard.

25. Choosing Metadata Standards
Image courtesy of Viv Hutchinson

26. Multiple Metadata Standards Exist: Examples
Dublin Core Element Set
Emphasis on web resources, publications
FGDC Content Standard for Digital Geospatial Metadata (CSDGM)
Emphasis on geospatial data
The Biological Data Profile (BDP) of the CSDGM is a profile to the CSDGM with an emphasis on biological data (and geospatial)
ISO 19115/ Geographic information – metadata
Emphasis on geospatial data and services
There are many standards available to document data. Each has a different focus, yet asks for similar information about the dataset.

27. Multiple Metadata Standards Exist: Examples
Ecological Metadata Language (EML)
Focus on ecological data
Darwin Core
Emphasis on museum specimens
Geography Markup Language (GML)
Emphasis on geographic features (roads, highways, bridges)
There are many standards available to document data. Each has a different focus, yet asks for similar information about the dataset.

28. Comparing Metadata Standards
Terminology for the same concepts may vary across standards
Ecological Metadata Language (EML)
FGDC Content Standard for Digital Geospatial Metadata
Title
Abstract
Entity Description
Entity Type Definition
Intellectual Rights
Use Constraints

29. Choosing a Metadata Standard
Many standards collect similar information
Factors to consider:
Your data type:
Are you working mainly with GIS data? Raster/vector or point data? Do you have biological or shoreline information in your dataset?
- Consider the FGDC Content Standard for Digital Geospatial Metadata with one of its profiles: the Biological Data Profile or the Shoreline Data Profile.
Are you working with data retrieved from instruments such as monitoring stations or satellites? Are you using geospatial data services such as applications for web-mapping applications or data modeling?
- If so, then consider using the ISO standard
Are you mainly working with ecological data?
- Consider Ecological Metadata Language (EML)

30. Choosing a Metadata Standard
More Factors to consider:
Your organization’s policies: do they state which standard to use?
What resources are available to create metadata?
Examples of Tools:
FGDC CSDGM:
- tools#availabletools
EML:
- Morpho (
ISO: (
- XML Spy or Oxygen
- CatMD
Other factors: Availability of human support; instructional materials; use of controlled vocabularies; output formats

31. What Makes a Good Metadata Record?
Metadata are developed continuously throughout the
entire data lifecycle
Plan
Collect
Assure
Describe
Preserve
Discover
Integrate
Analyze
Now that you know about some metadata standards to use and some available tools for developing metadata, let’s discuss some aspects of a good metadata record.
As mentioned at the beginning of this module, metadata should be developed continuously throughout the entire data lifecycle. This means that metadata should be generated along-side the data. Starting early will ensure that information about your data is fresh in your mind, which in turn saves you time. It will also enable you to provide more details about your data, which in turn leads to a higher-quality metadata record. For example, writing the Entity & Attributes section of your metadata or creating a separate data dictionary while you are developing your database will reduce this burden at the end of the project and can serve as a helpful tool during the project to ensure that everyone understands what each of the entities and attributes means. Writing the processing section of your metadata when you are processing your data ensures that all processing steps are documented. It is most beneficial if the person who is completing the data processing is the same person who writes the processing section for the metadata record.

32. What Makes a Good Metadata Record?
Consistency with commonly used fields
Examples for a FGDC CSDGM record: ✗ ✔
Publisher:
<publish>U.S. Geological Survey</publish>
<publish>USGS</publish>
Date:
<pubdate>YYYYMMDD</pubdate>
<pubdate>YYYY</pubdate>
<pubdate>MM/DD/YYYY</pubdate>
<pubdate>May 27, 2003</pubdate>
As you get started developing your metadata record, it is important that certain fields are used consistently. This means that some metadata fields require values that are written the same way to aid in machine-readability and discovery. For example, the publisher field should contain the standard form of your agency’s or organization’s name (if that is the appropriate publisher). For example, the USGS, the name should be written as U.S. Geological Survey, not USGS.
For CSDGM records, all dates should be written using the format of four digits for year, then two digits for month, followed by two digits for the day (YYYYMMDD). Data.gov is enforcing this format and metadata will fail validation if other formats are used.
Select the keywords that are specific to your dataset. The thesaurus used should be documented in the metadata. If a single thesaurus does not provide all of the theme keywords that your metadata require, you may use and reference more than one thesaurus. Within FGDC CSDGM and ISO there are specific fields for place keywords. The theme keyword field should not be used for place keywords. A good resource for finding standard place keywords is the Geographic Names Information System.
If you need to include species names in your metadata, you may use the taxonomic section within the Biological Data Profile instead of the theme keyword fields, to do so.
Refer to the appropriate documentation and/or schema for the standard you are using, as well as with your agency/organization to ensure you following the recommended usage.
Keywords:
<placekt>Geographic Names Information System</placekt>
<placekey>Roosevelt National Forest</placekey>
<themekey>Roosevelt Forest</themekey>

33. What Makes a Good Metadata Record?
Use Authority Files and Standard Vocabulary ✗
Global Change Master Directory
Geographic Names Information System
Getty Thesaurus of Geographic Names
ISO Topic Category Thesaurus
Rain
Rainfall
Precipitation
Showers
Rainstorm
Drizzle
Downpour
When possible, theme keywords should be drawn from thesauri or keyword lists. The use of authority files and standard vocabulary will help to make your metadata more discoverable, understandable, and interoperable. Make sure you reference the thesaurus used in your metadata record. Here are a few resources to get you started.
Photo by mxgirl2014 on flickr

34. What Makes a Good Metadata Record?
Acronyms
Spell out acronyms with first use. Many acronyms have multiple meanings (e.g., DOI)
Use widely known acronyms only when it corresponds to specific metadata fields such as file formats (e.g.,TIFF, JPEG, PDF)
If your metadata include acronyms, you should spell out the acronyms with their first use. Many acronyms have multiple meanings and, therefore, need to be clarified. DOI is an example of an acronym with multiple meanings. It is used for the Department of the Interior & Digital Object Identifiers. The use of widely known acronyms for file formats is acceptable without first spelling them out. For example, TIFF, JPEG, & PDF are all widely known across disciplines as different file types and would be acceptable to use.

35. What Makes a Good Metadata Record?
Provide all of the critical information for discovery, understanding, and reuse:
Identification Information
Entities & Attributes
Data Quality
Access, Use & Liability Constraints
Distribution
Spatial References
While not all metadata fields are mandatory, it is a best practice to provide all of the information that is applicable to your data. The more complete your metadata record is, the better chance your data have of being discovered and understood. This means that there will be less risk of your data being misinterpreted and misused. The critical information for CSDGM records includes: identification information, entities and attributes, data quality, access, use & liability constraints, distribution, and spatial references.

36. What Makes a Good Metadata Record?
Provide all of the critical information for: Identification
First and foremost, it is essential that your metadata record has complete identification information so that your data can be discovered. Basic citation information like the author’s name, the dataset title, and publication information allows your dataset to be referenced and attributed appropriately. A good, detailed abstract helps users get a general overview of your data without having to download the entire dataset. Theme keywords and Place keywords enable users to search for and find your data.

37. What Makes a Good Metadata Record?
Provide all of the critical information for: Entity / Attribute
Entity and attribute fields help to describe the often short and cryptic labels that are usually provided in datasets. If you have developed an external data dictionary for your data, that is great and you should link to it from your metadata. If an external data dictionary does not exist, you should describe each entity and attribute individually within your metadata record as is shown on the screen. A detailed attribute definition is essential to making your data usable. The definition should include the units, if applicable, and any special values, such as a no data value, which can be represented by a number such as -999.

38. What Makes a Good Metadata Record?
Provide all of the critical information for: Data Quality
Inform
- Accuracy
- Consistency
- Completeness
There are a number of available metadata fields for describing the quality of your data, such as attribute accuracy, logical consistency, completeness, and horizontal and vertical positional accuracy. Provide as much detail in these sections as is possible to enable users to determine if the data are appropriate for their needs.

39. What Makes a Good Metadata Record?
Provide all of the critical information for: Data Lineage
Citations for all source data used in the dataset should be included in the metadata record. These citations will allow the user to understand your dataset better and be able to trace the data back to their origin. The processing steps (lineage) that are performed on the data should also be documented in detail. Each step should be documented separately, preferably by the person performing that particular processing step. Contact information for that person should be included, so any questions from users can be directed to the most knowledgeable person.

40. What Makes a Good Metadata Record?
Provide all of the critical information for: Access, Use, & Liability Constraints
Access Constraints: restrictions and legal prerequisites for access the data.
Use Constraints: restrictions and legal prerequisites for using the data after access is granted.
Example: Use_Constraints:
Users are free to use, copy, distribute, transmit, and adapt the work for commercial and non-commercial purposes, without restriction, as long as clear attribution of the source is provided.
Distribution Liability: statement of the liability assumed by the distributor with respect to content and accuracy of the data.
Example: Distribution_Liability:
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
Describe if there are any access or use constraints for your data. Access Constraints refer to any restriction and legal prerequisites for accessing the data. Use Constraints refer to any restrictions and legal prerequisites for using the data after access is granted. Both of these elements include any constraints applied to assure the protection of privacy or intellectual property. Additionally, ensure that you establish what liability you have, if any, with respect to the content and accuracy of the data.

41. What Makes a Good Metadata Record?
Provide all of the critical information for: Accessing the Data
It is also important to inform users how and where they can access the data. Are they available for download or are there associated web services for the data? Also, be sure to include information about the format of the dataset, so users can understand what software applications they will need to utilize the data. In a CSDGM record there are a couple locations where you should include online links to your data. First, links can be included in the online linkage element (onlink) in the Citation Information subsection of Identification Information. Links can also be added to the Network Resource element (networkr) in the Distribution section, as shown on this slide. It is all right, and sometimes even encouraged, to have more than one format for your data. The online linkage and network resource elements can be repeated multiple times to accommodate links to these different data access points and formats.

42. What Makes a Good Metadata Record?
Provide all of the critical information for: Spatial Reference
Finally, spatial reference information is essential for integrating your data with other geospatial data. Spatial reference information includes information about both horizontal and vertical coordinate systems.

43. Steps to Create Quality Metadata
Organize your information
Did you write a project abstract to obtain funding for your proposal? Re- use it in your metadata!
Did you use a lab notebook or other notes during the data development process that define measurements and other parameters?
Do you have the contact information for colleagues you worked with?
What about citations for other data sources you used in your project?
Write your metadata using a metadata tool
Review for accuracy and completeness
Have someone else read your record
Revise the record, based on comments from your reviewer
Review once more before you publish

44. Tips for Writing Quality Metadata
Titles, Titles, Titles…
Titles are critical in helping readers find your data
While individuals are searching for the most appropriate datasets, they are most likely going to use the title as the first criteria to determine if a dataset meets their needs.
Treat the title as the opportunity to sell your dataset.
A complete title includes: What, Where, When, Who, and Scale
An informative title includes: topic, timeliness of the data, specific information about place and geography

45. Tips for Writing Quality Metadata
CC image by dolfi on
Flickr
A Clear Choice: Which title is better?
Rivers OR
Greater Yellowstone Rivers from 1:126,700 U.S. Forest Service Visitor Maps ( )
Greater Yellowstone (where) Rivers (what) from 1:126,700 (scale) U.S. Forest Service (who) Visitor Maps ( ) (when)
This example illustrates the importance of descriptive titles in metadata records.
The title “Greater Yellowstone Rivers from 1:126,720 Forest Visitor Maps ( )”, gives enough detail for a reader to discern whether they might like more information about your data from your metadata record.

46. Tips for Writing Quality Metadata
Be specific and quantify when you can! The goal of a metadata record is to give the user enough information to know if they can use the data without contacting the dataset owner.
Vague: We checked our work and it looks complete.
Specific: We checked our work using a random sample of 5 monitoring sites reviewed by 2 different people. We determined our work to be 95% complete based on these visual inspections.
CC image by PNASH on Flickr
One goal of a metadata record is to give a reader enough information about your data, that s/he could re-use it without contacting you, the dataset owner.
“We checked our work and it looks complete” is too vague for a reader to assess quality control on the dataset, for example. More specific language gives the reader more information about how the data was collected and analyzed.

47. Tips for Writing Quality Metadata
Use descriptive and clear writing
Fully document geographic locations
Select keywords wisely
Use thesauri for keywords whenever possible
Be detailed: there’s no such thing as too much metadata!
Select your keywords wisely. Think about the many ways someone might search for your data.
Use descriptive and clear writing.
Fully document geographic locations.
Use thesauri whenever possible for keywords. Keywords are essential for locating records in catalogs quickly and efficiently.
CC image by Marco Arment on Flickr

48. Tips for Writing Quality Metadata
Remember: a computer will read your metadata
Do not use symbols that could be misinterpreted by software: Examples: # % { } | / \ < > ~
Don’t use tabs, indents, or line feeds/carriage returns
When copying and pasting from other sources, use a text editor (e.g., Notepad) to eliminate hidden characters
When creating your metadata, keep in mind that a computer will read your metadata record. Therefore, it is important not to use tabs, indents, and special characters because they can be misunderstood by a computer.
If you are copying and pasting content from other sources into your metadata record it is prudent to use a text editor as a middle step to prevent applications from adding in unnecessary characters in the background of your text.

49. Summary Metadata is documentation of data
A metadata record captures critical information about the content of a dataset
Metadata allows data to be discovered, accessed, and re- used
A metadata standard provides structure and consistency to data documentation
Standards and tools vary – select according to defined criteria such as data type, organizational guidance, and available resources
Metadata is of critical importance to data developers, data users, and organizations
Metadata completes a dataset.

50. Additional Resources Federal Policies: Data Catalogs:
Executive Order 12906
M Open Data Policy
Data Catalogs:
DataONE
USGS Science Data Catalog
Data.gov
More about CSDGM & ISO 19115:
FGDC Geospatial Metadata Website
Metadata Tools:
Metadata Wizard✓
TKME✓*
CatMDEdit
GRIIDC Metadata Editor✓
ArcGIS 10.2✓
by J B on flickr
Standard Vocabularies
USGS Thesaurus
Global Change Master Directory
Geographic Names Information System
Getty Thesaurus of Geographic Names
Here are some additional resources to help you understand and create metadata for your research data.
 Supports Biological Data Profile
* Supports Biological Data Profile, Shoreline Profile, and Remote Sensing Extension
✓ Provides validation

51. The full slide deck may be downloaded from: http://www. dataone
The full slide deck may be downloaded from: Suggested citation: DataONE Education Module: Metadata. DataONE. Retrieved Nov12, From Copyright license information: No rights reserved; you may enhance and reuse for your own purposes. We do ask that you provide appropriate citation and attribution to DataONE.