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Tutorials on Data Management. Lesson 8: Value of Metadata. CC image by John Norris on Flickr. Lesson Topics. Illustrate the value of metadata to data users, data providers, and organizations Describe the utility of metadata for a variety of scenarios. CC image by PictureYouth on Flickr.

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Tutorials on data management
Tutorials on Data Management

Lesson 8: Value of Metadata

CC image by John Norris on Flickr

Lesson topics
Lesson Topics

  • Illustrate the value of metadata to data users, data providers, and organizations

  • Describe the utility of metadata for a variety of scenarios

CC image by PictureYouth on Flickr

Learning objectives
Learning Objectives

  • After completing this lesson, the participant will be able to:

    • Identify 3 reasons metadata is of value to data users, data developers, and organizations

    • List 3 uses for metadata, beyond discovery of data

CC image by ccarlstead on Flickr

Metadata has value to all
Metadata Has Value to ALL








What is the value to data developers
What is the Value to Data Developers?

  • 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

CC image by US Embassy Guyana on Flickr

What is the value to data users
What is the Value to Data Users?

  • Metadata gives a user the ability to:

    • Search, retrieve, and evaluate data set 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 data set meets a particular need

    • Discover how to acquire the dataset you identified; process and use the dataset

What is the value to organizations
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

  • Transcends people and time:

    • Offers data permanence

    • Creates institutional memory

  • Advertises an organization’s research:

    • Creates possible new partnerships and collaborations through data sharing

Information entropy
Information Entropy

Time of data development

Specific details about problems with individual items or specific dates are lost relatively rapidly

General details about datasets are lost through time


Retirement or career change makes access to “mental storage” difficult or unlikely

Accident or technology change may make data unusable

Loss of data developer leads to loss of remaining information


(From Michener et al 1997)

Information entropy1
Information Entropy Entropy

Sound information management, including metadata development, can arrest the loss of dataset detail.



A closer look the utility of metadata

collect Entropy















A Closer Look: The Utility of Metadata

  • Metadata can support:

    • data distribution

    • data management

    • project management

  • If it is:

    • considered a component of the data

    • created during data development

    • populated with rich content

Data distribution via metadata
Data EntropyDistribution via Metadata

data discovery

metadata publication


Distribution data discovery

  • keywords

  • geographic location

  • time period

  • attributes

  • use constraints

  • access constraints

  • data quality

  • availability/pricing




Distribution: Data Discovery

  • The descriptive content of the metadata file can be used to identify, assess, and access available data resources.

Distribution metadata publication

Internet / Entropy



Distribution: Metadata Publication

  • A metadata collection can be published to the Internet via:

    • website catalog

    • web accessible folder (waf)

    • Z39.50 metadata clearinghouse

    • metadata service

    • geospatial data portal


User Query

Metadata Collection

Distribution geospatial data portals
Distribution: Geospatial Data Portals Entropy

  • Examples of Federal and National Portals:

    • USGS

      • USGS Core Science Metadata Clearinghouse:


    • Geodata Portal

      • Federal e-gov geospatial data portal


    • ArcGIS Online

      • ESRI sponsored national geospatial data portal


    • GeoConnections Discovery Portal (Canada)


Data management via metadata

Data EntropyAccountability

Discovery & Re-use

Data Management via Metadata

Maintenance & Update


Management maintenance and update
Management: Maintenance and Update Entropy

  • Data Maintenance:

    • Are the data current?

      • Do we have data older than ten years?

      • was before some political or geophysical event that resulted in significant change?

    • Are the data valid?

      • prior to most current source data

      • prior to most current methodologies

  • Data Update:

    • Contact information

    • Distribution policies, availability, pricing, URLs

    • New derivations of the dataset

Management data discovery reuse
Management: Data Discovery & Reuse Entropy

  • Metadata marketing in the past…

    If you create metadata, other people can discover your data

  • New and improved message…

    If you create metadata,you can find your own data

Management data discovery reuse1
Management: Data Discovery & Reuse Entropy

  • Find your data by:

    • themes / attributes

    • geographic location

    • time ranges

    • analytical methods used

    • sources and contributors

    • data quality

      Discoverable data is usable data!

CC image by Oceanit Daily Photo

on Flickr

Management data accountability
Management: Data Accountability Entropy

  • Metadata is an exercise in data accountability. It requires you to assess:

    • What do you know about the dataset?

    • What don’t you know about the dataset?

    • What should you know about the dataset?

      Are you willing to associate yourself with the metadata record ?

Management data accountability1
Management: Data Accountability Entropy

  • Metadata allows you to repeat scientific process if:

    • methodologies are defined

    • variables are defined

    • analytical parameters are defined

  • Metadata allows you to defend your

    scientific process:

    • demonstrate process

    • increasingly GIS-savvy public requires metadata for consumer information



Management data liability
Management: Data Liability Entropy

  • Metadata is a declaration of:


    • the originator’s intended application of the data

      Use Constraints

    • inappropriate applications of the data


    • 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…

Project management via metadata

Project Coordination Entropy

Project Management via Metadata

Project Planning

Project Monitoring

Contract Deliverables

Project management project planning
Project Management: Project Planning Entropy

  • Metadata records can serve as a project design document:

    • descriptions & intent of project

    • geographic and temporal extent of project

    • source data of project

    • attribute requirements of project

  • Benefits:

    • expectations are clearly outlined

    • metadata is integrated into the process

    • provides a medium to record progress

Project management project monitoring

milestones Entropy


Project Management: Project Monitoring

  • Use metadata to monitor:

    • data development status

    • QA/QC assessments

    • needed changes in approach

      Monitoring requires that

      the metadata be actively

      maintained and reviewed!

Project management project coordination
Project Management: Project Coordination Entropy

  • Metadata can be a means to improve communications among project participants

    • descriptions & parameters

    • keywords, vocabularies, thesauri

    • contact information

    • attributes

    • distribution information

  • If reviewed regularly by all participants, metadata created early and updated during the project improves opportunity for coordinating:

    • source data

    • analytical methods

    • new information

Project management contract deliverables
Project Management: Contract Deliverables Entropy

  • As a key component of the data, metadata should be part of any data deliverable

  • For quality metadata from a deliverable, the record should provide:

    • Citation information

    • Data quailty information

    • Accurate geospatial information

    • Entities and attributes clearly defined

    • Distribution information

Summary Entropy

  • Metadata is of critical importance to data developers, data users, and organizations

  • Metadata can be effectively used for:

    • data distribution

    • Data management

    • Project management

  • Metadata completes a dataset.

    Creating robust metadata is in your OWN best interest!

Before you go
Before you go . . . Entropy

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