ArcView Metadata Training: American Samoa James Byrne Josh Murphy NOAA Coastal Services Center July 29-30, 2003

ArcView Metadata Training:ArcView Metadata Training:American SamoaAmerican Samoa

James ByrneJosh Murphy

NOAA Coastal Services CenterJuly 29-30, 2003

Course Outline

Part I: What Is Metadata?

Part II: Metadata Creation

Part III: Class Exercise

Part IV: Clearinghouses

First…. Some Terms

Metadata - Documentation of geospatial data written in a consistent manner

FGDC - Federal Geographic Data Committee

CSDGM - Content Standard for Digital Geospatial Metadata, referred to commonly as “The Standard” or “The Content Standard”

Clearinghouse - A distributed catalog of metadata

Geospatial - refers to a geographic location

Part I: What Is Metadata?Part I: What Is Metadata?

Simply put, metadata is information

about your data.

What is Metadata?

This is the metadata for this.

What’s Missing?

Aunu`u

Author(s) Boullosa, Carmen. Title(s) History of American Samoa / by Carmen Boullosa Place New York : Grove Press, 1997. Physical Descr viii, 180 p ; 22 cm. Subject(s) Oceana Format Reference

Author(s) Boullosa, Carmen. Title(s) History of American Samoa / by Carmen Boullosa Place New York : Grove Press, 1997. Physical Descr viii, 180 p ; 22 cm. Subject(s) Oceana Format Reference


While the card-catalog entry is a form of metadata, it does not address topics such as

quality, accuracy, or scale. Well-written geospatial metadata describes these and many more aspects of the data.

Identification_Information: Citation: Citation_Information: Originator: United States Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC) Publication_Date: 20020923 Title: Vectorized Shoreline of Hawaii, Derived from Landsat ETM, 2002 Edition: first Geospatial_Data_Presentation_Form: vector digital data Publication_Information: Publication_Place: Charleston, SC Publisher: United States Department of Commerce,

Identification_Information: Citation: Citation_Information: Originator: United States Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Coastal Services Center (CSC) Publication_Date: 20020923 Title: Vectorized Shoreline of Hawaii, Derived from Landsat ETM, 2002 Edition: first Geospatial_Data_Presentation_Form: vector digital data Publication_Information: Publication_Place: Charleston, SC Publisher: United States Department of Commerce,


What is Metadata?

Metadata contains vital information.Metadata contains vital information.Imagine, if you will…

You are given two identical cans without labels. One contains cat food, the other contains tuna (dolphin-safe, of course).

You must choose one these cans,

and then eat the contents.

Other Examples?

What is Metadata?

Properly documented

data provides vital information

to interested parties.

Metadata is that component of data which describes it.

Environmental Sensitivity Index Data

Metadata

RARNUM - unique combination of species, concentration, and seasonality

CONC (concentration) = Density species is found at location

Season_ID = seasonality code link to the seasonal table

Element - Biology group

What is Metadata?

It’s data about a data set.It’s data about a data set.

Title

Scale

Source

Content

Location

Publication

Access

Title

Scale

Source

Content

Location

Publication

Access

MetadataMetadataMetadataMetadata

GIS files

Imagery

Geospatial databases

GPS data

GIS files

Imagery

Geospatial databases

GPS data

Data setData setData setData set

What is Metadata?

Metadata describes…

CONTENT

CONDITION

QUALITY

Characteristics of the data

Characteristics of the data

What is Metadata?

Metadata

Non-spatial orattributes

Spatial

Because metadata provides vital information about a dataset, it should never be viewed or

treated as a separate entity.

Take Home Message

Metadata is a critical and

integral component of any complete

data set.

Metadata is a critical and

integral component of any complete

data set.

Two similar Two similar paintings by paintings by

Picasso up for Picasso up for auction sold for auction sold for vastly different vastly different

prices. prices.

Why?

One had metadata...

...One didn’t.

The Value of Metadata

Metadata should be updated to reflect changes in the data.

19701970

HEWHEWWestern SamoaWestern SamoaBritish HondurasBritish Honduras

Trust TerritoryTrust TerritoryCape Hatteras Light Cape Hatteras Light

ArpanetArpanetMt. St. HelenMt. St. Helen

West GermanyWest Germany

20002000

HHS & HUDHHS & HUDSamoaSamoaBelizeBelizeU.S. CommonwealthU.S. CommonwealthCape Hatteras LightCape Hatteras LightInternetInternetMt. St. HelenMt. St. HelenGermanyGermany

Metadata has Metadata has other value other value

associated with associated with it.it.

• Avoid duplication Avoid duplication

• Share reliable informationShare reliable information

• Publicize effortsPublicize efforts

• Reduce workloadReduce workload

For data developers, metadata...


• Facilitates understandingFacilitates understanding

• Focuses on key elements Focuses on key elements

• Enables discovery — inside and outside Enables discovery — inside and outside of organizationsof organizations

For data users, metadata...


For organizations, metadata...


• Protect investment in data

• Create an institutional memory

• Counter personnel changes

• Allow sharing of data with other agencies

• Reduce costs

• Limit potential liability

• Save time and money

Metadata as a “data discovery” toolMetadata as a “data discovery” tool

This saves time and money.

If it’s geospatial data you need, metadata helps

• Find data of interest

• Determine the usefulness of the data

• Determine how to access the data


Metadata Standards

Think for a moment how hard it would be to…

… bake a cake without standard units of measurement.

… put gas into your car without standard nozzle sizes.

… plug a lamp into a socket without standard electrical outlets.

The standard for

metadata ensures a level

of consistency in

data documentation.

Standards ensure consistency.

Metadata Standards

The Federal Geographic Data Committee (FGDC) was organized in 1990 under the

Office of Management and Budget to promote the coordinated use, sharing,

and dissemination of geospatial data on a national basis. The FGDC was tasked

with creating a metadata standard to meet these objectives.

The Metadata Standard

Metadata Standards

"... each agency shall document all new

geospatial data it collects or produces, either

directly or indirectly, using the standard under

development by the FGDC, and make that

standardized documentation electronically

accessible to the Clearinghouse network."

The Content Standard for Digital Geospatial Metadata (CSDGM)

Executive Order 12906, 1994

Metadata Standards

The Content Standard utilizes...The Content Standard utilizes...

• Common termsCommon terms

• Common definitionsCommon definitions

• Common languageCommon language

• Common structureCommon structure Access

constraints

Citation

currentness

entity

attrib

ute

domain

lineage

Process step

Metadata Standards

The Content Standard helps The Content Standard helps

the user determine...the user determine...

• If a set of geospatial data is available and fit for a particular use.

•How to access and transfer the data set.

Metadata Standards

FGDC’s Metadata

Workbook

Defines the 334

metadata elements.

Metadata Standards

What do I use “The Workbook” for?

• It is the definitive resource for applying the FGDC Content Standard.

• However, it does not define the production rules.

• It describes element domain values, which are valid values that can be assigned to the data element.

• It provides section and element definitions.

Interpreting the Metadata Workbook

A data element is a logically primitive itemof data. Data elements are the things thatyou “fill in.”

The form for the definition of a data element is:

Data element name -- definition.Type: (choice of “integer”, “real”, “text”, “date”, or “time”)Domain: (describes valid values that can be assigned)

An example of the definition of a data element is:

Abstract -- a brief narrative summary of the data set.Type: textDomain: free text

Note: Data element definitions are containedin the text of the Content Standard,

not in the graphical production rules.

• It is a quick reference for production rules and structure.

Use the “Graphical Representation”for quick access.

• You will still need to use the workbook to find the definition of a particular element and its domain.

Organization of the Content Standard

DataQuality

Information

SpatialData

OrganizationInformation

SpatialReference

Information

Entityand

AttributeInformation

4 52 6 731

Metadata

The Three Supporting SectionsThe Three Supporting Sections

9 Time PeriodInformation

10 Contact

Information

8 Citation

Information

DistributionInformation

MetadataReference

Information

IdentificationInformation

Organization of the Content Standard

The Seven Main Sections The Seven Main Sections

Mandatory - must be provided.

MeaningData

ElementCompound

Element

What’s Mandatory? What’s Not?

Mandatory if Applicable - must be provided if the data set exhibits

the defined characteristic.

Optional - provided at the discretion of the data set producer.

Remember, metadata is a legacy document that

concisely sums up your data or data set.

Without metadata, your data set is

incomplete.

FOR MORE INFORMATION

Michael Moeller NOAA CSC Metadata Specialist

[email protected]/metadata/

Part II: Metadata CreationPart II: Metadata Creation

Writing Metadata

is not THAT bad!

• 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.

Templates can help!!

• Contain information that is specific to your project or organization

• Allow you to enter and save pertinent information for use at later date

• Save time and effort!• No special tools needed!• Like any other metadata, can (and

should) be reviewed for updates.

Writing Metadata

Before you begin writing,get organized.

Writing Metadata

Document your data as you go.

Writing Metadata

Write so others can understand.

Writing Metadata

• Define all acronyms.

• Avoid using jargon.

• Clearly state data limitations.

Writing Metadata

Keep your readers in mind.

Always review your document.

Writing Metadata

Items required

Chocolate

FGDCWorkbook

Metadata entry tool

Tool Time

A sample of some of the available tools for metadata creation, validation, and publication.

• CNS and MP“Chew ‘n spit,” checks and corrects structural errors, and “Metadata Parser”, which checks for errors in element compliance.

• 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.

• TKMEText editor used for metadata entry.

• ArcCatalog Metadata Editor Metadata creation in ArcGIS

TKME

• An editor for formal metadata.• TKME is intended to simplify the process of creating metadata that conform to the content standard

Metadata Collector for ArcView 3.2

• A free, downloadable extension for ArcView 3.x users• Enters information for certain elements automatically• Allows user to save individual elements for future use

At the right side of most of the screens will be the option to Retrieve and Save the information you have entered into the fields. This allows you to save frequently used information such as contact and similar abstracts to be used repeatedly. These are generally saved as either .dbf or .txt files in the working directory specified.

On each screen, there is a SectionHelp and a Section Example button.The Section Help button opens a window containing definitions of the metadataelements for that section. The SectionExample button provides an example of an FGDC-compliant metadata record.


Certain sections are read directly from the data set by the ArcView Metadata Collector


When you have finished all of the metadata sections, you will be presented with the option to save the metadata file as both a text and an HTML file.


MetaScribeMetaScribe

• A tool for the creation of multiple, similar metadata records• Template driven

Metadata Parser (mp)Metadata Parser (mp)

• DOS-based tool that compiles and checks the syntax of “raw” metadata

• Input must be either text, XML, or SGML• Creates outputs in multiple formats (HTML, TXT, XML, SGML)• Also creates an error file

ArcCatalog Metadata EditorArcCatalog Metadata Editor

• Included with basic ArcGIS 8.x software• Simple to use:

• Projection parameters automatically captured (if .prj file present)

• Can use template to automatically fill in contact, distribution information

Using the AV Metadata Collector ExtensionUsing the AV Metadata Collector Extension

• For the remainder of this section, the instructor will demonstrate For the remainder of this section, the instructor will demonstrate metadata creation using the FGDC Content Standard and the metadata creation using the FGDC Content Standard and the ArcView Metadata Collector extension. ArcView Metadata Collector extension.

Section 1 – Identification InformationSection 2 – Data Quality InformationSection 3 – Spatial Data Organization InformationSection 4 – Spatial Reference InformationSection 5 – Entity and Attribute InformationSection 6 – Data Distribution InformationSection 7 – Metadata Reference Information

Review: The Seven Main Sections of the Content Standard

Using the AV Metadata Collector ExtensionUsing the AV Metadata Collector Extension

Data Set Example

Tutuila Shoreline

Section 1 – Identification Information

Basic Information about the data set.


Metadata

The title is critical in helping others find your data.

Which is better?

Greater Yellowstone Rivers from 1:126,700 Forest Visitor Maps (1961-1983)

Section 1

• The title is the first thing a user sees when searching for data• The title helps a user quickly determine the usefulness of data

Include topic, time and place!

Bad title (user has to read description):“Roads”

Better title:“Roads Shapefile for Guam - 2000”

Title, title, title

Section 1

Bounding Coordinates

West_Bounding_Coordinate: 145.69

East_Bounding_Coordinate: 145.83

North_Bounding_Coordinate: 15.29

South_Bounding_Coordinate: 15.09

15.29, 145.69

15.09, 145.83

Select your key words wisely.

• Use unambiguous words.

• Use descriptive words.

• Fully qualify geographic locations.

Key Words

Theme:Theme_keyword_thesaurus: NoneTheme_keyword: major roadsTheme_keyword: highwaysTheme_keyword: transportation networkTheme_keyword: thoroughfaresTheme_keyword: vector digital dataTheme_keyword: geographic information system

Key Words

Access and Use Constraints

• Essentially liability statements

• Example:

Section 1

Use_Constraints: Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distributionconstitute such a warranty.

Use_Constraints: Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distributionconstitute such a warranty.

Link to on-line data

Other_Citation_Details:Online_Linkage: http://www.csc.noaa.gov/hurricane_tracks.shp


Metadata

Section 2 – Data Quality Information

A general assessment of the quality of the data set.


A general assessment of the quality of the data set.

How thoroughly and correctly the features in the data set are described.

• What features have been omitted ? • What non-existent features are represented ? • How correct is their classification ? How can you test and report Attribute Accuracy?

• Field Verification• Visual comparison of source data to hard copy

Attribute Accuracy

Attributes

How accurate are these attributes?

Attribute Accuracy

DATA_QUALITY_INFORMATION

Attribute_Accuracy Attribute_Accuracy_Report: A team of field investigators participated in data verification exercises June, 1996 and December, 1996. Data validation teams consisted of personnel from Oak Ridge National Laboratory, Moss Landing Marine Laboratories, Ray L. Harris, Jr., and the Coastal Services Center. The team was equipped with a portable color laptop computer linked to a Global Positioning System (GPS). The field station runs software that supports the classified data as a raster background with the road network as a vector overlay with a simultaneous display of live GPS coordinates. Accuracy assessment points were generated with Erdas Imagine software using a stratified random sample. To make the acquisition of the field reference data more practical, a sixteen pixel buffer area around roads (i.e. 8 pixels on each side of the road) including logging trails was created. Seven thousand random points were generated within this area for the accuracy assessment. See the accuracy assessment table for results of data verification exercise.

Attribute Accuracy

Exa

mp

le A

ttri

bu

te A

ccu

racy

Rep

ort

A closer lookDo these footprints accurately represent these?

Attribute_Accuracy: Attribute_Accuracy_Report: Attribute accuracy was tested by manual comparison of the source with hardcopy printouts of the digital building footprint data. The attributes were visually compared to attributes in the source data (digital orthophoto).

Attribute Accuracy

Addresses geometric problems in your dataset-overshoots-undershoots-broken polygons-missing or duplicate labels

A typical Logical Consistency Statement:

Logical_Consistency_Report: These data are believed to be logically consistent, though no tests were performed. There are no overshoots, undershoots or broken polygons. Line geometry is topologically clean.

Logical Consistency

Geometric/Logical Consistency Problems

How the coordinate descriptions of features compare to the actual locations of those features on the ground.

How far away is a map feature from its actual location in the world?

How can you test for and report Positional Accuracy?

Comparison of your data to more accurate data (survey data) GPS accuracy Using the National Map Accuracy Standards (positional accuracy for paper maps only)

Positional Accuracy

Q: How horizontally accurate is the position of this shoreline?

A: As accurate as the data itwas derived from.

Positional Accuracy

Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: The data were created by delineating the boundary off a USGS 7.5 minute Topographic Map at 1:24000 scale. Therefore, the horizontal accuracy is assumed to be within National Map Accuracy Standards, with a horizontal accuracy of 45.6 feet at the 95% confidence level.

Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: The data were collected with a trimble pathfinder Global Positioning System. The horizontal accuracy of the point data is 300ft.

Positional Accuracy

Examples

Using National Map Accuracy Standards

Using GPS accuracy

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.

Process Step


Metadata

Section 3 – Spatial Data Organization Information

The mechanism used to represent spatial Information in the data set.

Spatial Data Organization Information

What is the Structure of the Data?

Raster

Vector

Row and Column count

Vector Object Count

Section 3 – Spatial Data Organization Information

Metadata

Section 4 – Spatial Reference Information

The description of the reference frame for, andThe means to encode coordinated in the data set.

Section 4 - Spatial Reference Information

Three Choices under Horizontal Coordinate System

• Geographic Latitude and Longitude

• Planar Map Projection Grid Coordinate System Local Planar

• Local

Geographic Coordinate System

Latitiude and longitude measurements define a position on the Earth.

Units of measurement can be• decimal degrees• decimal minutes• decimal seconds• degrees and decimal minutes• degrees minutes and seconds• radians • grads

Planar Systems

Map Projection - representation of the earth’s surface

East-West Projections: Lambert, Albers (Conic)Used in Florida, Massachusetts, and Ohio

North-South Projections: Transverse Mercator (Cylindrical) Used in Florida and California

Grid Coordinate Systems - State Plane and UTM

Used by states as common coordinate systemsBased on map projections

Datums

A datum is a set of parameters defining a coordinate system.

Typically, your data’s projection will be referenced to either North American Datum NAD 83World Geodetic System 1984North American Datum NAD 27

Section 4 – Spatial Reference Information

Metadata

Section 5 – Entity and Attribute Information

Information about the content of the data set,including the entity types, their attributes, andthe attribute values that may be assigned.

Attribute Table

attributes

attribute values

Attribute Table

Detailed Attribute DescriptionNot only do you have to describe your attributes but you also have to describe the values

Attribute Domains: domains are used to describe attribute values

1) Range Domain: a sequence of values- if the attribute is “water_depth” and the values are between 0 and 150, a range domain is suitable.

2) Enumerated Domain: comprised of a list of values- if the attribute is “landcover_code” and the list of values is between 1 16, then an enumerated domain should be used.

3) Codeset Domain: data values are defined by a set of codes- if the attribute is “wetland_id#” and the codes are defined in a standard or code book, then the codeset domain should be used.

4) Unrepresentable Domain: the set of data values cannot be represented- numbers assigned by software program that are meaningless

Enumerated Domain

To understand thislegend, each value in this enumerateddomain will have to be defined.

Section 5 – Entity and Attribute Information

Metadata

Section 6 – Distribution Information

Information about the distributor of and optionsfor obtaining the data set.

Section 6 – Distribution Information

Metadata

Section 7 – Metadata Reference Information

Information on the currentness of the metadata information, and the responsible party.

Section 7 – Metadata Reference Information

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.

Reviewing Metadata

• Can a novice understand what you wrote?

• Are your data properly documented for posterity?

When you review your work, ask:

Reviewing 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:

Reviewing Metadata

Part III: Class ExercisePart III: Class Exercise

Part IV: ClearinghousesPart IV: Clearinghouses

ClearinghousesClearinghouses

A metadata clearinghouse is a A metadata clearinghouse is a

location — typically accessed location — typically accessed

through the Internet — to through the Internet — to

search for spatial data setssearch for spatial data sets

A clearinghouse is a decentralized system of Internet servers you can search

Servers with metadataServers with metadata

Client


Clearinghouses make Clearinghouses make

metadata records easy to metadata records easy to

find find


The National Geospatial Data The National Geospatial Data

Clearinghouse has more than 100 spatial Clearinghouse has more than 100 spatial

data servers with digital geographic datadata servers with digital geographic data


The NGDC The NGDC is a set of information services is a set of information services

that use that use hardware, software,hardware, software, and and

telecommunications networkstelecommunications networks to provide to provide

searchable access to informationsearchable access to information


• FGDC Geospatial Data Clearinghouse

• Montana State Library Natural Resource Information System GIS

• Nebraska Geospatial Data Clearinghouse

• Wisconsin Land Information Clearinghouse

Some specific examples:Some specific examples:


You can search all or part of You can search all or part of

the community in a single the community in a single

sessionsession

x



www.fgdc.gov

You can define your criteria


You can select a server


You can view your search results


The FGDC Clearinghouse selected

the search and retrieve software

ANSI Z39.50-1995 (ISO 10163-1995)

Clearinghouse ImplementationClearinghouse Implementation

How can you participate? How can you participate?

• Set up your own node

• Send metadata to an existing node

• Have another organization host your node

• Put metadata on a web page for future “harvesting” to a node


Why set up a node? Why set up a node?

• YouYou control your metadata

• It’s easy to set up

• You choose the software

• The software operates on typical web server platforms


• In setting up a node, most work is in preparing metadata for available data sets

• Store these data in a structured form, according to the standard


Before you can index your

metadata into a clearinghouse,

you must check for completeness,

accuracy, and quality


Your metadata must meet clearinghouse requirements:

• Proper format

• Proper field names and values

• Appropriate formats: text, HTML, and fgfSGML


Parsing and validation tools check for Parsing and validation tools check for structural or content errorsstructural or content errors

errorerrorreportsreports

metadatametadatadocumentsdocuments

metadata parser metadata parser softwaresoftware

mpmp


Run cns output through mp to make text, SGML, HTML files

Run cns output through mp to make text, SGML, HTML files

YESYESCorrect original fileCorrect original file

Run original file through cnsRun original file through cns

Errors in error.txt?YESYES

CreateMetadataCreate

Metadata

Run cns output through mpRun cns output through mp

NONO

Correct original fileCorrect original file

Place 3 files on searchable system

Place 3 files on searchable system

Errors in error.txt?

Errors in error.txt?

NONO


mp produces metadata in HTML, mp produces metadata in HTML, SGML, and TEXTSGML, and TEXT

mpmpmpmp TEXTTEXTTEXTTEXTHTMLHTMLHTMLHTML

SGMLSGMLSGMLSGML


<html>

<head>

<title>1989 Land Cover/Land Use on the Upper Mississippi River System</title>

</head>

<body>

<h1>1989 Land Cover/Land Use on the Upper Mississippi River System</h1>

<h2>Metadata:</h2>

<ul>

<li><A HREF="#Identification_Information">Identification_Information</A>

<li><A HREF="#Data_Quality_Information">Data_Quality_Information</A>

<li><A HREF="#Spatial_Data_Organization_Information">Spatial_Data_Organization_Information</A>

<html>

<head>

<title>1989 Land Cover/Land Use on the Upper Mississippi River System</title>

</head>

<body>

<h1>1989 Land Cover/Land Use on the Upper Mississippi River System</h1>

<h2>Metadata:</h2>

<ul>

<li><A HREF="#Identification_Information">Identification_Information</A>

<li><A HREF="#Data_Quality_Information">Data_Quality_Information</A>

<li><A HREF="#Spatial_Data_Organization_Information">Spatial_Data_Organization_Information</A>

mp HTML filemp HTML file mp HTML filemp HTML file


mp HTML filemp HTML file mp HTML filemp HTML file


<!DOCTYPE METADATA PUBLIC "-//FGDC//DTD METADATA 1.0//EN"><metadata>

<idinfo>

<citation>

<citeinfo>

<origin>Kurt P. Kowalski and Douglas A. Wilcox</origin>

<origin>Great Lakes Science Center</origin>

<origin>Biological Resources Division</origin>

<pubdate>1997</pubdate>

<title>Coastal Wetland Vegetation Analysis (Metzger Marsh)

</title>

<pubinfo>

<pubplace>Ann Arbor, MI</pubplace>

<!DOCTYPE METADATA PUBLIC "-//FGDC//DTD METADATA 1.0//EN"><metadata>

<idinfo>

<citation>

<citeinfo>

<origin>Kurt P. Kowalski and Douglas A. Wilcox</origin>

<origin>Great Lakes Science Center</origin>

<origin>Biological Resources Division</origin>

<pubdate>1997</pubdate>

<title>Coastal Wetland Vegetation Analysis (Metzger Marsh)

</title>

<pubinfo>

<pubplace>Ann Arbor, MI</pubplace> mp SGML filemp SGML file mp SGML filemp SGML file


Identification_Information:

Citation:

Citation_Information:

Originator: Environmental Management Technical Center

Publication_Date: 19950829

Title: 1989 Land Cover/Land Use on the Upper Mississippi River System

Geospatial_Data_Presentation_Form: Map

Publication_Information:

Publication_Place: Environmental Management Technical Center

Publisher: Environmental Management Technical Center (EMTC)

Other_Citation_Details: White, B. M. and T. W. Owens. 1991. Geographic Information System Pilot Project For The Upper Mississippi River System. U.S. Fish and Wildlife Service, National Ecology Research Center, Fort Collins, Colorado, June 1991. LTRMP 91-05. 48 pp. + Appendix.

Identification_Information:

Citation:

Citation_Information:

Originator: Environmental Management Technical Center

Publication_Date: 19950829

Title: 1989 Land Cover/Land Use on the Upper Mississippi River System

Geospatial_Data_Presentation_Form: Map

Publication_Information:

Publication_Place: Environmental Management Technical Center

Publisher: Environmental Management Technical Center (EMTC)

Other_Citation_Details: White, B. M. and T. W. Owens. 1991. Geographic Information System Pilot Project For The Upper Mississippi River System. U.S. Fish and Wildlife Service, National Ecology Research Center, Fort Collins, Colorado, June 1991. LTRMP 91-05. 48 pp. + Appendix.

mp TEXT filemp TEXT file mp TEXT filemp TEXT file



For more information on For more information on clearinghouse implementation:clearinghouse implementation:


www.fgdc.gov/clearinghouse/tutorials/howto.html

OR

Please contactJohn Ulmer

NOAA CSC Computer [email protected]

Any Questions?Any Questions?


Documents

ArcView Metadata Training: American Samoa James Byrne Josh Murphy NOAA Coastal Services Center July 29-30, 2003