Documentation for Sevilleta LTER Datasets
Comprehensive metadata are necessary to support data quality control, efficient dataset archival
and retrieval, and functional re-use of the data both by owners and secondary users. The Sevilleta
LTER requires complete documentation for long-term maintenance and distribution of study
databases. Metadata elements requested in this form are consistent with elements required by the
Ecological Metadata Standard (EML), which was adopted by the LTER Coordinating Committee in
2004.
Sevilleta metadata consists of information about:
1) Why the study was done
2) Who is involved with study design, data collection, analysis and data management
3) Detailed study methods, so that a secondary user will be able to understand what was done
without contacting the study principal investigator.
4) Where the study was done, with GPS points so the site can be relocated.
5) Detailed variable information
Please fill in this metadata form to the best of your ability. If you have questions, please contact
the Sevilleta Information Manager, Kristin Vanderbilt, at 277-2109 or
vanderbi@sevilleta.unm.edu
METADATA TEMPLATE FOR SEVILLETA LTER DATA SETS
1] Data Set Code: {Information manager will enter this field}
2] Data Set Title:
3] Abstract: (Please provide an abstract describing the purpose of the research project.)
4] When the samples/data were collected: (Enter date as a single date –and/or- a range of dates in
format mm/dd/yyyy. If you only know the year enter the data as 01/01/2008. Copy and paste these
elements for multiple date ranges or single dates.
Date Range: Begin Date:
Date Range: Begin Date:
Or
Single Date:
Single Date:
End Date:
End Date:
4a] More information about when the data were collected: {If there was some information in the
“When the samples/data were collected:” section that you couldn’t express as single dates, or a
range of dates, enter that information into this section.)
5] Who is Involved with the Samples/Data: (Repeat each category of person as many times as
necessary to document all people involved with the data set. Please include address and email for
each.)
Principle Investigator(s):
Address:
Email:
Field Crew:
Address:
Email:
Data Manager:
Address:
Email:
Contact: (If you want the primary contact person for the dataset to be the Sevilleta information
manager, please leave this blank)
Address:
Email:
5a] More information about who is involved with the samples/data: {If there was some
information in the “Who is involved with the samples/data:” section that didn’t fit into the form
fields in 6], please enter it here. For example: “Several REUs helped collect the samples.”}
6] Where the Data were Collected: {Enter the list of core sites where the data were collected.
Separate sites by a comma. Core sites are: Deep Well, Five Points Grass, Five Points Creosote,
Blue Grama, Sepultura Canyon, Cerro Montoso, Goat Draw, Black Butte, Sevilleta Field Station,
Bronco Well, Rio Salado Grass, Rio Salado Creosote, Red Tank. If your data were not collected at
one of the core research sites, enter information about your site in 7a]}
Sites:
6a] Additional Geographic Metadata: {If your data were not collected at one of the Sevilleta Core
Sites in the dropdown list in 7], then enter specific data for your sites in the fields below. For
studies that contain several sampling locations, give specific site characteristics information about
each location. Copy and Paste more Study Area text blocks if you have more than two sites.
If you do not know the coordinates of your site, then enter the coordinates for the bounding box of
the Sevilleta: North: 34.42, South = 34.19, East = -106.513, West = -107.08. COORDINATES
MUST BE ENTERED in DECIMAL DEGREES AND NAD83. There is a degrees/minutes/seconds
to decimal converter at http://www.fcc.gov/mb/audio/bickel/DDDMMSS-decimal.html.
For Study Area Location, enter a text description of how one would find the site. For instance,
“Site is four km south of Black Butte on east side of road.”
Study Area 1:
*Study Area Name:
*Study Area Location:
*Study Area Description:
Elevation:
Landform:
Geology:
Soils:
Hydrology:
Vegetation:
Climate:
Site history:
*GPS coordinates in decimal degrees: Either describe a bounding box, -or- give a point location
for the study sites. Use NAD83 and decimal degrees.
Bounding Box:
North Coordinate:
South Coordinate:
East Coordinate:
West Coordinate:
Single Point:
North Coordinate:
West Coordinate:
Study Area 2:
*Study Area Name:
*Study Area Location:
*Study Area Description:
Elevation:
Landform:
Geology:
Soils:
Hydrology:
Vegetation:
Climate:
Site history:
Bounding Box:
North Coordinate:
South Coordinate:
East Coordinate:
West Coordinate:
Single Point:
North Coordinate:
West Coordinate:
7] How the Data were Collected: {Describe methods and instrumentation used in the study.
Copy and paste blocks of instrument fields if you used more than two instruments.}
Example:
*Methods:
*Experimental design: Randomized complete block design.
*Setting up plots: Plots were selected by …..
*Sample Plant Cover: A 100cm X 100 cm quadrat was placed ….}
Methods:
* Instrument Name:
* Manufacturer:
* Model Number:
8] Variable Descriptions: Each variable description should include the following information:
Variable X:
* Name: The name on the column in the data set (e.g. NO3_Conc)
* Label: Enter a more descriptive label (e.g. NO3 Concentration)
* Definition: A description of what the variable is: (e.g. Nitrate concentration in water sample.)
* Data Type: Nominal is used to represent named categories, a list of coded values, or plain text
descriptions; Ratio measurements are numerical (e.g. degrees, concentration, meter, ); Datetime
should be used for variables that are dates, days, months, years, etc.
* Units of Measure: Leave blank if the variable is nominal (categorical); otherwise enter the units
of measure (e.g. ppm, g/ml, m, mm/dd/yyyy)
* Precision of Measurements: Example: 0.001 means precision to the thousandths. Leave blank if
the variable is nominal. Other possible entries could be “1” for one stem, or “1” for one year
* Range or List of Values: List the codes and their meanings (e.g. CM = Cerro Montosa, DW =
Deep Well) for categorical variables. Separate codes by commas. If the variable is nominal, but
the description is something like plots number 1 – 100 (and you don’t want to enter 1 = plot 1, 2 =
plot 2) then leave this blank. Example: The variable is Plot_Number, and you have 500 plots. Fill
in the variable information as follows:
Variable X
* Name: Plot_Number
* Label: Plot Number Associated with Data
* Definition: Plot identification numbers ranging from 1 to 500
* Data Type: Nominal
* Units of Measure:
* Missing Data Code: Enter the code, followed by an =, followed by the code definition. Example:
-888 = data was not collected because there was no need to collect it, -999 data was not collected
due to human error); Other symbols such as . (a period) can be used. Leave blank if there are no
missing data for this variable. If there is more than one code used, separate them with commas.
* Computational Method for Derived Data: Example: Plant volume = cover * height. Leave blank
if there was no computational method.
Variable 1:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 2:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 3:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 4:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 5:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 6:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 7:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 8:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 9:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 10:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 11:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 12:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 13:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 14:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 15:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 16:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 17:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 18:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 19:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
Variable 20:
*Name:
*Label:
*Definition:
*Data Type:
*Units of Measure:
*Precision of Measurements:
*Missing Data Code:
*Computational Method for Derived Data:
9] QA/QC Procedures? {Describe how the data were checked for accuracy. For instance, “Data
were range checked using a SAS program.” Or “Data were entered twice and then compared to
find errors.”}
10] Additional metadata: {Enter any other information that would help someone trying to reuse
your dataset to understand why and how the data were collected.}