Documentation

TerraC in a Nutshell
TerraC provides a data engine which allows managing, archiving, sharing, editing, modifying, and querying carbon and associated environmental data. These data are derived from various projects and sources; thus, provide a wide array of different carbon measurements, in various ecosystems and geographic regions, and spatial and temporal scales. The Terra C data engine facilitates synthesis and modeling to gain better insight into carbon cycling from micro, plot, field, watershed, basin, large region, and global scales.

Data Sharing and Usage Policy
Data users submitting data to or use data from the TerraC Information System agree to abide by the terms and conditions explained in this document. Data users may be held responsible for any misuse that is caused or encouraged by failure to abide by this agreement.

Definitions

Project: Set of one or more datasets that contain carbon (and related) environmental data.

Dataset: Set of data comprised of one or more data fields that contain carbon (and related) data that is part of a single project.

Roles of users

Project owner (leader): Principal Investigator or person with similar credentials responsible for collecting and managing the original, quality controlled data generated by a specific project. The project leader needs to initiate a project before a dataset can be submitted to TerraC and is responsible for the quality of all datasets under his/her projects. The project leader controls the levels of data sharing and can assign one or more data managers to each of his/her projects.

Data contributor (or manager): User that has read/write access to a dataset in TerraC. The data manager has privileges to submit a new dataset to a project and access and modify existing ones in part or as a whole. The project leader needs to assign a user manager status before he/she can submit a new dataset or modify an existing one in a project.

Data user: User that can view a dataset in TerraC. The data user can read public datasets and also private datasets as long as he/she has been granted access to them by the project leader. The data user cannot submit a new dataset or modify existing ones unless he/she receives manager status from the project leader to a project.



Data sharing: Data stored in TerraC can be shared at three access levels. The access levels are chosen by the project leader to control access to their projects by different users. Different access levels can be assigned to different users, the level being project- and user-specific. Levels 1 and 2 mirror the roles of data user and data manager, respectively. Level 3 in the most restricted access level.

Levels of data sharing:

Level 1 – Public with read-only access: Access to the data is open to all TerraC users. Any person that has a TerraC user account (i.e. data users) can view the data, but not modify it directly from the TerraC database. Only the project leader can modify/edit data.

Level 2 – Private read/write access: Access to the data is open to data managers who were assigned (approved) by the project leader to have permissions to view and modify/edit data directly from TerraC. Private read/write access is password-protected.

Level 3 – Private read-only access: Access to the data is restricted to the project leader and users selected by the project leader. Users can only view the data, but not modify it directly from TerraC.


The project leader controls the sharing of data in TerraC. He/she provides leadership for collaboration with new partners on behalf of the project teams. The project leader can switch sharing levels from Level 3 to 2 and 1, but not vice versa, meaning if the data are released to other users or the general public this right cannot be reversed.
Data users who are interested in to gain access to a specific protected dataset can contact the project leader and negotiate agreement of data use of a specific project. The project leader may agree to share data with the data user to collaborate on a joint project, work on a co-authored research publication, or use them for other purposes.


Data usage:
Data users are expected to use data obtained from TerraC to the highest level of professional integrity and ethics. Data users must abide by the following guidelines when distributing or publishing data obtained from TerraC:

Data sharing and usage in TerraC is governed by the Attribution Non-Commercial Share Alike license provided by Creative Commons  (summary:
http://creativecommons.org/licenses/by-nc-sa/3.0; legal code:
http://creativecommons.org/licenses/by-nc-sa/3.0/legalcode
), which observes the following rules:

image

Attribution: The data user must give credit to the project leader (or project) in the manner specified by him/her (but not in any way that suggests that the  project leader endorses the data user or his/her use of the data);

Attribution

Noncommercial: The data user may not use TerraC data for commercial  purposes; data should be used for reserach and non-profit applications;

Noncommercial

Share Alike: If the data is modified in any manner or used to derive other products, the data user may distribute the resulting work only under the same or similar license to this one;

Share Alike

 

Credits and publications derived from TerraC usage:

  • The data user must inform or consult the project leader about his/her intentions to use the data for publication well in advance of submission of the publication; the project leader should be given the opportunity to read the manuscript and, if appropriate, be offered co-authorship;

  • The data user must give credit to the project leader (or project), which can be in the form of co-authorship, citation, or acknowledgement, according to the requirements imposed by the project leader; any deviation from this rule must be formally agreed between the data user and project leader;

  • The data user must cite or acknowledge TerraC as the data host used to obtain the data;

  • Any modification to the data originally obtained from TerraC by the data user must be fully documented.

 

Carbon Data and Associated Environmental Data
(1) Core Data Fields:

  • Identification number for each observation (ID)
  • Replication number (REPN)
  • X coordinate (X) {Geographic Coordinate - longitude in decimal degrees, World Geographic System 1984, WGS 1984}
  • Y coordinate (Y) {Geographic Coordinate - latitude in decimal degrees, World Geographic System 1984, WGS 1984}
  • Sample date (DATE) {MM/DD/YYYY}
  • Time (TIME) {HH:MM:SS}
  • Height or depth of measurement (Z) {in cm; below the soil surface negative numbers; above the soil surface positive numbers}
  • Carbon measurements (variable names, data values, and meta data: analytical methods & units of measurement in Standard International Units)
  • Biogeochemical or other environmental data (variable names, data values, and meta data: analytical methods & units of measurement in Standard International Units)


(2) Project Elements (meta data):

  • Project title
  • Project description (description of sampling design, sampling protocol, quality assessment, data constraints such as below detection limit treatment, missing values, etc.)
  • Project owner (typically Principal Investigator of a research project; or Project Leader for agency lead project)
  • Project contributor (optional)
  • Project user (optional)
  • Contact information (Project Owner)
  • Funding source
  • Project location (description of geographic location of project; size of project area)
  • Project period (YYYY to YYYY)
  • Link to project homepage
  • Publications from project
  • Acknowledgements

 

Data Quality and Standards

Data format: TerraC focuses on terrestrial carbon and related environmental data. Data submitted to TerraC must contain carbon data and have the following format:

  • Data organized n rows and columns, with cases (observations) listed in the rows and properties (attributes) listed in the columns;

  • Carbon and other measured properties must be presented as variables in specific columns:
    • Each column must only contain properties measured using the same method; if the same property was measured using more than one method (e.g. total carbon vs. carbon fractions), each method must be presented as a separate column;

  • Spatial coordinates (horizontal and vertical) and time stamps must be presented, whenever available, as variables in specific columns;

  • Repeated measures (e.g., the same property collected at different times or replicated) must be treated as separate cases (i.e. listed in separate rows):
    • A column indicating that the cases are repeated measures of the same property must be included (e.g. using the same sample identifier for the repetitions);
    • A column indicating the number of the repetition (i.e. 1, 2, 3…) must be included;

  • Quality assurance/quality control (QA/QC) data should not be included in the dataset, but instead in the metadata of the property it pertains to.


Data preparation:
You can use any relational data base software of spreadsheet program to prepare your data for upload into Terra C. For example, Excel, MS Access, SQL or similiar to organize your data listing cases (observations) in rows and properties in columns.


Note:

  • Data values can be represented in form of strings, boolean (yes or no; 1 or 0), continuous (float), or discrete (integer) data
  • Null values should be represented in the data as "0" or "0.0"
  • To represent missing data leave fields empty (blank); do not use "N/A"
  • To mark any special data values you may use codes "-999", "-9999" or similar (outside the data range for a specific measurement). The meaning of such special values should be included in the meta data
  • Below detection limits (BDL) should be marked in data fields with a value (numeric data value) instead of listing "BDL" (string). The numeric data value can either represent the "true" BDL for a specific analytical method (e.g. 0.0005) or a designated arbitrary value (e.g. -99999). Mixing of different data types in one variable should be avoided (e.g. mixing of numeric and string values; or decimal values and text)


Data upload into Terra C:
Tutorials provided on this web site provide step-by-step instructions for data upload into Terra C. In a nutshell:
(1) Setup an account in Terra C (http://terrac.ifas.ufl.edu/)
(2) Project Details: Create a new project and provide details about the project
(3) Data Tables: Add a new data table. Note (Data Setup): Core fields are automatically added to your new table, but additional data fields need to be added (e.g. soil carbon measurement)
(4) Template Download: Download your data template (ASCII file: *.txt) which contains your prepared data structure (core fields and added fields)
(5) Data preparation: Open the template in any spreadsheet / relational database software and add your data. Important: Keep the organizational structure of core fields in place and do not edit or delete them. Save your file in tab-delimited ASCII format
(6) Data Upload: Upload your tab-delimited data file into Terra C
(7) Add meta data to your data (each property/observation need to be described including analytical methods and units)


Metadata
: Since the objective of TerraC is to share data among multiple users, it is critical that metadata are provided in detail for every project, dataset, and variable in a dataset. Upon creation of a new project, the project leader needs to provide information (i.e. metadata) describing project detail, including location, sampling design, contact information, objectives, and others. Upon submission of a new dataset, the project leader or data manager needs to provide metadata for dataset and for every variable in the dataset.


Data quality
: It is the responsibility of the project leader to ensure that all data listed under a project in TerraC have passed QA/QC. The project leader provides information for each project’s data about the type of QA/QC and adopted standards. The data managers can assist the project leader to meet QA/QC requirements. The TerraC team may quarantine suspicious data and request information from the project leader and/or data manager to assure quality of the data before making them available online. TerraC cannot be held responsible for mistakes in the data or inadequate data usage.
Data that for some reason are restricted by funding agencies or imposed proprietary or legal rights (e.g. military projects, pending patents, projects funded by private companies, or other) should not be included in TerraC.

 

Citation Example
If data downloaded from TerraC are used in any publication (peer-reviewed journal article, textbook chapter, Power Point presentation, online publication, or other) the following citation should be used in the acknowledgement:

Terrestrial Carbon (TerraC) Information System. University of Florida, Gainesville, FL, USA. Available at: http://TerraC.ifas.ufl.edu. Last verified: date.

 

Disclaimer
Despite TerraC’s effort to assure the quality and integrity of its database, data accuracy cannot be guaranteed. Data users assume full responsibility for subsequent use of data obtained from TerraC.