Project, Studies, and Collections: Difference between revisions

From Network for Advanced NMR
Jump to navigationJump to search
Line 1: Line 1:


= Organizational Structure: Projects, Studies, Collections, and Funding Sources =
== Overview ==
NAN provides a structured, hierarchical approach to organizing NMR data in the Data Browser which is accessible from the [[Datasets#Navigation Pane|Navigation Pane]].
NAN provides a structured, hierarchical approach to organizing NMR data in the Data Browser which is accessible from the [[Datasets#Navigation Pane|Navigation Pane]].


== Projects ==
== Projects ==
Projects are the top-level organizational unit and are typically created by a Principal Investigator (PI) or a PI Delegate. Projects can:
[[File:Navigation-pane.png|thumb|Navigation Pane]]
Projects are the top-level organizational unit and are created by a Principal Investigator (PI) or a PI Delegate. Projects features include:


* Be linked to one or more funding sources (e.g., NIH, NSF).
* The ability to link to one or more funding sources (e.g., NIH, NSF)
* Grant automatic access to all members of the PI’s lab group.
* Serving as containers for datasets, studies, and collections
* Serve as containers for datasets, studies, and collections.
** Datasets added at the Project level appear in the "''default collection''" for that Project
* Be selected during data collection from the NDTS GUI or used post-collection for organizing datasets in the Data Browser.
*The ability to grant all lab-group users access to the Project or to apply fine-grain access control to the Project data
 
* Allowing the Project and Study to be selected at the time of data collection through the NDTS GUI


Projects are ideal for grouping data related to a particular grant, research theme, or initiative. Associating datasets with projects allows for clear attribution of funding and enables both investigators and facilities to generate accurate usage and funding reports.
Projects are ideal for grouping data related to a particular grant, research theme, or initiative. Associating datasets with projects allows for clear attribution of funding and enables both investigators and facilities to generate accurate usage and funding reports.


== Studies ==
== Studies ==
Studies are mid-level containers that exist within Projects. They can be created by any user with access to the parent project.
Studies are mid-level containers that exist within Projects. They can be created by any user with access to the parent Project.
 
* Each study belongs to a single project.
* Studies can contain datasets and collections.
* Studies provide a finer-grained way to organize data under a broader research effort.


Examples of studies might include a time course experiment, a particular sample series, or a set of related experiments under a project umbrella.
* Each Study belongs to a single Project
* Studies can contain datasets and Collections
** Datasets added at the Study level appear in the "''default collection''" for that Study


== Collections ==
== Collections ==

Revision as of 15:21, 29 May 2025

Overview

NAN provides a structured, hierarchical approach to organizing NMR data in the Data Browser which is accessible from the Navigation Pane.

Projects

Navigation Pane

Projects are the top-level organizational unit and are created by a Principal Investigator (PI) or a PI Delegate. Projects features include:

  • The ability to link to one or more funding sources (e.g., NIH, NSF)
  • Serving as containers for datasets, studies, and collections
    • Datasets added at the Project level appear in the "default collection" for that Project
  • The ability to grant all lab-group users access to the Project or to apply fine-grain access control to the Project data
  • Allowing the Project and Study to be selected at the time of data collection through the NDTS GUI

Projects are ideal for grouping data related to a particular grant, research theme, or initiative. Associating datasets with projects allows for clear attribution of funding and enables both investigators and facilities to generate accurate usage and funding reports.

Studies

Studies are mid-level containers that exist within Projects. They can be created by any user with access to the parent Project.

  • Each Study belongs to a single Project
  • Studies can contain datasets and Collections
    • Datasets added at the Study level appear in the "default collection" for that Study

Collections

Collections are flexible containers that serve two purposes:

  • **Within a Study:** Collections group datasets that share a specific context, such as replicates or multi-condition experiments.
  • **Independent Use:** Any user can create personal collections accessible from My Collections. These allow individuals to organize datasets privately, even if those datasets are part of shared projects.

Key points about collections:

  • Collections can be nested inside studies or used independently.
  • Collections can only contain datasets the user already has permission to view.
  • Datasets added to personal collections retain the PI-defined permission model—they do not become private or public by virtue of the collection.

Funding Sources

Funding sources may be added by PIs and linked directly to Projects. Each funding source includes fields such as:

  • Agency and Institute (e.g., NIH/NIGMS)
  • Grant number
  • PI and Co-PI names
  • Abstract, start and end dates, and optional URL

When a dataset is linked to a Project, and that Project is associated with one or more funding sources, those funding relationships are inherited. This structure supports downstream reporting, including generation of reports for funding agencies and internal accounting by facilities.

Summary

Together, Projects, Studies, Collections, and Funding Sources provide a scalable and intuitive structure for organizing NMR data in NAN:

  • Projects group datasets at the lab/grant level.
  • Studies subdivide projects into experimental or thematic areas.
  • Collections bundle related datasets, either collaboratively or privately.
  • Funding sources tie datasets to their financial support, improving accountability and reporting.

This structure parallels a traditional file system, making it intuitive for users while supporting robust metadata tracking and analysis across the NAN platform.