Help Login Create account

Data released on March 06, 2018

Supporting data for "The Scientific Filesystem (SCIF)".

Sochat, V (2018): Supporting data for "The Scientific Filesystem (SCIF)". GigaScience Database. http://dx.doi.org/10.5524/100420 RIS BibTeX Text

Here we present the Scientific Filesystem (SCIF), an organizational format that supports exposure of executables and metadata for discoverability of scientific applications. The format includes a known filesystem structure, a definition for a set of environment variables describing it, and functions for generation of the variables and interaction with the libraries, metadata, and executables located within. SCIF makes it easy to expose metadata, multiple environments, installation steps, files, and entrypoints to render scientific applications consistent, modular, and discoverable. We will start by reviewing the background and rationale for the Scientific Filesystem, followed by an overview of the specification, and the different levels of internal modules ("apps") that the organizational format affords. Finally, we demonstrate that SCIF is useful by implementing and discussing several use cases that improve user interaction and understanding of scientific applications. SCIF is released along with a client and integration in the Singularity 2.4 software to quickly install and interact with Scientific Filesystems. When used inside of a reproducible container, a scientific filesystem is a recipe for reproducibility and introspection of the functions and users that it serves.
We use SCIF to evaluate container software, provide metrics, serve scientific workflows, and execute a primary function under different contexts. To encourage collaboration and sharing of apps, we have developed tools along with an open source, version controlled, tested, and programmatically accessible web infrastructure. SCIF and associated resources are available at https://sci-f.github.io. The ease of using SCIF, especially in the context of containers, offers promise for scientists’ work to be self-documenting, and programatically parseable for maximum reproducibility. SCIF opens up an abstraction from underlying programming languages and packaging logic to work with scientific applications, opening up new opportunities for scientific software development.

Contact Submitter

Additional information:

https://github.com/sci-f/sci-f.github.io

https://sci-f.github.io/

Keywords:

filesystem reproducibility singularity hpc linux containers docker containers workflows 

Software

http://gigadb.org/images/data/cropped/100420.jpg

Files: (FTP site) Table Settings

Columns:

File Description
Sample ID
Data Type
File Format
Size
Release Date
Download Link
File Attributes

File NameSample IDData TypeFile FormatSizeRelease Date 
ReadmeTEXT2.56 KB2018-02-21
GitHub archivearchive2.64 MB2018-02-21
Displaying 1-2 of 2 File(s).

History:

+

Other datasets you might like: