Evidence map›Paper›PMID 31197310›Full record

ArticleBioinformatics (Oxford, England)2020

Cloud bursting galaxy: federated identity and access management.

Vahid Jalili, Enis Afgan, James Taylor, Jeremy Goecks

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vahid JaliliDepartment of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA.
Enis AfganDepartment of Biology, Johns Hopkins University, Baltimore, MD, USA.
James TaylorDepartment of Biology, Johns Hopkins University, Baltimore, MD, USA.
Jeremy GoecksDepartment of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA.

Funding

Democratization of Data Analysis in Life Sciences Through GalaxyU41HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, SCHATZ, MICHAEL · 2012 to 2020
$14.4M
A Federated Galaxy for user-friendly large-scale cancer genomics researchU24CA231877 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI GOECKS, JEREMY, SCHATZ, MICHAEL · 2018 to 2022
$3.9M
NCI NIH HHS U24 CA231877NHGRI NIH HHS U41 HG006620
6 · The paper itself

Abstract

motivationLarge biomedical datasets, such as those from genomics and imaging, are increasingly being stored on commercial and institutional cloud computing platforms. This is because cloud-scale computing resources, from robust backup to high-speed data transfer to scalable compute and storage, are needed to make these large datasets usable. However, one challenge for large-scale biomedical data on the cloud is providing secure access, especially when datasets are distributed across platforms. While there are open Web protocols for secure authentication and authorization, these protocols are not in wide use in bioinformatics and are difficult to use for even technologically sophisticated users.

resultsWe have developed a generic and extensible approach for securely accessing biomedical datasets distributed across cloud computing platforms. Our approach combines OpenID Connect and OAuth2, best-practice Web protocols for authentication and authorization, together with Galaxy (https://galaxyproject.org), a web-based computational workbench used by thousands of scientists across the world. With our enhanced version of Galaxy, users can access and analyze data distributed across multiple cloud computing providers without any special knowledge of access/authorization protocols. Our approach does not require users to share permanent credentials (e.g. username, password, API key), instead relying on automatically generated temporary tokens that refresh as needed. Our approach is generalizable to most identity providers and cloud computing platforms. To the best of our knowledge, Galaxy is the only computational workbench where users can access biomedical datasets across multiple cloud computing platforms using best-practice Web security approaches and thereby minimize risks of unauthorized data access and credential use. AVAILABILITY AND IMPLEMENTATION: Freely available for academic and commercial use under the open-source Academic Free License (https://opensource.org/licenses/AFL-3.0) from the following Github repositories: https://github.com/galaxyproject/galaxy and https://github.com/galaxyproject/cloudauthz.

Indexed as

Cloud ComputingComputational BiologyComputer SecuritySoftware

Identifiers

PMID31197310
PMCPMC6956780

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.