COLLECTED BY

Organization: Archive Team

Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.

History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.

The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.

This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.

Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.

The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.

Collection: Archive Team: URLs

TIMESTAMPS

The Wayback Machine - https://web.archive.org/web/20210721120234/https://github.com/AstraZeneca

AstraZeneca

Data Science & AI: Unlocking new science insights

Global
https://www.astrazeneca.com/
Verified
We've verified that the organization AstraZeneca controls the domain:
- www.astrazeneca.com
Learn more about verified organizations

Pinned repositories

kallisto

Efficiently calculate 3D-atomic/molecular features for quantitative structure-activity relationship approaches.

Python 18 9
awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

937 43

Repositories

qscheck

R Apache-2.0 0 0 0 0 Updated Jul 20, 2021
awesome-explainable-graph-reasoning

A collection of research papers and software related to explainability in graph machine learning.

deep-learning graph graph-algorithms awesome-list graphml explainable-ai explainable-ml

Apache-2.0 43 937 0 0 Updated Jul 20, 2021
kallisto

Efficiently calculate 3D-atomic/molecular features for quantitative structure-activity relationship approaches.

chemistry computational-chemistry quantum-chemistry machinelearning

Python Apache-2.0 9 18 1 3 Updated Jul 18, 2021
detectIS

A pipeline to rapidly detect exogenous DNA integration sites using DNA or RNA paired-end sequencing data

Perl Apache-2.0 1 2 0 0 Updated Mar 22, 2021
OmicsFold

Multi-omics data normalisation, model fitting and visualisation.

R Apache-2.0 0 0 1 0 Updated Jan 19, 2021
CTELC-Patient-Attrition-Model

Clinical Trial Enrollment Life Cycle (CTELC) modeling project aims to leverage "industry-wide" data to understand key drivers and build predictive models. Patient attrition, also referred to as dropout or patient withdrawal, occurs when patients enrolled in a clinical trial either withdraw or are lost to follow-up by the clinical site and trial …

R Apache-2.0 0 0 0 0 Updated Dec 16, 2020

Top languages

Most used topics

Loading…

People