Virtual machine image reproducing data analysis of WebSci'18 paper: Using the Web of Data to Study Gender Differences in Online Knowledge Sources
Description
This image contains the materials to reproduce all figures, tables and other data analysis results reported in our Web Science 2018 paper:
Hollink, Laura, Astrid van Aggelen, and Jacco van Ossenbruggen. Using the Web of Data to Study Gender Differences in Online Knowledge Sources: the Case of the European Parliament. ACM Conference on Web Science, May 2018, Amsterdam, The Netherlands. doi:10.1145/3201064.3201108
This provides a virtual machine image with fully installed reproducibility pack as defined by https://doi.org/10.5281/zenodo.1232929
The image is based on a standard Ubuntu 17.04 iso image. It is shipped with checked-out versions of all relevant source code and data and installed versions of the relevant docker images. On bootup, the docker images running in the guest will start a web server that is available from the host at 127.0.0.1:3052/gender/p/tables_and_figures_from_paper.swinb.
The virtual machine can be accessed (directly or via ssh) using the user name "vre" with password "vrevre".
The image is archived as an Open Virtual Appliance (.ova file) that packages a vmdk vdisk image with an Open Virtual Machine Format (ovf) metadata descriptor. It should run out of the box using commonly supported hypervisors including VMware, VirtualBox and Xen. If needed, the vmdk vdisk can be imported into Qemu/kvm after converting the vdisk to qcow2 using qemu-img convert.
Files
Files
(2.6 GB)
Name | Size | Download all |
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md5:84d6bd3543744f82cb6f852f943a67a9
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2.6 GB | Download |
Additional details
Related works
- Is compiled by
- https://github.com/vre4eic/websci2018-reproducibility-pack/tree/V1.0.0 (URL)
- https://hub.docker.com/r/vre4eic/gender-demo-data/ (URL)
- https://hub.docker.com/r/vre4eic/rserve-sandbox/ (URL)
- https://hub.docker.com/r/vre4eic/swish/ (URL)
- Is documented by
- md5sum://84d6bd3543744f82cb6f852f943a67a9 (URL)
Funding
References
- Hollink, Laura, Astrid van Aggelen, and Jacco van Ossenbruggen. Using the Web of Data to Study Gender Differences in Online Knowledge Sources: the Case of the European Parliament. ACM Conference on Web Science, May 2018, Amsterdam, The Netherlands. doi:10.1145/3201064.3201108