Renku is a platform that bundles together various tools for reproducible and collaborative data analysis projects. It is aimed at independent researchers and data scientists as well as labs, collaborations, and courses and workshops. Renku can be used by anyone who deals with data, whether they are a researcher, data analyst, project owner, or data provider.
Renku promotes reproducibility by providing tools to track your analysis workflows and save them together with your versioned data, code, and environment specification. Every result can be replayed either to repeat a calculation or to re-execute on new data or with a different choice of parameters.
Renku encourages reusability by storing and querying the connections between datasets, code executions, and results in a Knowledge Graph. Producers and consumers of analysis artifacts can always recover the full provenance of a result, establishing trust and reducing boilerplate.
Renku stimulates collaboration among peers and across disciplines by guaranteeing that a media-rich discussion space and fully configured, shareable interactive computational environments are always just a click away. Collaborators can easily work on projects together or in parallel, combining their work in a systematic and safe manner.
Turn a Git repo into a collection of interactive notebooks
Have a repository full of Jupyter notebooks? With Binder, open those notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere.
Whole Tale is an NSF-funded Data Infrastructure Building Block (DIBBS) initiative to build a scalable, open source, web-based, multi-user platform for reproducible research enabling the creation, publication, and execution of tales – executable research objects that capture data, code, and the complete software environment used to produce research findings.
A beta version of the system is available at https://dashboard.wholetale.org
ArchivesSpace is the next-generation web-based archives information management system, designed by archivists and supported by diverse archival repositories.
ArchivesSpace is an open source, web application for managing archives information. The application is designed to support core functions in archives administration such as accessioning; description and arrangement of processed materials including analog, hybrid, and born-digital content; management of authorities (agents and subjects) and rights; and reference service. The application supports collection management through collection management records, tracking of events, and a growing number of administrative reports. The application also functions as a metadata authoring tool, enabling the generation of EAD, MARCXML, MODS, Dublin Core, and METS formatted data.
ArchivesSpace is a program with a current staff of 4.5 FTE, a community of over 400 members, and three administrative groups—a Governance Board (elected), a Technical Advisory Council (appointed), and an User Advisory Council (appointed)—and published Bylaws. LYRASIS is the organizational home for ArchivesSpace.
convOERter is a tool that converts the educational resources to OER. The tool (convOERter) is designed to read a file, extract all images as well as all possible metadata and substitute them with OER elements in a semi-automated manner. The web-based analysis tool consists of two components: The frontend, which provides the user interface that accomplishes the import, conversion and final download of the teaching materials.
Full featured editor and C# class structures for Library of Congress MARC21 and MARCXML bibliography records.
This project is built upon the CSharp_MARC project of the same name available at http://csharpmarc.net, which itself is based on the File_MARC package (http://pear.php.net/package/File_MARC) by Dan Scott, which was based on PHP MARC package, originally called “php-marc”, that is part of the Emilda Project (http://www.emilda.org). Both projects were released under the LGPL which allowed me to port the project to C# for use with the .NET Framework.
Editor online for create MARC records