Bucknell Digital Commons, a service of Bucknell University Libraries, is an institutional repository that bring together all of Bucknell University's research and scholarship under one umbrella, with an aim to preserve and provide access to that research and scholarship.
The research and scholarly output included in Bucknell Digital Commons is selected and deposited by the individual university departments and centers on campus. The repository is an excellent vehicle for working papers or copies of published articles and conference papers, as well as presentations, senior theses, and other works not published elsewhere.
Most research can be submitted electronically. Click on the link above to submit your research. Some publications do not allow authors to submit directly. In these cases, you will be provided with a mail form to contact the appropriate administrator for further instruction.
Open data and content can be freely used, modified, and shared by anyone for any purpose.
The Open Definition (a project of the Open Knowledge Foundation) defines in detail the meaning of “open” with respect to knowledge, promoting a robust commons in which anyone may participate, and interoperability is maximized.
An open work must satisfy the following requirements in its distribution:
Open License or Status: The work must be in the public domain or provided under an open license
Access: The work must be provided as a whole and at no more than a reasonable one-time reproduction cost, and should be downloadable via the Internet without charge.
Machine Readability: The work must be provided in a form readily processable by a computer and where the individual elements of the work can be easily accessed and modified.
Open Format: The work must be provided in an open format. An open format is one which places no restrictions, monetary or otherwise, upon its use and can be fully processed with at least one free/libre/open-source software tool.
A license is open if its terms satisfy the following conditions:
Required Permissions: The license must irrevocably allow use, redistribution, modification, and compilation for any purpose. The license must not restrict anyone from making use of the work in a specific field of endeavor. The license must not impose any fee arrangement, royalty, or other compensation or monetary remuneration as part of its conditions.
Acceptable Conditions: The license may require distributions of the work to: include attribution of contributors, rights holders, sponsors, and creators as long as any such prescriptions are not onerous; and to remain under the same license or a similar license; among other conditions.
Open Definition 2.1, Open Knowledge Foundation, http://opendefinition.org/od/2.1/en/, accessed on August 12, 2019.
CC BY-NC 4.0 license is a Creative Commons international license that is commonly used for scientific data.
The licensor cannot revoke these freedoms as long as you follow the license terms.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Kristin Briney argues for publishing both the research findings and the research data, in order to improve the quality, reproducibility, and impact of research. "Data, or it didn't happen!" TED x UW-Milwaukee, 2015. Length: 15 minutes.
Open Data: Unleashing Hidden Value (LinkedIn Learning)
An online course on LinkedIn Learning with transcripts, exercise files, and self-assessment quizzes. Governments around the world are discovering the value and responsibility in making the data they collect and store easily available to anyone who wants to access it. Making the decision to open up data sets is a strategic choice that requires detailed tactics. There are processes and technologies to make data accessible while minimizing risk. If you want to start opening up your organization's data to enable transparency and catalyze innovation, or use open data to drive analysis and make more informed decisions, this course is for you. The course introduces real-world use cases for open data, as well as the steps you need to take to develop and operationalize an open data program, and measuring the value of open data.
Length: 1 hour, 10 minutes. (Free access with Bucknell login.)