Research Data Management Short Online Short-Seminar
What a neat study finding, can you do it again? Reproducible results is an essential benchmark in research, regardless of discipline.
Research should be reproducible in two ways. First, your research should be thoroughly described so that other researchers could replicate the study independent of your involvement. Second, your specific research finding must be reproducible using your own data and code by someone else.
In this session, you will learn about best practices for...
Neglecting to develop and implement a detailed naming convention for your data files. Data hot mess. Failing to sync and back up your data in three separate locations. Deadly data loss. Saving your data to a proprietary file format that is on the verge of insolvency. Walking dead data. Facing the shame of having your publication retracted due to data irregularities. The horror. The horror.
Data management is not easy, as is evidenced by these true horror stories of data quality gone wrong. Learn from (and wince...
Data management focuses on data organization and sharing. DASH and Dataverse are platforms to help you share your work and increase your scholarly impact. In this session, learn practices and platforms to achieve your open access goals!
In celebration of Open Access Week 2020, join this conversational panel with members of the Harvard community as we discuss considerations, benefits and challenges of open scholarship. Hear from a variety of domain experts working on projects designed to democratize knowledge and remove barriers to research, teaching and learning.
Research papers and protocol organization in labs often lack detailed instructions for repeating experiments. protocols.io is an open-access platform for researchers to create step-by-step, interactive and dynamic protocols that can be run on mobile or web. Researchers can share protocols with colleagues, collaborators, the scientific community or make them public, with ease and efficiency...
Digital Scholarship Discussion Group lunchtime meet up -- OA edition!
The Long 19th Amendment Project is a research and teaching collaboration spearheaded by the Schlesinger Library at Harvard’s Radcliffe Institute for Advanced Study. This open-access digital portal facilitates interdisciplinary, transnational scholarship and innovative teaching around the history of gender and voting rights in the United States.
A part of the data workflow is preparing the data for analysis. Some of this involves data cleaning, where errors in the data are identified and corrected or formatting made consistent. This step must be taken with the same care and attention to reproducibility as the analysis.
OpenRefine (formerly Google Refine) is a powerful free and open source tool for working with messy data: cleaning it and transforming it from one format into another. Many people comment that this tool saves them literally months of work trying to make these edits by hand!
Turn messy data into tidy data! Much of your time will be spent in this ‘data wrangling’ stage. It’s not the most fun, but it’s necessary and food data organization is the foundation of data analysis. Learn the rules for a 'tidy dataset' in order to clean and prepare your data with examples and tools.
This workshop will build on principles from the June Tidy Data is Good Data seminar, and explore how to turn messy data into tidy data using simple functions in R. Note: You do not have to have...