7 Ocean Data Things Self-Directed Course

See this page for the Learning Objectives for each Thing.

Modules

Ready, Set, Data!: The first and most basic introduction to data. Assumes limited encounters with data. Goes over what data is contextually within ocean research, providing concrete examples within an ocean’s framework.
Ocean Data For People and the Economy: This connects data to research and introduces the geospatial elements of ocean data. This module also explores how the ocean can be used to help people and the economy.
Introduction to Data Management: This lesson would give concrete steps for implementing data management into research plans. It would also go over the Portage System, including looking at some of the common templates, and what tends to be the standard taxonomy and metadata used within ocean’s research. Emphasize that data management plans can be broken down into smaller, easier to manage pieces when filling it out. As well, DMPs can offer valuable built-in check-ins that make it easier to see if a project is running smoothly or not.

Data Management Plans: This lesson would give concrete steps for implementing data management into research plans. It would also go over the Portage System, including looking at some of the common templates, and what tends to be the standard taxonomy and metadata used within ocean’s research.
Data in the Research Lifecycle: Goes over how data is used now, in that it is now moving forward into a holistic bottom up approach. Specifically in that data is treated as the foundation and lynchpin that it is and is considered in every step right from the conception stage.
Ocean Publishers and Funders: This module talks about specific ocean publishers and funders on a local, national and international scale. It brings into light some of the things that they are looking for from future researchers and challengers learners to do their own independent research on organizations that they might be interested in.

Data Literacy: What is data literacy and how does one become data literate? How is it different from simply understanding data? This lesson teaches participants how to critically examine their ideas and biases about data.
Data Interviews: Talk the talk. How does one even talk about data to other people? What language should they use? This module would help new researchers get comfortable talking about data and challenge them to reach out to and connect with other researchers and members of their organizations over data.
Data Discovery: This lesson would be a hands-on tutorial that teaches about how to search on specific ocean’s databases, and what kind of language and labelling tends to be the standard. (Boolean operators, and other such database quirks). Would also go over the fact that almost all datasets have different protocols/priorities, and there isn’t a standard way of accessing them, so researchers will need to think about and plan how they are going to access the data.

Data Sharing: This lesson would teach the best practices of data sharing, and why it is important to think about how to share data before you even begin your research work.
Data Sharing and CARE: This lesson goes over the pros and cons of sharing data and how to anonymize it, and who would want their data anonymized. Touches briefly on Indigenous data sharing principles and why not all data is meant to be shared. Offers examples specific to oceans.
Creation and Preservation of Data: This lesson introduces learners to the two sides of data storage: short term, active data management during the project and long term data storage. It will emphasize the ways that data can be lost or become cumbersome to use if not actively managed during the project and the fact that their ocean research data could be relevant for decades after they create it.

Citation Culture: This lesson would introduce learners to the idea that data itself benefits from its own citation and attribution, rather than just being bundled/summarized in the research report, and how citation breeds more citation, greater credibility, a larger body of work for replicability studies and allows for networking opportunities with new and open data.
Data Licensing: This lesson would go over the various kinds of licenses one can give to their data, and that data sharing and licensing are opt-in, not opt-out. Sharing doesn’t happen automatically and the plan for how that will be applied for needs to be considered, and built into the time and budget plan.
Controlled Vocabulary: This lesson explains what a controlled vocabulary is and how to use one. It touches on the controlled vocabularies used most often by the actual tools and researchers used in local ocean’s research.

Metadata: This lesson would be one of the major ones! It would introduce metadata and how to use it, what the most common schema are
Walk the Crosswalk: This lesson would touch on basic coding principles such as XSLT and XML. These basic principles and their structures will help learners visualize how to transform data from one metadata schema to the other.
Identifiers and Linked Data: This lesson would have learners create not only an ORCID idea, but also focus on teaching them how to link their research data to their publishing name, and why it is important to make sure that everything is properly credited to them.

Exploring CIOOS Tools: This lesson would involve instruction and activities on a number of ocean’s data tools, specifically CIOOS’ tools.
Dirty Data: This lesson would teach users about dirty data, what it is and how to avoid it. It would culminate with an example packet of dirty data to clean, that is from the tools they have already learned how to use in the previous module
Making Ocean Data Connections: A simple wrap-up and reminder of everything that was learned in the course. Also functions as a simple and easy list of all the modules, without any extra reading.