As ocean research moves into the future, so do the expectations around data. This course walks early career researchers through 7 essential themes and 21 topics, adapted from the original 23 Data Things, to help them manage, share, and reuse data with confidence.
A Self-Guided Data Management Course for Early Career Ocean Researchers
Data shapes our world and our oceans. As we continue to study the ocean and create projects that will bring us into the future, we need to have plans for that data to ensure its longevity and reuse. Not only is this best practice to ensure an efficient project, but the Tri-Agency of Canada is moving forward in the future to mandate Data Management Plans as essential parts of ethical research. Improving research is the main impetus behind this course, as that will improve FAIR outcomes.
The 7 Ocean Data Things project is based on 23 Data Things by Helene Blowers, but given an Ocean Data context for early career researchers. The 7 Ocean Data Things project is a self guided course, part of CIOOS’ Data Champions Early start program. It aims to introduce early career researchers to data concepts ranging from as simple as “What is data?” all the way through to each part of a data management plan!
While this course is based on the ’23 Data Things’, we modified it and gave it new context for early career researchers specifically focused on the ocean and related topics. We researched the 23 Things themselves, as well as studied different sectors, such as the ocean industry sector, and young researchers who already worked with the ocean. There were a few of the things that we consolidated to make our course more efficient, leaving only 21 unique topics. Those topics we divided into 7 overarching things, each with 3 modules.
Course Materials
Read the Learning Objectives or start with Thing 1. For teachers, the “Teaching and Learning Guide” uses research on Human Factors in Data Sharing to provide suggestions about how to incorporate this tutorial into lesson plans.
Learning Objectives
This is a self-directed course about data and data management within an ocean research context. Follow along with these modules to understand the best practices to make you an amazing ocean researcher.
There are learning objectives for the entire course itself. If you already meet these objectives, then the course is best taken as a refresher to your knowledge. This course contains 7 Things, each of which is divided into 3 modules, for a total of 21 modules. This division is used to allow the user to pick and choose which modules they feel will be most beneficial to their learning. Each Thing has it’s own associated learning objectives, which you can use to see if the modules within are best taken as a refresher to your own knowledge, or if they are new information to be studied. This is a self-directed course, but can also be taken together with other researchers and used to facilitate discussion, or run as a semi-guided course.
By the time you have finished the 7 Ocean Data Things you will be able to :
- Assess research data management (RDM) and data literacy needs for a particular ocean research problem, or generally.
- Identify major data sources, stakeholders, and tools in the ocean data sector.
- Apply metadata, licensing and data management planning to an ocean research problem.
Thing 1: An ocean of data
By the end of this “thing” you will be able to:
- Define research data.
- Create a data management plan (DMP).
- Understand geospatial and geographic data, and their context within the ocean sector
Thing 1 introduces emerging researchers to the idea that everything is data with the proper context. That means all of the ocean work they do could be data, and making sure that work is always kept within its geospatial context is important. Once ocean data is placed into its proper context, the basics of data management are introduced.
Thing 2: A deeper dive in ocean data
By the end of this “thing” you will be able to:
- Describe the ocean data research lifecycle.
- Create a data management plan (DMP).
- Identify major stakeholders in ocean data.
Thing 2 builds on the data context described in Thing 1, introducing data management plans and how they fit into the research lifecycle. Finally, it talks about ocean organizations and how to recognize and find them.
Thing 3: Why your data matters
By the end of this “thing” you will be able to:
- Relate data literacy practices to an ocean data problem.
- Implement a data interview.
- Use a collection of ocean data search tools
After things 1 and 2 researchers should have a solid baseline understanding of what data is contextually, how to talk about it and how to improve their data literacy. Thing 3 begins introducing more complex topics about data such as issues one might face in trying to discover data. And finally this Thing sets users up with the tools to talk about data to people.
Thing 4: Sharing and Caring with Ocean Data
By the end of this “thing” you will be able to:
- Discuss OCAP and CARE principles in Indigenous Data management.
- Explain active data management principles and feel comfortable beginning to implement them.
- Explain the importance of preservation and sharing in research data management.
- Understand when to restrict sharing for ocean data.
Thing 4 concerns the spectrum of data sharing. It emphasizes why it is important, the best practices to manage it and when things shouldn’t be shared. When considering an ocean’s worth of data it is important to lay the groundwork to understand how to protect, share and preserve that data long term.
Thing 5: On the road to metadata
By the end of this “thing” you will be able to:
- Apply controlled vocabularies to describe ocean data.
- Properly cite an ocean dataset.
- Apply an appropriate license to ocean data.
- Discuss the major metrics used to evaluate ocean data.
Thing 5 talks about properly citing data, and goes into the licenses to apply to do so. Then it introduces the first parts of the theory that unpins metadata: controlled vocabularies.
Thing 6: Managing your metadata
By the end of this “thing” you will be able to:
- Create a metadata schema.
- Develop a data researcher presence in your field.
- Explain the basic ways coding and web design can help RDM outcomes.
Thing 6 brings home the lessons about controlled vocabularies and gets into metadata, the data that describes your data. From there it explains how to translate that data from one schema to the other, and especially when the schemas have different levels of specificity.
Thing 7: Tools of the ocean data trade
By the end of this “thing” you will be able to:
- Use a collection of ocean data tools to collect, clean and analyse data.
- Recognize when data doesn’t make sense, and how to fix it
Thing 7 uses the base knowledge of data and data management plans that learners will have at this point to get into the weeds of specific ocean’s data tools, focusing on some of the most prominent and used tools.
Teaching and Learning Guide
For those who would like to use this tutorial as a teaching aid to their class, we have a few recommendations to help the process go more smoothly, based on Human Factors research.
1. Participation
The first recommendation is to give a percentage of the students’ participation grade as freebie simply for taking the course. We recommend 3-5%. This can be a great low stress way for students to bump up their grade a little, and gives immediate and tangible benefits to taking the course—delayed benefits and only having intrinsic rewards can prevent uptake on courses. If you would like to make sure they have taken the course, simply have them discuss one of the modules or write a short informal piece about something that they learned or found interesting.
2. Scheduling
Our second recommendation is around how this course should be completed. For those taking the course as a self-guided tutorial, whatever speed at which they can most comfortably absorb the information, is the best speed to do this course. However, our recommendation for teaching or taking this tutorial with others, is to set aside time to simply do 1 module a week, absorb the information in it and discuss that module, before the next one.
We have included detailed descriptions of each module, to make it easy to understand and choose which modules are relevant for each person/group’s specific needs.
3. Celebrate Failure
Our third recommendation is to emphasize confidence building and encourage mistakes and ‘failures’ as a learning opportunity. There are real concerns with funding and ability to conduct research if a project is seen as failing. This can lead to decision paralysis and end projects before they even begin due to wanting to do things correctly.
We have identified that when it comes to data sharing, these same concerns hold true. There is concern that data might be shared too far, or that they might make a mistake when anonymizing data, and so it is better to not start at all.
Our recommendation to combat this, is to emphasize that this program will help build their confidence to working towards best practices, and that it is an extremely low stakes course, a great way to learn about data without any worries about how things will turn out. If there are mistakes made, such as in making an account for something or any of the other activities, they should be celebrated as learning opportunities.
More broadly, moving attitudes away from a failure mindset and into a celebration of learning something new will help mitigate these issues on a broader scientific level.
4. Emphasize what is already known
Our final recommendation is based on making the skill gap seem small. If the gap between what students can already do and what they need to learn seems too large, then it will be intimidating and unfun.
This course is designed to be easy to take and understand. It builds on what students already know, and is sub-divided into easy to study module, so that they can choose which ones they feel most excited to learn. The modules introduce data management early, and then build on each skill that is needed to make data management plans function successfully.
The 7 Things
Thing 1: An ocean of data
Module 3 – 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.
Thing 2: A deeper dive in ocean data
Module 4 – 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.
Module 6 – 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.
Thing 3: Why your data matters
Module 8 – 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.
Module 9 – 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.
Thing 4: Sharing and Caring with Ocean Data
Module 12 – 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.
Thing 5: On the road to metadata
Module 13 – 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.
Module 14 – 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.
Thing 6: Managing your metadata
Thing 7: Tools of the ocean data trade
Funding
Funding for the ‘7 Ocean Data Things’ tutorial, a part of the Data Champions Project, brought you by: The Digital Research Alliance of Canada (DRAC).
