Funding for Agri-food Data Canada is provided in part by the Canada First Research Excellence Fund
A Peek Inside the Ontario Dairy Research Centre – Part 3
On our last blog post, we talked about events and feed data collected routinely at the Ontario Dairy Research Centre (ODRC). Today we’ll talk about milk and milk analysis data. If you missed the other parts of this series, check the links at the end of this post to learn more about other types of…
ViewOrganizing your data – Research Data Management (RDM)
Show of hands – how many people reading this blog know where their current research data can be found on their laptop or computer? No peaking and no searching! Can you tell me where your data is without looking? Let’s be honest now! I suspect a number do know where your data is, but I…
ViewGuidance for designing datasets
Recommendation: Long format of datasets is recommended for schema documentation. Long format is more flexible because it is more general. The schema is reusable for other experiments, either by the researcher or by others. It is also easier to reuse the data and combine it with similar experiments. Data must help answer specific questions or…
ViewA Peek Inside the Ontario Dairy Research Centre – Part 2
Let’s continue to peek into more of the types of data collected routinely at the Ontario Dairy Research Centre (ODRC). Today we’ll talk about health, reproductive, preventive, and research-specific events data, as well as feed analysis and intake data. If you missed part one of this series, read A Peek Inside the Ontario Dairy Research…
ViewResearch Data Life Cycle
Anyone who knows me or has sat in one of my classes, will know how much I LOVE the data life cycle. As researchers we have been taught and embraced the research life cycle and I’m sure many of you could recite how that works: Idea → Research proposal → Funding proposal → Data collection…
ViewThe different types of files used in Overlays Capture Architecture
Overlays Capture Architecture (OCA) is a structured way to describe data schemas. By making a schema a collection of separate functional parts bundled together, you can introduce the benefits of modular design. A modular schema means you can have multiple parties using their own expertise for separate features of a schema. For example, you could…
ViewA Peek Inside the Ontario Dairy Research Centre – Part 1
The Ontario Dairy Research Centre (ODRC) stands as an example to the importance of data-driven research in the dairy industry. With a dedicated commitment to several areas of dairy research, this research centre has been collecting and storing an extensive array of data through regular operations and exciting research projects. Today, we’re peeking into three…
ViewHistorical Data – Where is it?
Have you heard the news? The Ontario Agricultural College will be 150 years old in 2024. Wow!! 150 years of being recognized for our research, our students, our faculty, and our community in the areas of food, agriculture, communities and the environment. Now, as a data archivist and researcher, I only have one question: Where…
ViewCrafting Effective Machine-Actionable Schemas with SemanticEngine.org
In the realm of data analysis, having well-structured and clear data is fundamental for meaningful insights. Data schemas provide a blueprint for understanding and organizing datasets. In today’s digital landscape, where automation and machine-readability are vital, machine-actionable schemas offer enhanced utility. This blog post will guide you through the process of creating a machine-actionable schema…
ViewExploring Data Collection at Ontario’s Livestock Research Centres
This blog post marks the beginning of a series exploring the invaluable data collected at livestock research centres owned by the Agricultural Research Institute of Ontario and managed by the University of Guelph through the Ontario Agri-Food Innovation Alliance. These centres are instrumental in advancing agricultural knowledge and practice, boasting remarkable infrastructure for research data…
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