Funding for Agri-food Data Canada is provided in part by the Canada First Research Excellence Fund
Data Needs Context
Understanding Data Requires Context Data without context is challenging to interpret and utilize effectively. Consider an example: raw numbers or text without additional information can be ambiguous and meaningless. Without context, data fails to convey its full value or purpose. By providing additional information, we can place data within a specific context, making it more…
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From Siloed Systems to Shared Success: Why a Shared Infrastructure Makes Sense
Part of the blog series on Collaborative Research IT Infrastructure In our last post, we talked about the problem with researchers ‘DIYing’ their IT infrastructure, and today we’ll explore a few benefits that researchers and institutions can have for going with a shared IT infrastructure. As research grows increasingly data-driven, the challenges of managing IT…
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Happy Holidays!
I hope you’ve enjoyed our Blog posts in 2024! There are more to come in 2025 – but we’ll be taking a short holiday break! See you back in 2025 – January 10 will be our first blogpost of the year! Happy New Year! Photo generated by AI
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What is a Self-Addressing Identifier?
A Self-Addressing Identifier (SAIDs) is a key feature of an Overlays Capture Architecture (OCA) schema. SAIDs are a type of digest which are calculated from one-way hashing functions. Let’s break this idea down further and explore. Hashing functions create digests A hashing function is a calculation you can perform on something digital. The function takes…
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GitHub for Documentation
GitHub is more than just a code repository, it is a a powerful tool for collaborative documentation and standards development. GitHub is an important tool for the development of FAIR data. In the context of writing and maintaining documentation, GitHub provides a comprehensive ecosystem that enhances the quality, accessibility, and efficiency of the process. Here’s…
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The “Elephant in the Room” – Data Ownership
Alrighty let’s address that proverbial Elephant in the Room – WHO owns the data? This question goes round and round and round – but does it ever land comfortably for everyone? We have been discussing this topic for quite a while here at Agri-food Data Canada, and it keeps cropping up in all the projects…
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From Siloed Systems to Shared Success: The Problem with Doing It All Yourself
Part of the blog series on Collaborative Research IT Infrastructure In our first post, we discussed the challenges universities face with fragmented IT systems and the need for unified solutions. Here, we explore the specific issues that arise when research teams independently manage their IT infrastructure. Research IT infrastructure often develops in response to immediate…
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Data – So What?
I have been attending industry-focused meetings over the past month and I’m finding the different perspectives regarding agri-food data very interesting and want to bring some of my thoughts to light. I first want to talk about my interpretation of the academic views. In research and academia we focus on Research Data Management, how and…
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Ontologies for agriculture
Using an ontology in agri-food research provides a structured and standardized way to manage the complex data that is common in this field. Ontologies are an important tool to improve data FAIRness. Ontologies define relationships between concepts, allowing researchers to organize information about crops, livestock, environmental conditions, agricultural practices, and food systems in a consistent…
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From Siloed Systems to Shared Success: A Blog Series on Collaborative Research IT Infrastructure
In today’s data-driven research environment, universities face a growing challenge: while researchers excel at pushing the boundaries of knowledge, they often face challenges managing the technology that supports their work. Many university research teams still operate on isolated, improvised systems for computing and data storage—servers tucked in closets or offices, ad-hoc storage solutions, and no…
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