Data has an ever-increasing role in agriculture. From input decisions to changes in production practices to increasing levels of automation, data is powering progress for farmers. Data is also being collected in many different ways around the farm. With cameras and sensors along for the ride on many passes through the field, farmers have a whole new view of their land and crop performance.
As data shows so much promise on the farm, it’s no wonder why bringing it back to the basics of data management is so important. Ensuring that data has a solid foundation – built on data standardization and harmonization – protects the integrity of the dataset and increases effectiveness when the data is put to use.
What is data standardization?
Data standardization is the process of converting data into a standard format and utilizing that across the board. One agronomy data standardization example would be making all plant measurements using the metric system. More generally, data standardization can be as simple as listing all dates in a dataset as YYYY-MM-DD.
Data standardization ensures all people recording data for experiments are measuring and entering data in the same way. Typically, this is determined prior to an experiment in a standard operating procedure (SOP). This keeps the data collection team aligned and minimizes data cleanup after data collection is complete.
The purpose of data standardization is to improve data quality and usability, reduce errors, and improve communication and collaboration across teams. Overall, this strategy results in improved decision-making generally and in agronomy applications.
Why is data standardization important?
Data standardization plays an important role in ensuring data-based agronomy decisions are effective. In fact, data standardization can be the bedrock for the critical collaboration that occurs between growers, farmers, agronomists, and industry researchers. The benefits unfold in a few different areas:
- Upgrading data quality and usability: with fewer errors in data entry, data quality, and usability are simultaneously improved. This is a big net positive!
- Enhancing communication and collaboration: having standardized data actually makes the data more shareable across team members. It ensures everyone is speaking the same language. This improved transparency allows for more collaboration and communication within and across teams.
- Improving decision-making: clean and consistent data enables researchers to focus on the important questions and tasks at hand, rather than worrying about whether data is formatted correctly or entered incorrectly. Standardized data is immediately available for analysis and collaboration. This increases efficiency and speeds up the process of finding the answer or making the final decision. Agronomists, researchers, and farmers can move quickly towards necessary changes or adjustments. Making fast decisions and learning quickly enables innovation at a faster pace.
What is data harmonization?
Picture a symphony hall with music swelling to the rafters. That music is only a beautiful sound if everyone is in harmony! When different notes, heard simultaneously, come together in a single composition, that’s harmony – and it’s a sweet sound.
Data harmonization is similar to musical harmony. It’s the act of unifying data from several formats or sources into a single location. This combination of data from different sources provides people with a view of data from different sources represented in a similar way. When all the data comes together to form the big picture, you can get a totally different view.
A general example of data harmonization would be bringing together multiple years of a similar study on a single topic. Agronomically speaking, data harmonization might mean bringing together data collected in separate passes across the field, or ingesting data from a worldwide database to complement local data collected in an on-farm experiment.
Data harmonization and standardization work together to ensure data is apples to apples – or all speaking the same language – and ready for analysis. They improve data quality and reduce redundancy, making data transfer and collaboration easy.
Even though it’s critically important, standardizing and harmonizing data isn’t always easy. Legacy data, multiple data sources, and large raw datasets can make this process complex.
What is Agmatix’s role in data standardization and harmonization?
Agmatix, a global informatics company, is dedicated to growing data for impact through innovative platforms that empower field-level decisions. A big part of enabling agronomic insights is agricultural data harmonization. Agmatix’s Axiom technology includes an agronomic data harmonization platform that ingests and integrates data for predictive modeling, agronomic research, and field trials.
Axiom technology is used by in-house ontologies with several sources to standardize and harmonize data. This powers big data’s transformation into powerful insights. Agronomic analysis software speeds the time to insights from this data through powerful insights and models that can even leverage legacy data. The cross-trial analysis becomes possible, providing an additional perspective.
The GUARDS (Growing Universal Agronomic Data Standard) protocol enables agronomic data standardization. It’s intended to translate data – regardless of the unique way a researcher preserved it – into a single common language. This translation process means that any researcher in the world can use that data – and it’s based on the FAIR data principles.
The GUARDS protocol system actively monitors data integrity and quality using ML. This proactive approach then alerts for abnormalities in datasets when needed. The unit converter translates measurements into a standardized unit. Through this process, databases and values can be customized.
Standardized and harmonized data fuels decision-making in many areas of agriculture. Having the right tools to support these decisions can be critical. Agmatix has platforms that can take data from standardization and harmonization all the way to action through the Digital Crop Advisor crop nutrition recommendation tool. Once data is standardized, it can be ingested in a unified, cloud-based system to share and collaborate within a single organization or with external collaborators. Having a unified platform enables seamless data sharing and collaboration. This is one example of Agmatix and data together fueling action that makes a real difference for farmers and the environment.
You may be interested in:
The Role of Data Standardization in Driving Efficiency Across the
Agriculture Supply Chain
Benefits of Sharing Agronomic Data and Using Data Standardization
Data’s foundation for evolution
No matter how much, or how little, data you work with, data standardization and harmonization are extremely important. Transparent, high-quality data ensures that data-driven decisions will make each season better than the last. These data-driven decisions can help overcome some of agriculture’s biggest challenges – and make a meaningful difference in supplying a growing world with healthy, accessible, and sustainable fuel.
At Agmatix, our mission is to power agronomy data standardization and harmonization to turn it into actionable insights. We want to make this process seamless so you can focus on what’s important – making efficient and informed decisions. Let us help you!
