Your role as a Local Partner
This article will touch upon the following subjects:
Introduction to the Local Partner Role from a DCT perspective
Organizing data collection efforts
Training your Data Collectors
Data quality - Polygons
Data quality - Farmer details
Data quality - Acorn contracts
Introduction to the Local Partner Role from a DCT perspective
As a Local Partner you are responsible for running the Acorn Project in your region. Your role in Data Collection involves onboarding farmers, managing data collectors, and making sure the data is of good quality. You play a crucial role in the data collection process. Let’s take a closer look at your tasks.
Onboarding farmers: As a Local Partner, you organize the data collection and handle things like giving data collectors the participant agreements and planning meetings with farmers to explain the Acorn Project.
Managing data collectors: As a Local Partner, you are responsible for training and supporting data collectors. Data collectors are often the first people farmers talk to about the Acorn Project. This means data collectors need to explain the project, your organization’s role, and agroforestry. They are also responsible for collecting good data like legal documents and mapping polygons. If you need help with training or other materials, you can contact someone from the Acorn team.
Ensuring data quality: Data collectors are the first to check the data, but as the Local Partner, you are the second. You check that all the data is correct, from polygons and farm details to legal documents like signed agreements.
Organizing data collection efforts
When planning data collection, there are a few important things to keep in mind:
1. Equipment and tools
Make sure your data collectors have the right equipment and tools, including:
A DCT-compatible device
At least one copy of the participant agreement per farmer
The Acorn infographic
Optional: a power bank and additional materials
2. Adaptability
When organizing which data collector goes where, keep the following in mind:
Local language: If your region has many dialects, consider sending a data collector who understands the local language.
Familiarity: Local data collectors can build trust faster with farmers and understand their needs better.
Distance: If farmers live far away, find out when they will be available to avoid multiple trips.
Weather: Plan around the weather. Very hot or cold days can slow down data collection. Remember, safety first.
Culture: Research any cultural obstacles you might experience. In some places, you may need permission from a local leader or chief before talking to farmers.
Tip: Learning about the local culture can help a lot. If local leaders trust you, farmers are more likely to join the project. Since leaders are often busy, try to contact them early.
Training your data collectors
Data collectors play a key role in ensuring data quality and engaging farmers. They are usually the first people to talk to farmers about the Acorn project. They're also responsible for explaining the program clearly, getting the farmer’s consent, and collecting good data. As a Local Partner, it’s your job to train them so they can do this work successfully.
1. Farmer engagement
Data collectors must know how to explain the Acorn program and keep the farmer’s attention. Key topics they need to understand and explain include:
The Acorn program and its benefits
Climate change and its effects on farmers
Carbon and how it relates to climate change
Agroforestry and Acorn’s role in supporting it
They should also be able to explain:
Farmer eligibility for Acorn
Program requirements and obligations
What farmers can expect from Acorn and from the Local Partner
The purpose of the participant agreement and data sharing consent
What data Acorn uses and how it is shared (data sharing consent)
2. Collecting high-quality data
The quality of the data depends on how well the data collectors understand their tools and the concepts behind them.
For polygon quality, data collectors should know:
How to download and use offline maps
How to use a script; how to gather the correct farmer information
Key terms like "Saved," "Submitted," "Enrolled," and "Polygon"
Key terms like "Polygon," "Markers," "Plotting," "Auto-tracking" and "Manual-tracking"
How to track and edit polygons; adjusting, adding and removing markers
What different types of invalid polygons look like
What makes a polygon high or low quality
How to edit and submit profiles
How to recollect data
For farmer detail quality, ensure that data collectors understand what good farmer data looks like for your project. For example, correct contact information is vital for smooth payouts.
3. Acorn contract quality
Data collectors need to explain and gather the following documents:
Data sharing consent (both digitally and on paper)
Participant agreements (both digitally and on paper)
If you need any assistance in training your data collector or would like to make use of the Acorn training materials, reach out to one of your Acorn contacts.
Data quality - polygons
As a Local Partner, it’s your job to check all the polygons submitted via the DCT dashboard. You need to decide whether they meet your standards or need to be recollected.
What is a good polygon?
A good quality polygon is a shape that accurately represents the farm. The size of the polygon is important because only the area within the polygon will be used for measurements.
Too small: The measurements will be incorrect, and the farmer could lose out.
Too large: This can also cause problems with inaccurate data.
Key points to check for polygon quality:
GPS inaccuracy: Does the polygon align with the actual location?
Partial farm area: Is part of the farm missing from the polygon?
Excessive buildings: Are too many buildings included in the polygon?
Unlikely farm location: Is the farm location realistic?
Unnatural shapes: Does the polygon have odd or unrealistic shapes?
Misalignment with natural boundaries: Does the polygon follow the farm's natural borders?
Common issues
Poor quality polygons often happen due to:
Lack of understanding: The data collector might not fully understand how to use the tools or the concepts behind them.
Technical problems: Issues like GPS inaccuracy can affect polygon quality.
Data falsification: Sometimes, a data collector may submit false polygons. Signs of this include too many buildings, strange farm locations, or polygons that don’t follow natural boundaries (such as roads or rivers).
If you suspect that the data is inaccurate or falsified, you should discuss it with the data collector and take appropriate action. If you need help or guidance, contact someone from the Acorn team.
Data quality - farmer details
Farm address: In the DCT app, many address fields are optional because different countries use different systems. However, it is still important to gather as much address information as possible when it is available. Make sure you define what "good quality" address data looks like for your project.
Farm contact information: Accurate contact information is crucial for things like farmer payments or scheduling seedling deliveries. When reviewing farm profiles, ensure that a valid phone number or email address is included.
Data quality - Acorn contracts
Your data collectors will be responsible for gathering two important legal documents: the data sharing consent and the participant agreement. These can be collected either digitally or on paper.
The data sharing consent
This document explains what data is collected, how it will be used, and by whom. The way you check the quality of this document depends on how it was collected.
On paper: The data sharing consent is often part of the larger participant agreement document. If collected on paper, it's your responsibility to ensure all pages are signed correctly and to store the document safely.
Digitally: The digital process guides the user through a form, and checks are done automatically. No further action is needed.
The participant agreement
This agreement outlines the role of the local partner, the expectations Acorn has of the farmer, and what the farmer can expect from Acorn. Similar to the data sharing consent, the way you verify its quality depends on how it was collected.
On paper: The data collector should return one of the two signed copies of the participant agreement. You must ensure all signatures are in place and store the document securely.
Digitally: Pictures of the signed participant agreement are uploaded to the portal as a PDF. Please review the PDF to confirm that all required information has been captured properly.
Data collector incentives
Data collectors need incentives to perform their tasks effectively, and this is often provided through payment. Payment methods can vary, such as paying per plot, by plot size, or per submission. It is important to create a reward system that encourages data collectors to work both accurately and efficiently, while taking into account the specific conditions in the region.