SayPro Field data validation checklists

SayPro Field Data Validation Checklists

SayPro Objective:
To ensure that all educational data collected in the field is accurate, complete, and reliable before submission to the SayPro platform.

---

SayPro Purpose of the Checklist:
This checklist serves as a tool for field staff, data collectors, and supervisors to verify the quality of data at the point of collection. It helps minimize errors, inconsistencies, and omissions that could compromise the validity of research outputs.

---

✅ SayPro Field Data Validation Checklist

1.SayPro General Information

• Is the name of the institution or location clearly and correctly entered?
• Is the date of data collection recorded in the correct format (YYYY-MM-DD)?
• Are the names and IDs of data collectors included and accurate?

2.SayPro Completeness Check

• Are all required fields filled out (no missing values in mandatory columns)?
• Are participant demographic details (age, gender, grade level, etc.) complete?
• Have all sections of the form or template been addressed?

3.SayPro Accuracy & Logic Check

• Are numeric values within expected or logical ranges (e.g., ages 5–20 for students)?
• Do attendance and literacy rates make sense when compared with enrollment numbers?
• Are there any duplicate entries for the same student or institution?

4.SayPro Formatting Compliance

• Is the data recorded in the approved SayPro format (Excel/CSV template)?
• Are all date, number, and text fields using standardized formatting (no merged cells or inconsistent entries)?
• Are codes and categories (e.g., gender: M/F, grade levels) used correctly?

5.SayPro Source Verification

• Is the data traceable to a legitimate source (school register, interview log, etc.)?
• Have supporting documents (photos, forms, attendance logs) been collected and attached if required?
• Has a cross-verification with secondary data sources (e.g., official school reports) been conducted?

6.SayPro Ethical Compliance

• Was informed consent obtained where applicable (e.g., interviews, surveys)?
• Is any personal or sensitive information anonymized or handled as per SayPro privacy standards?

7.SayPro Final Checks

• Was the data reviewed by a supervisor or team lead before upload?
• Are there comments or notes explaining unusual data entries?
• Has the file been named correctly and uploaded to the correct SayPro folder?

---

SayPro Expected Outcome:

• Clean, verified datasets ready for analysis and reporting.
• Reduced risk of errors or rework during later project phases.
• Strengthened credibility of SayPro’s field research operations.