Research-Grade XLSForms, Ready for Deployment.

This workflow template shows how to programmatically download and access public datasets from various sources including Census Bureau, NASA, open data portals, and government databases. 

Learn to automate data retrieval, handle # large files, use APIs, and integrate multiple data sources. Essential for reproducible research and automated data pipelines.

WHO CAN USE THIS: # - Researchers using public datasets # - Census data analysts # - Climate scientists (NASA, NOAA data) # - Urban planners (city open data) # - Social scientists (government surveys) # - Environmental researchers # - Anyone automating data collection # - Students working with public data # - Data journalists # - Policy analysts needing current data

This template provides a complete, step-by-step guide for your first data # analysis in R. Learn the essential workflow: load data → explore → visualize # → test → report. Perfect for absolute beginners or as a quick reference for # basic exploratory analysis.

A statistically sound EDA workflow with line-by-line explanations.

WHO CAN USE THIS: # - Complete R beginners starting first analysis # - Students in introductory statistics courses # - Researchers new to R (coming from SPSS, Excel, etc.) # - Anyone doing quick exploratory analysis # - Teachers looking for teaching examples # - Data analysts needing a refresher # - Anyone learning data science fundamentals # - Practitioners wanting a simple workflow template # - Consultants doing initial data exploration # - Anyone overwhelmed by complex R workflows

• Actor identification: Captures type of respondent (importer, exporter, economist, trader)
• Input type: Captures the type of imported agricultural input affected by forex changes
• Cost before and after: Numeric fields for costs before and after currency fluctuations
• Percentage change: Optional calculation of percentage change in cost
• Location: Optional GPS for mapping reporting locations
• Notes: Optional text field for additional observations

• Built-In Analytics - % change in footfall = (current vs last month) / last month
• Peak-low season ratio for seasonal volatility
• Demand trend tracking per product
• Cleaner Data
• Numeric validation

• Tracking multiple crops per farm
• Recording observed climate changes and adaptation practices per crop
• Ranking perceived effectiveness of each adaptation
• Capturing challenges and support received

• Vendors can report multiple challenges using the repeat group
• Each challenge has severity and optional frequency per week
• Optional additional details provide context for qualitative analysis
• Clean numeric validation ensures data quality

• Assess compliance with hygiene, safety, and documentation standards
• Capture scope of audit (full facility or specific sections)
• Compare compliance across different respondent types
• Support basic reporting and analysis of non-compliance areas

• Basic assessment of meal quality (taste, variety, portion)
• Evaluation of impact on student health, attendance, and learning
• Works for schools, households, or restaurants providing school meals
• Compatible with Kobo/ODK for quick data collection and simple analytics

• Farmer Identification and Geolocation: Captures farmer details and GPS coordinates to link seed performance data to specific producers and locations.
• Multi-Variety Assessment per Farmer: Supports repeated entry of multiple seed varieties, enabling comparison of different crops and varieties on the same farm.
• Detailed Seed and Crop Information: Records crop type, seed variety name, brand, and seeding rate to document management practices.
• Performance and Resilience Metrics: Collects germination rate, yield, and drought and pest/disease tolerance ratings for comprehensive variety evaluation.
• Built-in Data Validation: Enforces required fields and realistic value ranges to ensure accuracy and consistency of field data.
• Automated Performance Indicators: Automatically classifies germination and yield into clear performance categories (e.g., Poor, Good, High).

• Calculates total and per capita food expenditure
• Computes percentage of income spent per category and overall
• Automatically flags high-risk households spending >50% of income on food
• Dashboard-ready metrics for financial analysis and policy interventions
• Suitable for households, schools, and restaurants

• Qualitative-to-Quantitative Bridge: Digitizes visual PRA tools (Social Maps, Calendars) by combining photo evidence with structured indicator selection for statistical analysis.
• Automated Seasonality Risk: Calculates a 'Seasonality Risk Score' based on the duration of the identified 'Hunger Gap' months to prioritize high-vulnerability communities.
• Visual Evidence Integration: Mandatory image upload fields ensure that the original community-drawn diagrams are preserved as primary source data for the analyst.
• Spatial Logic via Transect Repeats: The repeat group structure allows for systematic data entry during a Transect Walk, capturing variations in land and soil across different ecological zones.
• Data Validity Scoring: Includes a facilitator-led synthesis section that scores the quality of community participation, helping analysts weight the reliability of the qualitative data.

• Target users: Government Agencies, Hospital Administrators, Procurement Officers
• Simple design: Minimal fields for rapid data collection
• Tax coverage: VAT and cess taxes in food trade
• Key checks: Business type, turnover, tax registration, tax paid, margin impact
• Global applicability: Includes international country options
• Notes field: Allows qualitative observations per respondent