Draft:International Development Data Types

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Digital Data Types Used in International Development

International humanitarian and development projects rely upon analysis of data created by digital technologies to evaluate project performance, manage projects and to identify future needs and opportunities. Artificial intelligence tools, including machine learning, deep learning and deep neural networks, enable increasingly complex analyses that can establish correlations between and amongst that traditional form of analysis might otherwise miss. This article is a resource for international development practitioners seeking to do more with data, specifically to find useful correlations between seemingly disparate data types. It is a community resource placed on Wikipedia so that experts can edit and contribute examples and insights.

Technologies providing data:

1. Mobile network data

2. Satellite data, including from satellites focused on earth observation, communications and internet of things (IOT) networks

3. Sensor data

4. Wearable technology data (a distinct form of sensor data deserving its own consideration)

5. Network data

6. Social media usage data (including over the top, or "OTT" services such as WhatsApp, Facebook, Netflix, etc.)

7. Mobile money transfers

8. Crowdsourced data

9. Human-computer interaction data

10. Weather station data


1. Mobile network data

a. Call detail records (CDRs) are captured every 15 minutes from each individual cell tower. They include:

  • phone number of person calling
  • phone number receiving the call
  • starting time of the call (date and time)
  • call duration
  • the billing phone number charged for the call
  • the identification of the telephone exchange or equipment writing the record
  • a unique sequence number identifying the record
  • additional digits on the called number used to route or charge the call
  • the disposition or the results of the call, indicating, for example, whether or not the call was connected
  • the route by which the call entered the exchange
  • the route by which the call left the exchange
  • call type (voice, SMS, USSD, etc.)
  • any fault condition encountered[1]

Useful information that adds to an understanding of CDRs includes the tower location, height, frequency, coverage area and information on up-time and downtime[2]

b. Radio resource data

"The major functions of the RRC protocol include connection establishment and release functions, broadcast of system information, radio bearer establishment, reconfiguration and release, RRC connection mobility procedures, paging notification and release and outer loop power control."[3]

2. Satellite data

  • Imagery includes visible and invisible light. The bands include:
  • NIR1 (near infrared 1)
  • Red
  • Green
  • Blue
  • Red Edge
  • Yellow
  • Coastal
  • NIR2 (near infrared 2)
  • SWIR-1 (Shortwave infrared)
  • SWIR-2
  • SWIR-3
  • SWIR-4
  • SWIR-5
  • SWIR-6
  • SWIR-7[4]
  • Light Detection and Ranging (LIDAR) uses laser pulses to measure ranges to the Earth and the height of physical objects on the earth's surface.

The two types of LIDAR are topographic (3D dimensions of the earth) and bathymetric (related to water). It can also be used to detect chemicals in the air.[5]

  • Radio Detection and Ranging (RADAR)
  • Unmanned Aerial Systems
  • Hyperspectral Imagery
  • Thermal Imagery
  • Aerial Photography (by manned aircraft or UAV)

Remote sensing satellites can be tasked to collect new imagery. Satellite companies also resell imagery at a discount.[6]

3. Sensor data

  • Water levels
  • Temperature
  • Water acidity
  • Battery levels
  • Lumens
  • Components need replacing
  • Amount of local storage remaining
  • current settings

4. Wearable data

This data comes from smart devices attached onto or inside the body. Data types include:

  • accelerometer data
  • heart rate
  • GPS
  • Gyroscope
  • Compass
  • audio
  • microphone
  • ambient light
  • barometer
  • ambient temperature
  • body temperature[7] [8]

6. Social media usage

  • Number of connections
  • Frequency of posts by type
  • Number of views
  • Number of likes
  • Number of reposts
  • Bulleted list item

7. Mobile Money transfers

  • Sender
  • Recipient
  • Amount
  • Time of transfer
  • Currency
  • Sender location
  • Recipient location
  • How much left in mobile wallet
  • How much cashed out
  •  % of GDP
  • rate of automatic payments usage
  • loan amount
  • loan repayment period
  • loan interest rate

8. Crowdsourced data

  • observations by location and time
  • polling/surveys

9. Human-computer interaction data

  • Average # of interface layers users pass through
  • Amount of time spent on one section of page before scrolling

10. Weather station data[9]

  • temperature
  • Degree days
  • Sun
  • Weather type
  • precipitation
  • pressure
  • Wind
  • Wind Speed

Other useful articles:

  • "Guide to Mobile Data Analytics in Refugee Scenarios"[10]
  • "The top 10 sources of data for international development research"[11]
  • The OECD AI Principles[12]


  1. ^ "Call detail record".
  2. ^ "Call Detail Record - an overview | ScienceDirect Topics".
  3. ^ "Radio Resource Control".
  4. ^ Mineral Mapping Using Simulated Worldview-3 Short-Wave-Infrared Imagery - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/The-proposed-Worldview-3-WV-3-VNIR-and-SWIR-Spectral-Bands_tbl1_258811622
  5. ^ "What is LIDAR".
  6. ^ "Remote Sensing Data Types". 2016-07-26.
  7. ^ "Catalogue".
  8. ^ De Arriba-Pérez, F.; Caeiro-Rodríguez, M.; Santos-Gago, J. M. (2016). "Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios". Sensors (Basel, Switzerland). 16 (9): 1538. doi:10.3390/s16091538. PMC 5038811. PMID 27657081.
  9. ^ "Land-Based Station Data | National Centers for Environmental Information (NCEI) formerly known as National Climatic Data Center (NCDC)".
  10. ^ Guide to Mobile Data Analytics in Refugee Scenarios: The 'Data for Refugees Challenge' Study. Springer. 2019. ISBN 9783030125530.
  11. ^ Holden, Joseph (2016-03-16). "The top 10 sources of data for international development research". The Guardian.
  12. ^ "OECD Principles on Artificial Intelligence - Organisation for Economic Co-operation and Development".