1. Definition of Community-Generated Data (CGD) and How It Differs from Traditional Data Collection Methods

What is Community-Generated Data (CGD)?

Community-Generated Data (CGD) refers to the data that is actively produced, collected, and managed by individuals or groups within a community. It empowers community members to directly contribute to the data collection process, enabling them to influence decision-making, improve local services, and address community-specific challenges. CGD can come from a variety of sources, such as surveys, community mapping, social media interactions, or environmental monitoring, and is often used to solve issues that matter most to the community.

Key Characteristics of CGD:

• Bottom-up approach: Data is initiated and controlled by the community rather than by external researchers or institutions.
• Community participation: The process of data collection engages the community, building trust and fostering a sense of ownership over the data.
• Local relevance: CGD is hyper-local, focusing on community-specific issues and solutions, which may be overlooked by traditional data collection methods.

Differences between CGD and Traditional Data Collection Methods

Traditional Data Collection Methods:

Traditional data collection methods are typically designed and conducted by institutions, such as governments, NGOs, or research organizations. These methods rely on structured approaches like censuses, national surveys, and administrative data collection, where the community may be participants but are rarely involved in the design, data collection, or data analysis process. This top-down approach often aims to collect data that fits into a larger regional or national framework.

Key Differences:

Example Comparison:

• CGD in Practice: In a small rural village, residents use smartphones to map water access points and track water quality, creating a real-time database to address water scarcity issues.
• Traditional Data Collection: The national government conducts a periodic census to gather data on population, employment, and housing conditions, providing a general overview but lacking the specificity to address immediate local challenges.

2. Types of Data Considered as CGD: Surveys, Social Media Posts, Community Mapping, etc.

Community-Generated Data (CGD) can be produced from various sources, each playing a unique role in capturing different aspects of community life. The following are common types of data that fall under the umbrella of CGD:

1. Surveys and Questionnaires

Overview:
Surveys are one of the most widely used methods for CGD. These surveys are usually designed by community members themselves to gather input on specific local issues, such as housing conditions, public health, or local infrastructure.

Example:
Residents of a neighborhood design and distribute a survey asking community members about their biggest concerns regarding safety and crime. The collected data is used to advocate for increased police presence or community safety initiatives.

2. Community Mapping

Overview:
Community mapping involves using local knowledge to create maps that detail specific elements of a community, such as roads, schools, health centers, or hazards. These maps are often created with the help of digital tools like GPS-enabled devices or mapping software (e.g., Google Maps, OpenStreetMap).

Example:
In informal settlements like Kibera in Nairobi, residents mapped infrastructure such as clean water access points and healthcare centers. These maps were crucial in advocating for municipal investment in infrastructure.

3. Social Media Data

Overview:
Social media platforms such as Twitter, Facebook, and Instagram provide a wealth of CGD, as users share information about their experiences, opinions, and needs in real-time. Social media data can be analyzed for trends, sentiments, or urgent community issues.

Example:
During a natural disaster, residents in a city use Twitter to report flooded areas, damaged roads, and emergency needs. The real-time data is aggregated and used by local government for disaster response.

4. Crowdsourced Data Platforms

Overview:
Crowdsourcing refers to data collected from a large group of people, usually via online platforms or apps. These platforms invite users to contribute specific types of data, such as environmental observations or public health information.

Example:
In New York City, the SeeClickFix app allows residents to report non-emergency issues such as potholes, broken streetlights, and graffiti. The data is used by the local government to prioritize repairs and maintenance.

5. Sensors and IoT Devices

Overview:
Communities can use sensors and Internet of Things (IoT) devices to gather data on environmental conditions, such as air quality, noise levels, and water pollution. This real-time, automated data collection is often integrated into larger CGD efforts.

Example:
In New Delhi, India, communities have placed air quality sensors in local neighborhoods to monitor pollution levels. The data helps raise awareness about air pollution and influences public policy to reduce emissions.

6. Participatory Action Research

Overview:
In participatory action research (PAR), community members work with researchers to collect data about local issues. The focus is on collaborative learning and problem-solving, with data collected through interviews, focus groups, or workshops.

Example:
In a participatory project in Brazil, residents of low-income neighborhoods helped researchers conduct interviews on food insecurity. The findings informed local food distribution programs.

3. The Role of Technology in Facilitating CGD: Mobile Apps, Online Surveys, and Social Media Analytics

Technology plays a pivotal role in the success and scalability of Community-Generated Data (CGD). It allows communities to easily collect, process, analyze, and share data in real time, often with limited resources. Below are some of the most prominent technologies used to facilitate CGD:

1. Mobile Apps

Overview:
Mobile applications designed for CGD can allow individuals to collect and report data on specific local issues. Apps can integrate features such as GPS for geolocation, cameras for photo evidence, and easy-to-use forms for data entry. Mobile apps are particularly useful in remote or underserved communities where desktop access may be limited.

Example:

• Ushahidi (Kenya): This app enables users to report incidents of violence or social injustice via SMS, email, or web. The data is then displayed on a map, providing a real-time picture of local events.
• SeeClickFix (USA): This app enables residents to report non-emergency issues like road damage, enabling local governments to respond quickly.

2. Online Surveys and Platforms

Overview:
Online surveys and forms (e.g., Google Forms, SurveyMonkey) are widely accessible and can be easily distributed via email, social media, or community websites. Online platforms that allow crowdsourcing of data, such as Maptionnaire or OpenStreetMap, also empower communities to engage in CGD initiatives.

Example:

• SABASI: Sabasi is a free to use application that is ideal for all types of researchers, including private and public organisations, communities and individuals, such as students and independent researchers.
• Google Forms (Global): A community group collects data on public transportation use in a small town via an online survey, enabling the group to present the data to the local government for transportation improvements.
• Maptionnaire (Finland): A mapping platform that allows community members to engage in urban planning by providing insights on local land use preferences.

3. Social Media Analytics

Overview:
Social media analytics involves using platforms like Twitter, Facebook, and Instagram to collect data on public sentiment, community issues, or emerging trends. Analytical tools like Hootsuite or Sprout Social can gather data on specific hashtags, keywords, or geolocated posts, allowing real-time insights into community concerns.

Example:

• Twitter Analytics (Global): A local health organization monitors tweets containing keywords related to flu symptoms to detect an outbreak in the region.
• Facebook Pages (Global): Community organizations track user engagement on their Facebook pages to better understand which social issues are resonating with residents and where more engagement is needed.

4. Sensors and IoT Devices

Overview:
Internet of Things (IoT) devices are physical objects embedded with sensors and connected to the internet, allowing them to collect and transmit data autonomously. Communities can use sensors to monitor environmental factors such as air and water quality, temperature, humidity, and noise levels.

Example:

• Air Quality Sensors (USA): Residents in Los Angeles install low-cost air quality sensors in their homes to measure pollution levels. The data is shared with local authorities and environmental NGOs to advocate for better pollution controls.
  
  

5. Crowdsourcing Platforms

Overview:
Crowdsourcing platforms enable the collection of large amounts of data from a community over a short period. These platforms allow users to submit data related to various fields, such as environment, public health, or social justice, creating a collective data set that reflects community concerns.

Example:

• OpenStreetMap (Global): A collaborative project where users can contribute geographic data about their local areas, enabling the creation of detailed, community-led maps.