Background: Scientific field observation by members of the public is known as citizen science and has become popular all across the world. Citizen science is advantageous for collecting large amounts of scientific data and can be seen as a crowdsourcing approach to data collection. Information and communications technology is enhancing the availability of citizen science. Mobile devices, such as mobile phones, that have a digital camera with a global positioning system (GPS) are necessities of contemporary life and can be utilized as powerful observation tools in citizen science. New information: We developed a web-based system as a data collection tool for citizen science. Participants submit an e-mail with a photo taken by their mobile phones. The photos contain location information, which can be easily and automatically embedded if the mobile phone is equipped with GPS. We collaborated with regional event managers, such as museum curators, and held citizen science events in each region and for various target taxonomic groups. All photos were stored in our data server, and the organisms were taxonomically identified by citizen scientists, regional managers, and us. In total, 154 species and 843 data records were collected in this project conducted from 2011 to 2016.

Map Data Crowdsourcing Market Outlook

According to our latest research, the global map data crowdsourcing market size reached USD 2.6 billion in 2024, demonstrating robust momentum driven by the proliferation of connected devices and the increasing demand for real-time geospatial information. The market is projected to expand at a CAGR of 13.2% from 2025 to 2033, with the total market size expected to reach USD 7.9 billion by 2033. This impressive growth is primarily fueled by advancements in mobile technology, the rise of location-based services, and the need for accurate, up-to-date mapping data across various industries.

One of the primary growth factors propelling the map data crowdsourcing market is the widespread adoption of smartphones and mobile devices equipped with GPS functionality. These devices have enabled millions of users worldwide to contribute geospatial data, thereby enhancing the accuracy and richness of digital maps. The ubiquity of mobile internet access further accelerates the aggregation and dissemination of real-time mapping information, which is crucial for applications such as navigation, traffic management, and disaster response. As urban populations swell and smart city initiatives multiply, the need for granular, up-to-date map data becomes even more critical, driving organizations and governments to increasingly leverage crowdsourced solutions. The ease of participation and the ability to rapidly update maps in response to changing conditions are significant advantages that continue to foster market expansion.

Another significant driver for the map data crowdsourcing market is the growing reliance on location-based services (LBS) across sectors such as transportation, retail, and utilities. Businesses are leveraging crowdsourced map data to optimize logistics, enhance customer experiences, and streamline operations. For instance, ride-sharing platforms, delivery services, and urban mobility providers depend on highly accurate and current mapping data to ensure efficient routing and timely services. Additionally, the integration of artificial intelligence and machine learning with crowdsourced data is enabling more sophisticated analytics and predictive insights, further increasing the value proposition of map data crowdsourcing. This synergy between advanced analytics and user-generated data is expected to unlock new opportunities for innovation and operational efficiency in both the public and private sectors.

The increasing frequency and severity of natural disasters have also underscored the importance of real-time, accurate mapping data. Crowdsourced map data plays a pivotal role in disaster management by facilitating rapid assessment of affected areas, enabling efficient allocation of resources, and supporting emergency response operations. Government agencies and humanitarian organizations are increasingly adopting crowdsourcing platforms to gather situational intelligence from affected populations, thereby enhancing their ability to respond effectively. This trend is expected to continue as climate change drives more frequent extreme weather events, necessitating agile and scalable mapping solutions that only crowdsourcing can provide. Furthermore, the collaborative nature of crowdsourcing fosters community engagement and resilience, which are vital components of modern disaster preparedness strategies.

Regionally, the map data crowdsourcing market is witnessing significant growth in Asia Pacific, North America, and Europe, with each region exhibiting unique drivers and adoption patterns. North America leads in terms of market share, supported by a mature digital infrastructure and a high concentration of technology providers. Europe follows closely, propelled by strong regulatory support for open data initiatives and active participation from both public and private sectors. Asia Pacific, meanwhile, is emerging as the fastest-growing region, fueled by rapid urbanization, expanding mobile penetration, and substantial investments in smart city projects. Latin America and the Middle East & Africa are also showing promising growth prospects, albeit from a smaller base, as governments and enterprises in these regions increasingly recognize the value of crowdsourced mapping for urban planning and infrastructure development.

Data attained through crowdsourcing have an essential role in the development of computer vision algorithms. Crowdsourced data might include reporting biases, since crowdworkers usually describe what is “worth saying" in addition to images’ content. We explore how the unprecedented events of 2020, including the unrest surrounding racial discrimination, and the COVID-19 pandemic, might be refected in responses to an open-ended annotation task on people images, originally executed in 2018 and replicated in 2020. Analyzing themes of Identity and Health conveyed in workers’ tags, we found evidence that supports the potential for temporal sensitivity in crowdsourced data. The 2020 data exhibit more race-marking of images depicting non-Whites, as well as an increase in tags describing Weight. We relate our findings to the emerging research on crowdworkers’ moods. This dataset includes all the tags, provided by crowdworkers, relevant to the topics of Health and Identity, providing aggregated counts of the occurrences of each tag in 2018 and 2020. Additionally, separate counts of the occurrences of each tag in 2018 and 2020 are provided for each depicted race (a.k.a., White, Latino, Black and Asian).

Map Data Crowdsourcing Market Outlook

According to our latest research, the global map data crowdsourcing market size reached USD 1.92 billion in 2024, demonstrating robust expansion driven by the proliferation of location-based services and the increasing adoption of real-time mapping solutions. The market is set to grow at a CAGR of 14.7% from 2025 to 2033, with the total value forecasted to reach USD 6.07 billion by 2033. This impressive growth trajectory is underpinned by the rising integration of crowdsourced data in navigation, urban planning, and disaster management applications, as well as the accelerating digitization of mapping ecosystems worldwide.

A primary growth factor for the map data crowdsourcing market is the exponential rise in smartphone penetration and the widespread use of location-enabled applications. With billions of individuals using mobile devices daily, there is an ever-growing pool of real-time data contributors. This surge in user-generated content enhances the granularity, accuracy, and timeliness of digital maps, making them more relevant for navigation, traffic management, and emergency response. Moreover, the democratization of mapping through open-source platforms such as OpenStreetMap has empowered both individuals and organizations to contribute, validate, and update geospatial information, thereby accelerating the pace of innovation and reducing reliance on traditional, labor-intensive mapping techniques.

Another significant driver is the increasing demand for hyper-local and up-to-date mapping data across industries such as transportation, automotive, and urban planning. The evolution of smart mobility solutions, autonomous vehicles, and intelligent transportation systems is heavily reliant on precise, real-time map data. Crowdsourcing offers a scalable and cost-effective approach to capturing nuanced changes in road networks, traffic patterns, and points of interest. This agility is particularly valuable in rapidly urbanizing regions where infrastructure is constantly evolving. Additionally, the integration of artificial intelligence and machine learning with crowdsourced data streams is enhancing the ability to detect anomalies, predict traffic conditions, and optimize routing, further fueling market growth.

The market is also witnessing robust participation from government agencies and public sector organizations, which are leveraging crowdsourced mapping for disaster management, urban development, and public safety initiatives. By harnessing the collective intelligence of citizens, governments can quickly identify hazards, monitor infrastructure conditions, and coordinate emergency responses. This participatory approach not only improves situational awareness but also fosters community engagement and transparency. Furthermore, the growing emphasis on sustainability and smart city initiatives is prompting municipalities to adopt crowdsourced mapping as a tool for resource optimization, environmental monitoring, and citizen-centric planning.

From a regional perspective, North America currently leads the map data crowdsourcing market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The high adoption rate of advanced mapping technologies, strong presence of key market players, and supportive regulatory frameworks in these regions are key contributors to their dominance. Meanwhile, Asia Pacific is poised for the fastest growth over the forecast period, propelled by rapid urbanization, expanding digital infrastructure, and increasing government investments in smart city projects. Latin America, the Middle East, and Africa are also emerging as promising markets, driven by the need for improved transportation, disaster resilience, and public service delivery.

Component Analysis

The map data crowdsourcing market is segmented by component into software and services. The software segment encompasses platforms and applications that facilitate the collection, validation, and integration of crowdsourced map data. These solutions are central to the market’s expansion, as they provide the technological backbone for aggregating vast amounts of geospatial information from diverse sources. Advanced mapping software is increasingly incorporating features such as real-time data processing, AI-driven anomaly detection, and intuitive user interfaces, making it easier for individuals and organizations to contribute and consume mapping data. As the demand for dynamic and int

Crowdsourced Work Zone Data Market Outlook

As per our latest research, the global crowdsourced work zone data market size reached USD 1.38 billion in 2024, demonstrating robust expansion driven by the growing need for real-time, accurate roadwork and traffic information. The market is expected to grow at a CAGR of 17.1% from 2025 to 2033, reaching a projected value of USD 5.10 billion by 2033. This significant growth is being fueled by increasing investments in smart infrastructure, rising adoption of connected vehicles, and the necessity for enhanced traffic and safety management solutions in urban and interurban environments.

One of the primary growth factors for the crowdsourced work zone data market is the proliferation of connected devices and mobile applications that empower drivers, construction workers, and traffic authorities to share real-time information. The widespread penetration of smartphones and the integration of advanced sensors in vehicles have made it easier to collect, aggregate, and disseminate work zone data efficiently. This democratization of data collection has led to more reliable and timely updates regarding road conditions, work zones, and traffic incidents, which in turn enhances road safety and optimizes traffic flow. As governments and private entities continue to prioritize smart city initiatives, the demand for comprehensive crowdsourced data solutions is expected to rise, further accelerating market growth.

Another critical factor driving the expansion of the crowdsourced work zone data market is the increasing adoption of intelligent transportation systems (ITS) by transportation authorities and urban planners. These systems rely heavily on accurate, real-time data to enable dynamic traffic management, route optimization, and incident response. Crowdsourced data, with its ability to provide granular and up-to-date information, plays a pivotal role in enhancing the efficiency and effectiveness of ITS deployments. Additionally, as cities face mounting pressures from population growth and urbanization, the need for scalable, cost-effective solutions to manage work zones and minimize disruptions has become paramount. Crowdsourced data platforms offer a flexible alternative to traditional data collection methods, reducing operational costs while improving situational awareness.

The growing focus on road safety and regulatory compliance is also a significant catalyst for market growth. Governments worldwide are enacting stricter regulations and safety standards for work zones, necessitating the use of advanced monitoring and management tools. Crowdsourced work zone data enables authorities to quickly identify hazardous conditions, deploy resources more effectively, and communicate critical information to drivers and construction teams. This not only helps in reducing accidents and fatalities but also ensures smoother project execution and compliance with legal mandates. As the transportation ecosystem becomes increasingly interconnected, the synergy between public agencies, private companies, and end-users is expected to unlock new opportunities for innovation and market expansion.

From a regional perspective, North America currently dominates the crowdsourced work zone data market, accounting for over 38% of the global market share in 2024. This is primarily due to the region's advanced transportation infrastructure, high adoption of digital technologies, and supportive regulatory frameworks. Europe follows closely, benefiting from significant investments in smart mobility and stringent road safety regulations. The Asia Pacific region is poised for the fastest growth, with a projected CAGR of 19.4% between 2025 and 2033, driven by rapid urbanization, expanding road networks, and increasing government initiatives to modernize transportation systems. Latin America and the Middle East & Africa are also witnessing steady growth, supported by ongoing infrastructure development and rising awareness of the benefits of crowdsourced data solutions.

Data Ty

Road Hazard Crowdsourcing Platform Market Outlook

According to our latest research, the global Road Hazard Crowdsourcing Platform market size in 2024 stands at USD 1.42 billion. The market is experiencing a robust expansion, with a compound annual growth rate (CAGR) of 17.8% from 2025 to 2033. By the end of 2033, the market is forecasted to reach USD 6.13 billion. This remarkable growth is primarily driven by the increasing adoption of real-time data sharing technologies and the pressing need for enhanced road safety and efficient traffic management worldwide. As per our latest research, the surge in connected vehicles, proliferation of smartphones, and the growing emphasis on smart city initiatives are significantly propelling the demand for road hazard crowdsourcing platforms across various regions.

The growth trajectory of the Road Hazard Crowdsourcing Platform market is underpinned by several pivotal factors. The rapid urbanization witnessed globally has intensified the challenges of traffic congestion and road safety hazards. Consequently, governments and urban planners are leveraging crowdsourced data to gain real-time insights into road conditions and hazards, thereby enabling prompt responses and proactive infrastructure maintenance. The integration of advanced technologies such as artificial intelligence, machine learning, and geospatial analytics has further empowered these platforms to deliver more accurate, actionable, and timely information. These technological advancements, coupled with the increasing penetration of mobile devices, have made it easier for individuals and organizations to contribute and access hazard data, fostering an ecosystem of collaborative road safety management.

Another significant driver of market growth is the rising collaboration between public sector entities, such as government agencies and transportation authorities, and private organizations. These partnerships are facilitating the development and deployment of comprehensive road hazard crowdsourcing solutions that cater to diverse end-user needs. The ability to aggregate and analyze vast volumes of user-generated data enables stakeholders to identify patterns, predict potential hazards, and implement targeted interventions. Moreover, the integration of these platforms with existing navigation and traffic management systems is streamlining communication between road users and authorities, ultimately enhancing the overall efficiency of urban transportation networks. The growing awareness about the benefits of crowdsourced road hazard reporting, including cost savings, improved response times, and enhanced public safety, is further fueling market expansion.

The market is also benefitting from the increasing focus on sustainability and smart infrastructure development. As cities strive to become smarter and more resilient, the adoption of road hazard crowdsourcing platforms is emerging as a critical component of urban mobility strategies. These platforms play a vital role in supporting infrastructure maintenance by enabling timely identification and resolution of road defects, thereby extending the lifespan of road assets and reducing repair costs. Furthermore, the integration of crowdsourced data with public safety initiatives is helping authorities to mitigate accident risks, optimize emergency response, and enhance the overall quality of life for citizens. The growing emphasis on data-driven decision-making and the proliferation of Internet of Things (IoT) devices are expected to further accelerate the adoption of road hazard crowdsourcing solutions in the coming years.

From a regional perspective, North America currently dominates the Road Hazard Crowdsourcing Platform market, accounting for the largest share in 2024. This leadership is attributed to the region's advanced technological infrastructure, high smartphone penetration, and proactive government initiatives aimed at improving road safety. Europe follows closely, driven by stringent regulatory frameworks and the widespread adoption of smart transportation solutions. The Asia Pacific region is poised for the fastest growth during the forecast period, fueled by rapid urbanization, increasing investments in smart city projects, and the growing adoption of connected vehicles. Latin America and the Middle East & Africa are also witnessing steady growth, supported by rising awareness about road safety and the gradual modernization of transportation infrastructure.

Volunteered geographical information (VGI) and citizen science have become important sources data for much scientific research. In the domain of land cover, crowdsourcing can provide a high temporal resolution data to support different analyses of landscape processes. However, the scientists may have little control over what gets recorded by the crowd, providing a potential source of error and uncertainty. This study compared analyses of crowdsourced land cover data that were contributed by different groups, based on nationality (labelled Gondor and Non-Gondor) and on domain experience (labelled Expert and Non-Expert). The analyses used a geographically weighted model to generate maps of land cover and compared the maps generated by the different groups. The results highlight the differences between the maps how specific land cover classes were under- and over-estimated. As crowdsourced data and citizen science are increasingly used to replace data collected under the designed experiment, this paper highlights the importance of considering between group variations and their impacts on the results of analyses. Critically, differences in the way that landscape features are conceptualised by different groups of contributors need to be considered when using crowdsourced data in formal scientific analyses. The discussion considers the potential for variation in crowdsourced data, the relativist nature of land cover and suggests a number of areas for future research. The key finding is that the veracity of citizen science data is not the critical issue per se. Rather, it is important to consider the impacts of differences in the semantics, affordances and functions associated with landscape features held by different groups of crowdsourced data contributors.

Drive Test Data Crowdsourcing Market Outlook

According to our latest research, the global Drive Test Data Crowdsourcing market size reached USD 1.42 billion in 2024. The market is anticipated to witness a robust CAGR of 18.6% during the forecast period, with the market projected to reach USD 7.07 billion by 2033. This impressive growth trajectory is primarily driven by the increasing demand for real-time, cost-effective, and large-scale network performance insights, as well as the proliferation of connected devices and advancements in mobile technologies worldwide.

One of the primary growth factors boosting the Drive Test Data Crowdsourcing market is the exponential increase in mobile data traffic and the need for telecom operators to optimize their network infrastructure. With the advent of 5G technology and the rapid expansion of IoT ecosystems, operators are under immense pressure to ensure seamless connectivity and superior quality of service (QoS) for end users. Traditional drive testing methods have proven to be resource-intensive and limited in scope, prompting the shift towards crowdsourced solutions. By leveraging data from millions of devices, operators can gain granular insights into network performance, coverage gaps, and user experiences across diverse geographies, ultimately enabling more efficient network planning and optimization.

Another significant driver is the rising adoption of smartphones, connected vehicles, and IoT devices, which act as continuous sources of network performance data. The ubiquity of these devices allows for the collection of vast amounts of real-time data, providing a comprehensive view of network conditions in urban and rural settings alike. This democratization of data collection not only reduces operational costs but also accelerates the identification of network issues, enabling proactive maintenance and faster troubleshooting. Furthermore, advancements in data analytics and artificial intelligence have enhanced the ability to process and interpret large datasets, delivering actionable insights to telecom operators, network equipment manufacturers, and regulatory bodies.

Regulatory support and industry collaboration have also played a crucial role in market expansion. Regulatory bodies across regions are increasingly mandating transparent and accurate reporting of network performance metrics to ensure fair competition and improve consumer satisfaction. Crowdsourced drive test data provides an unbiased and scalable approach to meeting these regulatory requirements. Additionally, partnerships between telecom operators, technology vendors, and analytics firms are fostering innovation and driving the adoption of standardized methodologies for data collection and analysis. These collaborative efforts are expected to further accelerate market growth and facilitate the development of next-generation network solutions.

From a regional perspective, Asia Pacific has emerged as the fastest-growing market, fueled by the rapid expansion of mobile networks, rising smartphone penetration, and significant investments in 5G infrastructure. North America and Europe continue to lead in terms of technological adoption and regulatory frameworks, while Latin America and the Middle East & Africa are exhibiting steady growth, driven by increasing digitalization initiatives and improving telecom infrastructure. Each region presents unique opportunities and challenges, but the overarching trend remains the same: the shift towards data-driven, crowdsourced approaches for network optimization and quality assurance is reshaping the global telecom landscape.

Component Analysis

The Drive Test Data Crowdsourcing market is segmented by component into Software and Services, each playing a pivotal role in the market’s value chain. The software segment encompasses advanced analytics platforms, data collection tools, and visualization dashboards that enable seamless integration, processing, and interpretation of crowdsourced data. These solutions are designed to handle large volumes of heterogeneous data generated by diverse sources, offering real-time insights into network performance and user experiences. The continuous evolution of software capabilities, including AI-driven analytics and machine learning algorithms, has significantly enhanced the accuracy and predictive power of network assessments, making software a cornerstone of m

Retail Crowdsourcing Platform Market Outlook

According to our latest research, the global Retail Crowdsourcing Platform market size reached USD 1.74 billion in 2024, registering a robust year-on-year growth. The market is anticipated to expand at a CAGR of 17.8% from 2025 to 2033, with forecasts indicating a value of USD 7.19 billion by 2033. This remarkable growth trajectory is primarily driven by the increasing adoption of digital transformation initiatives among retailers, the rising need for real-time customer insights, and the growing importance of agile product development cycles. As the retail sector continues to evolve in response to changing consumer preferences and technological advancements, the demand for advanced crowdsourcing platforms is expected to accelerate, reshaping the competitive landscape and driving innovation across the industry.

One of the primary growth factors propelling the Retail Crowdsourcing Platform market is the mounting pressure on retailers and brands to innovate rapidly and respond to dynamic consumer preferences. In todayÂ’s fast-paced digital economy, retailers are leveraging crowdsourcing platforms to tap into a diverse pool of global talent and consumer insights, enabling them to co-create new products, improve merchandising strategies, and enhance marketing campaigns. These platforms facilitate the collection of real-time feedback, ideas, and solutions from a wide array of participants, significantly reducing the time and cost associated with traditional research and development processes. As a result, retailers can quickly adapt to market trends and deliver products and experiences that resonate with their target audiences, thereby gaining a competitive edge.

Another significant driver is the proliferation of cloud-based solutions and the integration of artificial intelligence (AI) and machine learning (ML) technologies in crowdsourcing platforms. Cloud deployment not only offers scalability and flexibility but also ensures seamless collaboration among geographically dispersed teams and contributors. AI-powered analytics further enhance the value proposition by providing actionable insights from large volumes of crowdsourced data, enabling retailers to make data-driven decisions with greater accuracy and speed. The convergence of these technologies is fostering a new era of digital transformation in retail, where crowdsourcing is not just a tool for ideation but a strategic enabler of customer-centric innovation and operational efficiency.

The surge in omnichannel retailing and the growing emphasis on personalized customer experiences are also fueling the adoption of crowdsourcing platforms. Retailers are increasingly seeking ways to engage customers at various touchpoints, gather feedback, and co-create personalized offerings. Crowdsourcing platforms serve as a bridge between retailers and consumers, facilitating two-way communication and fostering brand loyalty. Additionally, the rise of social media and mobile technologies has made it easier for retailers to crowdsource ideas and feedback from a global audience, further expanding the reach and impact of these platforms. This trend is expected to intensify in the coming years, as retailers continue to prioritize customer engagement and experience as key differentiators.

From a regional perspective, North America currently dominates the Retail Crowdsourcing Platform market, owing to the presence of major retail chains, advanced technological infrastructure, and a high degree of digital adoption. However, the Asia Pacific region is poised for the fastest growth, driven by the rapid expansion of the retail sector, increasing internet penetration, and a burgeoning middle-class population. Europe is also witnessing steady growth, supported by strong regulatory frameworks and a focus on sustainability and innovation. Latin America and the Middle East & Africa are emerging markets with significant potential, as retailers in these regions increasingly embrace digital transformation to stay competitive in a rapidly evolving landscape.

The emergence of the Robot Skill Crowdsourcing Platform is transforming the way retailers approach automation and robotics in their operations. By leveraging crowdsourcing, these platforms enable retailers to access a vast pool of expertise and skills from around

How would AI define neighborhood boundaries? A comparison with human-crowdsourced data

This data accompanies the study "Crowdsourcing Bridge Dynamic Monitoring with Smartphone Vehicle Trips" published in (Nature) Communications Engineering. This paper focuses on using large and inexpsensive datasets for obtaining information on the dynamics of bridges. In this study, data is collected by smartphones in moving vehicles as the cross over a bridge, in three distinct applications. Smartphone data was collected in controlled field experiments and uncontrolled Uber rides on a long-span suspension bridge in the USA (The Golden Gate Bridge) and an analytical method was developed to accurately recover modal properties. The method was also successfully applied to partially-controlled crowdsourced data collected on a short-span highway bridge in Italy. The results suggest that larve and inexpensive datasets collected by smartphones could play a role in monitoring the health of existing transportation infrastructure.

The data provided includes the source data for the figures in the publication as well as the "controlled data" referenced in the study.

Drive Test Data Crowdsourcing Market Outlook

According to our latest research, the Global Drive Test Data Crowdsourcing market size was valued at $1.2 billion in 2024 and is projected to reach $4.3 billion by 2033, expanding at a robust CAGR of 15.2% during the forecast period of 2025–2033. One major factor propelling the growth of the drive test data crowdsourcing market globally is the rapid proliferation of mobile devices and the exponential surge in mobile data traffic, which is compelling telecom operators and network equipment manufacturers to adopt more scalable, cost-effective, and real-time solutions for network optimization and quality assurance. The increasing complexity of heterogeneous network environments and the growing demand for seamless connectivity are further pushing stakeholders to leverage drive test data crowdsourcing as a strategic tool to gain actionable insights into network performance, thereby enabling more efficient network planning and optimization initiatives.

Regional Outlook

North America currently holds the largest share of the global drive test data crowdsourcing market, accounting for over 38% of the total market value in 2024. This dominance is attributed to the region’s mature telecommunications infrastructure, early adoption of advanced mobile technologies such as 5G, and the presence of leading telecom operators and network equipment manufacturers. The regulatory environment in North America is also highly conducive, with strong policy support for digital transformation and spectrum management. Furthermore, the region’s high smartphone penetration and the proliferation of IoT devices have created a rich ecosystem for collecting and leveraging crowdsourced drive test data. These factors, combined with aggressive investments in network modernization and the integration of AI-driven analytics, have solidified North America’s leadership in this market segment.

The Asia Pacific region is emerging as the fastest-growing market for drive test data crowdsourcing, projected to register a remarkable CAGR of 18.7% from 2025 to 2033. This growth is primarily driven by the rapid expansion of mobile networks in densely populated countries such as China and India, coupled with the accelerated rollout of 4G and 5G infrastructure. Governments across the region are actively supporting digital initiatives and smart city projects, which are further boosting the demand for real-time network performance monitoring and optimization solutions. Additionally, the region’s burgeoning base of smartphone users and connected vehicles is generating vast volumes of data, providing telecom operators with unprecedented opportunities to enhance coverage, reduce operational costs, and improve service quality through crowdsourcing models.

In emerging economies such as Latin America, the Middle East, and Africa, the adoption of drive test data crowdsourcing is gaining momentum, albeit at a more measured pace. These regions face unique challenges, including limited network infrastructure, regulatory uncertainties, and varying levels of digital literacy. However, the growing demand for reliable mobile connectivity and the increasing penetration of affordable smartphones are gradually bridging the digital divide. Localized demand for network optimization is also being fueled by government-led initiatives aimed at expanding rural and underserved areas. While policy frameworks are still evolving, there is a clear trend towards embracing innovative, cost-efficient solutions like crowdsourced drive test data to accelerate network expansion and improve quality of service in these markets.

Report Scope

This dataset is published by the Geophysical Research Letters (https://doi.org/10.1029/2024GL112853). The CSV file contains precipitation phase observations (i.e., rain, snow, and mix) and other related meteorological variables (e.g., temperature) from the Mountain Rain or Snow citizen science project. There are 37,338 MRoS observations (i.e., rows) from January 2020 to July 2023 across the conterminous United States.

Crowdsourcing has gained considerable traction over the past decade and has emerged as a powerful tool in the innovation process of organizations. Given its growing significance in practice, a profound understanding of the concept is crucial. The goal of this study is to develop a comprehensive understanding of designing crowdsourcing projects for innovation by identifying and analyzing critical design elements of crowdsourcing contests. Through synthesizing the principles of the social exchange theory and absorptive capacity, this study provides a novel conceptual configuration that accounts for both the attraction of solvers and the ability of the crowdsourcer to capture value from crowdsourcing contests. Therefore, this paper adopts a morphological approach to structure the four dimensions, namely, (i) task, (ii) crowd, (iii) platform and (iv) crowdsourcer, into a conceptual framework to present an integrated overview of the various crowdsourcing design options. The morphological analysis allows the possibility of identifying relevant interdependencies between design elements, based on the goals of the problem to be crowdsourced. In doing so, the paper aims to enrich the extant literature by providing a comprehensive overview of crowdsourcing and to serve as a blueprint for practitioners to make more informed decisions when designing and executing crowdsourcing projects.

Video Evidence Crowdsourcing Platforms Market Outlook

According to our latest research, the Global Video Evidence Crowdsourcing Platforms market size was valued at $1.24 billion in 2024 and is projected to reach $4.68 billion by 2033, expanding at a robust CAGR of 15.8% during the forecast period of 2025–2033. The primary factor fueling this remarkable growth is the increasing reliance of law enforcement and public safety agencies on real-time, community-driven video evidence to accelerate investigations, enhance situational awareness, and improve overall response efficiency. The proliferation of smartphones, ubiquitous internet connectivity, and the rising societal emphasis on transparency and accountability are further accelerating the adoption of video evidence crowdsourcing platforms globally.

Regional Outlook

North America currently commands the largest share of the Video Evidence Crowdsourcing Platforms market, accounting for approximately 38% of the global revenue in 2024. This dominance is attributed to the region’s mature digital infrastructure, high penetration of smartphones, and proactive adoption of advanced law enforcement technologies. The United States, in particular, has witnessed substantial investment from both government and private sectors in developing and deploying sophisticated crowdsourcing platforms for public safety and criminal investigations. Stringent regulatory frameworks supporting digital evidence collection, combined with a strong culture of civic engagement, have further entrenched these platforms as essential tools for agencies and organizations. Moreover, leading platform providers are headquartered in North America, contributing to a robust ecosystem of innovation and deployment.

The Asia Pacific region is projected to be the fastest-growing market, with an anticipated CAGR exceeding 18.5% from 2025 to 2033. Rapid urbanization, increasing incidence of natural disasters, and growing concerns regarding public security are driving demand for scalable, cloud-based video evidence crowdsourcing solutions. Countries such as China, India, and Japan are investing heavily in smart city initiatives, which encompass the integration of crowdsourced video data for urban management and emergency response. Government incentives, coupled with a burgeoning tech-savvy population, are fostering an environment ripe for adoption. Additionally, the proliferation of affordable smartphones and high-speed internet is enabling greater citizen participation, making the Asia Pacific a focal point for platform providers seeking global expansion.

Emerging economies in Latin America, the Middle East, and Africa are gradually embracing video evidence crowdsourcing platforms, although adoption is hindered by infrastructural limitations and varying levels of digital literacy. In these regions, localized demand is primarily driven by the need to improve disaster response and public safety in densely populated urban centers. However, challenges such as inconsistent regulatory frameworks, data privacy concerns, and limited funding for technology upgrades persist. Despite these hurdles, international aid agencies and NGOs are increasingly collaborating with local governments to pilot crowdsourcing initiatives, particularly in disaster-prone or high-crime areas. These efforts are expected to pave the way for broader market penetration as digital infrastructure matures and policy support strengthens.

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Road Condition Crowdsourcing App Market Outlook

According to our latest research, the global Road Condition Crowdsourcing App market size reached USD 1.21 billion in 2024, reflecting robust momentum driven by increasing urbanization and the growing adoption of smart mobility solutions. The market is set to expand at a CAGR of 18.7% from 2025 to 2033, with the forecasted market size expected to reach USD 5.38 billion by 2033. This impressive growth trajectory is attributed to the growing emphasis on real-time data collection, the proliferation of smartphones, and the rising need for efficient road infrastructure management worldwide.

The primary driver fueling the growth of the Road Condition Crowdsourcing App market is the increasing demand for real-time, actionable road data to improve traffic management, enhance public safety, and optimize infrastructure maintenance. As cities become more congested and transportation networks more complex, the need for accurate, up-to-the-minute information becomes critical. Crowdsourcing apps leverage the collective input of users to provide granular insights into road hazards, potholes, accidents, and other conditions, enabling quicker response times from authorities and better decision-making by drivers. The integration of artificial intelligence and machine learning algorithms into these platforms further enhances data accuracy and predictive capabilities, making them indispensable tools for modern urban mobility ecosystems.

Another significant growth factor is the widespread penetration of smartphones and mobile internet connectivity, which has democratized access to road condition reporting. The proliferation of affordable Android and iOS devices, coupled with user-friendly app interfaces, has empowered millions of private users to contribute to and benefit from these platforms. This shift has not only increased the volume and diversity of data collected but has also fostered a sense of community engagement in road safety and maintenance. In addition, advancements in cloud-based infrastructure have facilitated seamless data aggregation and analysis, enabling real-time updates and scalable deployment across regions.

Government agencies and transportation authorities are increasingly recognizing the value of crowdsourced data in supplementing traditional road monitoring systems. Budget constraints and the logistical challenges of maintaining vast road networks have prompted public sector stakeholders to adopt innovative digital solutions. By collaborating with app developers and leveraging crowdsourced insights, governments can prioritize maintenance activities, allocate resources more efficiently, and enhance public safety initiatives. Furthermore, the integration of crowdsourcing apps with existing traffic management and navigation systems is driving interoperability and holistic urban mobility planning, further accelerating market growth.

In recent years, Crowdsourced Pothole Reporting Platforms have emerged as a crucial component in the realm of road condition monitoring. These platforms empower citizens to report potholes and other road surface irregularities directly from their smartphones, providing authorities with real-time data to prioritize repairs. By utilizing the collective input of the community, these platforms not only enhance road safety but also foster a sense of civic responsibility among users. The integration of geolocation and image capture features allows for precise identification and documentation of road issues, streamlining the maintenance workflow. As urban areas continue to expand, the role of these platforms in maintaining road infrastructure becomes increasingly vital, offering a cost-effective solution to traditional monitoring methods.

Regionally, North America and Europe are leading the adoption of Road Condition Crowdsourcing Apps, buoyed by advanced digital infrastructure, strong regulatory support, and a high degree of public awareness regarding road safety. The Asia Pacific region, however, is emerging as the fastest-growing market, propelled by rapid urbanization, increasing smartphone penetration, and government-led smart city initiatives. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as infrastructure investments and digital transformation efforts gather pace.

Road Hazard Crowdsourcing Platform Market Outlook

According to our latest research, the global road hazard crowdsourcing platform market size reached USD 1.32 billion in 2024, and is anticipated to grow at a robust CAGR of 13.8% during the forecast period, reaching USD 4.10 billion by 2033. This growth is primarily driven by the rising adoption of smart transportation solutions, increased smartphone penetration, and the growing need for real-time hazard identification to enhance road safety. As per the latest research, the market is witnessing significant momentum as urbanization and the proliferation of connected vehicles fuel the demand for advanced road safety and traffic management platforms globally.

One of the primary growth factors for the road hazard crowdsourcing platform market is the increasing demand for real-time data sharing and actionable insights among urban commuters, authorities, and transportation agencies. As cities experience rapid urbanization and vehicle density continues to rise, the frequency of road hazards such as potholes, debris, and sudden lane closures also increases. Crowdsourcing platforms leverage the collective intelligence of drivers and commuters to report hazards instantly, enabling swift responses from authorities and minimizing the risk of accidents. The integration of artificial intelligence and machine learning within these platforms further enhances the accuracy and relevance of reported incidents, making them invaluable tools for proactive road safety management. The push towards smart cities and digital infrastructure investments by governments worldwide further amplifies the adoption of these platforms.

Another significant factor propelling the growth of the road hazard crowdsourcing platform market is the widespread adoption of smartphones and mobile applications. With over 6 billion smartphone users globally in 2024, the ability to crowdsource data in real time has become more accessible than ever before. Mobile apps equipped with GPS, camera, and sensor integration allow users to report hazards with a single tap, including uploading images and precise location data. This democratization of hazard reporting not only empowers citizens but also creates a vast, continuously updated data pool for transportation authorities. The growing trend of integrating crowdsourced hazard data with navigation and mapping services, such as Google Maps and Waze, further enhances the relevance and utility of these platforms for daily commuters and logistics operators.

The evolving regulatory landscape and increased emphasis on public safety are also crucial to the market's expansion. Governments and transportation authorities are increasingly recognizing the value of crowdsourced data for infrastructure maintenance and long-term planning. By analyzing aggregated hazard reports, agencies can prioritize road repairs, allocate resources efficiently, and develop targeted safety campaigns. Furthermore, public-private partnerships are emerging, with technology companies collaborating with municipalities to deploy customized crowdsourcing solutions. These partnerships accelerate platform adoption and foster innovation in hazard detection and mitigation. As the market matures, enhanced data privacy measures and seamless integration with existing traffic management systems are expected to be key differentiators for leading vendors.

Regionally, North America leads the road hazard crowdsourcing platform market due to its advanced transportation infrastructure, high smartphone penetration, and early adoption of smart city initiatives. Europe follows closely, driven by stringent road safety regulations and government-backed digitalization projects. The Asia Pacific region is witnessing the fastest growth, propelled by rapid urbanization, infrastructure investments, and a burgeoning population of tech-savvy commuters. Latin America and the Middle East & Africa are also showing increasing interest, particularly in urban centers where traffic congestion and road safety are major concerns. The regional outlook remains positive, with all regions expected to contribute to the market's robust expansion through 2033.

Component Analysis

The component segment of the road hazard crowdsourcing platform market is primarily divided into software and services. Software forms the backbone of these platforms, encompassing user interfaces, data analytics engines, mobile applic

Recent years have shown the power of user-sourced information evidenced by the success of Wikipedia and its many emulators. Agencies on the other hand publish metadata on their data products, but have little opportunity to get structured feedback on that metadata (codebooks) from their users. Creating and augmenting metadata is a labour-intensive endeavor. Harnessing collective knowledge from actual data users can supplement officially generated metadata. As part of our Comprehensive Extensible Data Documentation and Access Repository (CED2AR) infrastructure, we demonstrate a prototype of crowdsourced metadata (codebooks), using DDI-C and supplemental XML.

Big Data and Society Abstract & Indexing - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Road Hazard Crowdsourcing Market Outlook

According to our latest research, the global road hazard crowdsourcing market size reached USD 1.92 billion in 2024, with a robust growth trajectory driven by the increasing adoption of real-time data solutions in transportation. The market is expected to expand at a CAGR of 13.4% from 2025 to 2033, reaching approximately USD 5.86 billion by 2033. The surge in demand for intelligent traffic management and public safety solutions, coupled with the proliferation of smartphones and connected vehicles, is fueling the market’s rapid expansion.

One of the primary growth factors propelling the road hazard crowdsourcing market is the widespread integration of mobile technology and GPS-enabled devices. As more individuals use smartphones and navigation apps, real-time sharing of road hazard information has become increasingly feasible and effective. The collective power of user-generated reports enables authorities and navigation platforms to identify hazards such as potholes, debris, accidents, and other obstructions more quickly than traditional methods. This democratization of hazard reporting not only empowers drivers to make safer decisions but also aids municipal agencies in prioritizing maintenance and emergency response, thereby enhancing overall road safety and operational efficiency.

Another significant driver is the growing emphasis on smart city initiatives and the digital transformation of transportation infrastructure. Governments and transportation authorities are investing heavily in intelligent traffic management systems that leverage crowdsourced data to optimize traffic flow, reduce congestion, and minimize accident risks. These initiatives are supported by advancements in cloud computing, artificial intelligence, and big data analytics, which collectively enable the aggregation and real-time analysis of vast amounts of hazard data. This technological synergy is fostering a more proactive approach to road safety, where potential risks can be predicted and mitigated before they escalate into major incidents.

Furthermore, the market is benefiting from increasing collaborations between public agencies, private organizations, and technology providers. Such partnerships are critical for the development and deployment of robust crowdsourcing platforms that integrate seamlessly with existing navigation and transportation management systems. By leveraging open data and APIs, these platforms can extend their reach and functionality, ensuring comprehensive coverage and timely hazard alerts. The growing awareness among end-users about the benefits of real-time hazard reporting, coupled with supportive regulatory frameworks, is expected to sustain the market’s momentum over the coming years.

Regionally, North America is leading the market, fueled by advanced transportation infrastructure, high smartphone penetration, and early adoption of crowdsourced navigation applications. Europe follows closely, driven by stringent road safety regulations and significant investments in smart mobility projects. The Asia Pacific region is poised for the fastest growth, supported by rapid urbanization, expanding digital ecosystems, and government-led smart city initiatives. Latin America and the Middle East & Africa are also witnessing steady progress, albeit at a slower pace, as infrastructure modernization and digital adoption continue to gain traction.

Component Analysis

The road hazard crowdsourcing market is segmented by component into platforms and services, each playing a pivotal role in the ecosystem’s development. Platforms form the backbone of the market, providing the digital infrastructure necessary for aggregating, analyzing, and disseminating hazard information. These platforms typically incorporate advanced features such as geolocation, real-time notifications, and user-friendly interfaces, enabling seamless participation from a broad user base. The increasing deployment of sophisticated platforms by both public and private entities i