This statistic presents the opinion of French Internet users on the collection and the use of their data when surfing online or purchasing on e-commerce websites in a survey from 2019. It appears that the majority of the respondents were rather concerned or a lot concerned about this.

The oceanographic time series data collected by U.S. Geological Survey scientists and collaborators are served in an online database at http://stellwagen.er.usgs.gov/index.html. These data were collected as part of research experiments investigating circulation and sediment transport in the coastal ocean. The experiments (projects, research programs) are typically one month to several years long and have been carried out since 1975. New experiments will be conducted, and the data from them will be added to the collection. As of 2016, all but one of the experiments were conducted in waters abutting the U.S. coast; the exception was conducted in the Adriatic Sea. Measurements acquired vary by site and experiment; they usually include current velocity, wave statistics, water temperature, salinity, pressure, turbidity, and light transmission from one or more depths over a time period. The measurements are concentrated near the sea floor but may also include data from the water column. The user interface provides an interactive map, a tabular summary of the experiments, and a separate page for each experiment. Each experiment page has documentation and maps that provide details of what data were collected at each site. Links to related publications with additional information about the research are also provided. The data are stored in Network Common Data Format (netCDF) files using the Equatorial Pacific Information Collection (EPIC) conventions defined by the National Oceanic and Atmospheric Administration (NOAA) Pacific Marine Environmental Laboratory. NetCDF is a general, self-documenting, machine-independent, open source data format created and supported by the University Corporation for Atmospheric Research (UCAR). EPIC is an early set of standards designed to allow researchers from different organizations to share oceanographic data. The files may be downloaded or accessed online using the Open-source Project for a Network Data Access Protocol (OPeNDAP). The OPeNDAP framework allows users to access data from anywhere on the Internet using a variety of Web services including Thematic Realtime Environmental Distributed Data Services (THREDDS). A subset of the data compliant with the Climate and Forecast convention (CF, currently version 1.6) is also available.

The online survey site market is experiencing robust growth, driven by the increasing demand for market research data and the rising adoption of digital technologies. The market's expansion is fueled by several factors, including the growing preference for online surveys among businesses for their cost-effectiveness and speed of data collection, compared to traditional methods. The proliferation of smartphones and internet access globally further expands the pool of potential respondents, leading to larger and more diverse datasets. Segmentation within the market reveals a significant contribution from both SMEs leveraging online surveys for affordable feedback and large enterprises utilizing them for comprehensive market analysis. The "paid" segment dominates the market due to the incentive-driven participation of respondents, while the "free" segment offers a leaner, though often less engaged, participation approach. We can estimate a 2025 market size of approximately $5 billion, based on observable growth trends in related sectors and considering the substantial existing player base. A Compound Annual Growth Rate (CAGR) of 15% over the forecast period (2025-2033) suggests a significant market expansion, driven by technological advancements and the evolving needs of the market research industry. However, challenges remain, including concerns around data privacy, survey fatigue among respondents, and the potential for biased or inaccurate results if not carefully designed and administered. The competitive landscape is highly fragmented, with numerous players offering various survey platforms and incentives. Established platforms like Swagbucks and Survey Junkie benefit from strong brand recognition and user bases. Newer entrants continuously emerge, often focusing on niche markets or innovative survey formats to gain market share. Regional variations exist, with North America and Europe currently holding the largest market shares due to higher internet penetration and established market research practices. However, rapidly increasing internet adoption in Asia-Pacific and other developing regions presents significant growth opportunities in the coming years. The ongoing need for reliable market intelligence across all sectors, coupled with technological advancements leading to more sophisticated survey methodologies and data analysis, will continue to drive the growth trajectory of the online survey site market. Maintaining data privacy and security, alongside fostering respondent trust, will be crucial for sustained growth and the long-term success of companies in this sector.

1. Environmental volunteering can benefit participants and nature through improving physical and mental wellbeing while encouraging environmental stewardship. To enhance achievement of these outcomes, conservation organisations need to reach different groups of people to increase participation in environmental volunteering. This paper explores what engages communities searching online for environmental volunteering.
   

2. We conducted a literature review of 1032 papers to determine key factors fostering participation by existing volunteers in environmental projects. We found the most important factor was to tailor projects to the motivations of participants. Also important were: promoting projects to people with relevant interests; meeting the perceived benefits of volunteers and removing barriers to participation.
   

3. We then assessed the composition and factors fostering participation of the NatureVolunteers’s online community (n = 2216) of potential environmental volunteers and compared findings with those from the literature review. We asked whether projects advertised by conservation organisations meet motivations and interests of this online community.
   

4. Using Facebook insights and Google Analytics we found that the online community were on average younger than extant communities observed in studies of environmental volunteering. Their motivations were also different as they were more interested in physical activity and using skills and less in social factors. They also exhibited preference for projects which are outdoor based, and which offer close contact with wildlife. Finally, we found that the online community showed a stronger preference for habitat improvement projects over those involving species-survey based citizen science.
   

5. Our results demonstrate mis-matches between what our online community are looking for and what is advertised by conservation organisations. The online community are looking for projects which are more solitary, more physically active and more accessible by organised transport. We discuss how our results may be used by conservation organisations to better engage with more people searching for environmental volunteering opportunities online.
   

6. We conclude that there is a pool of young people attracted to environmental volunteering projects whose interests are different to those of current volunteers. If conservation organisations can develop projects that meet these interests, they can engage larger and more diverse communities in nature volunteering.
   

Methods The data set consists of separate sheets for each set of results presented in the paper. Each sheet contains the full data, summary descriptive statistics analysis and graphs presented in the paper. The method for collection and processing of the dataset in each sheet is as follows:

The data set for results presented in Figure 1 in the paper - Sheet: "Literature"

We conducted a review of literature on improving participation within nature conservation projects. This enabled us to determine what the most important factors were for participating in environmental projects, the composition of the populations sampled and the methods by which data were collected. The search terms used were (Environment* OR nature OR conservation) AND (Volunteer* OR “citizen science”) AND (Recruit* OR participat* OR retain* OR interest*). We reviewed all articles identified in the Web of Science database and the first 50 articles sorted for relevance in Google Scholar on the 22nd October 2019. Articles were first reviewed by title, secondly by abstract and thirdly by full text. They were retained or excluded according to criteria agreed by the authors of this paper. These criteria were as follows - that the paper topic was volunteering in the environment, including citizen science, community-based projects and conservation abroad, and included the study of factors which could improve participation in projects. Papers were excluded for topics irrelevant to this study, the most frequent being the outcomes of volunteering for participants (such as behavioural change and knowledge gain), improving citizen science data and the usefulness of citizen science data. The remaining final set of selected papers was then read to extract information on the factors influencing participation, the population sampled and the data collection methods. In total 1032 papers were reviewed of which 31 comprised the final selected set read in full. Four factors were identified in these papers which improve volunteer recruitment and retention. These were: tailoring projects to the motivations of participants, promoting projects to people with relevant hobbies and interests, meeting the perceived benefits of volunteers and removing barriers to participation.

The data set for results presented in Figure 2 and Figure 3 in the paper - Sheet "Demographics"

To determine if the motivations and interests expressed by volunteers in literature were representative of wider society, NatureVolunteers was exhibited at three UK public engagement events during May and June 2019; Hullabaloo Festival (Isle of Wight), The Great Wildlife Exploration (Bournemouth) and Festival of Nature (Bristol). This allowed us to engage with people who may not have ordinarily considered volunteering and encourage people to use the website. A combination of surveys and semi-structured interviews were used to collect information from the public regarding demographics and volunteering. In line with our ethics approval, no personal data were collected that could identify individuals and all participants gave informed consent for their anonymous information to be used for research purposes. The semi-structured interviews consisted of conducting the survey in a conversation with the respondent, rather than the respondent filling in the questionnaire privately and responses were recorded immediately by the interviewer. Hullabaloo Festival was a free discovery and exploration event where NatureVolunteers had a small display and surveys available. The Great Wildlife Exploration was a Bioblitz designed to highlight the importance of urban greenspaces where we had a stall with wildlife crafts promoting NatureVolunteers. The Festival of Nature was the UK’s largest nature-based festival in 2019 where we again had wildlife crafts available promoting NatureVolunteers. The surveys conducted at these events sampled a population of people who already expressed an interest in nature and the environment by attending the events and visiting the NatureVolunteers stand. In total 100 completed surveys were received from the events NatureVolunteers exhibited at; 21 from Hullabaloo Festival, 25 from the Great Wildlife Exploration and 54 from the Festival of Nature. At Hullabaloo Festival information on gender was not recorded for all responses and was consequently entered as “unrecorded”.

OVERALL DESCRIPTION OF METHOD DATA COLLECTION FOR ALL OTHER RESULTS (Figures 4-7 and Tables 1-2)

The remaining data were all collected from the NatureVolunteers website. The NatureVolunteers website https://www.naturevolunteers.uk/ was set up in 2018 with funding support from the Higher Education Innovation Fund to expand the range of people accessing nature volunteering opportunities in the UK. It is designed to particularly appeal to people who are new to nature volunteering including young adults wishing to expand their horizons, families looking for ways connect with nature to enhance well-being and older people wishing to share their time and life experiences to help nature. In addition, it was designed to be helpful to professionals working in the countryside & wildlife conservation sectors who wish to enhance their skills through volunteering. As part of the website’s development we created and used an online project database, www.naturevolunteers.uk (hereafter referred to as NatureVolunteers), to assess the needs and interests of our online community. Our research work was granted ethical approval by the Bournemouth University Ethics Committee. The website collects entirely anonymous data on our online community of website users that enables us to evaluate what sort of projects and project attributes most appeal to our online community. Visitors using the website to find projects are informed as part of the guidance on using the search function that this fully anonymous information is collected by the website to enhance and share research understanding of how conservation organisations can tailor their future projects to better match the interests of potential volunteers. Our online community was built up over the 2018-2019 through open advertising of the website nationally through the social media channels of our partner conservation organisations, through a range of public engagement in science events and nature-based festivals across southern England and through our extended network of friends and families, their own social media networks and the NatureVolunteers website’s own social network on Facebook and Twitter. There were 2216 searches for projects on NatureVolunteers from January 1st to October 25th, 2019.

The data set for results presented in Figure 2 and Figure 3 in the paper - Sheet "Demographics"

On the website, users searching for projects were firstly asked to specify their expectations of projects. These expectations encompass the benefits of volunteering by asking whether the project includes social interaction, whether particular skills are required or can be developed, and whether physical activity is involved. The barriers to participation are incorporated by asking whether the project is suitable for families, and whether organised transport is provided. Users were asked to rate the importance of the five project expectations on a Likert scale of 1 to 5 (Not at all = 1, Not really = 2, Neutral = 3, It

The goal of this study is to measure willingness to participate in passive mobile data collection among German smartphone owners. The data come from a two-wave web survey among German smartphone users 18 years and older who were recruited from a German nonprobability online panel. In December 2016, 2,623 participants completed the Wave 1 questionnaire on smartphone use and skills, privacy and security concerns, and general attitudes towards survey research and research institutions. In January 2017, all respondents from Wave 1 were invited to participate in a second web survey which included vignettes that varied the levels of several dimensions of a hypothetical study using passive mobile data collection, and respondents were asked to rate their willingness to participate in such a study. A total of 1,957 respondents completed the Wave 2 questionnaire.

Wave 1

Topics: Ownership of smartphone, mobile phone, PC, tablet, and/or e-book reader; type of smartphone; frequency of smartphone use; smartphone activities (browsing, e-mails, taking photos, view/ post social media content, shopping, online banking, installing apps, using GPS-enabled apps, connecting via Bluethooth, play games, stream music/ videos); self-assessment of smartphone skills; attitude towards surveys and participaton at research studies (personal interest, waste of time, sales pitch, interesting experience, useful); trust in institutions regarding data privacy (market research companies, university researchers, statistical office, mobile service provider, app companies, credit card companies, online retailer, and social networks); concerns regarding the disclosure of personal data by the aforementioned institutions; general privacy concern; privacy violated by banks/ credit card companies, tax authorities, government agencies, market research companies, social networks, apps, internet browsers); concern regarding data security with smartphone activities for research (online survey, survey apps, research apps, SMS survey, camera, activity data, GPS location, Bluetooth); number of online surveys in which the respondent has participated in the last 30 days; Panel memberships other than that of mingle; previous participation in a study with downloading a research app to the smartphone (passive mobile data collection).

Wave 2

Topics: Willingness to participate in passive mobile data collection (using eight vignettes with different scenarios that varied the levels of several dimensions of a hypothetical study using passive mobile data collection. The research app collects the following data for research purposes: technical characteristics of the smartphone (e.g. phone brand, screen size), the currently used telephone network (e.g. signal strength), the current location (every 5 minutes), which apps are used and which websites are visited, number of incoming and outgoing calls and SMS messages on the smartphone); reason why the respondent wouldn´t (respectively would) participate in the research study used in the first scenario (open answer); recognition of differences between the eight scenarios; kind of recognized difference (open answer); remembered data the research app collects (recall); previous invitation for research app download; research app download.

Demography: sex; age; federal state; highest level of school education; highest level of vocational qualification.

Additionally coded was: running number; respondent ID; duration (response time in seconds); device type used to fill out the questionnaire; vignette text; vignette intro time; vignette time.

TagX Web Browsing Clickstream Data: Unveiling Digital Behavior Across North America and EU Unique Insights into Online User Behavior TagX Web Browsing clickstream Data offers an unparalleled window into the digital lives of 1 million users across North America and the European Union. This comprehensive dataset stands out in the market due to its breadth, depth, and stringent compliance with data protection regulations. What Makes Our Data Unique?

Extensive Geographic Coverage: Spanning two major markets, our data provides a holistic view of web browsing patterns in developed economies. Large User Base: With 300K active users, our dataset offers statistically significant insights across various demographics and user segments. GDPR and CCPA Compliance: We prioritize user privacy and data protection, ensuring that our data collection and processing methods adhere to the strictest regulatory standards. Real-time Updates: Our clickstream data is continuously refreshed, providing up-to-the-minute insights into evolving online trends and user behaviors. Granular Data Points: We capture a wide array of metrics, including time spent on websites, click patterns, search queries, and user journey flows.

Data Sourcing: Ethical and Transparent Our web browsing clickstream data is sourced through a network of partnered websites and applications. Users explicitly opt-in to data collection, ensuring transparency and consent. We employ advanced anonymization techniques to protect individual privacy while maintaining the integrity and value of the aggregated data. Key aspects of our data sourcing process include:

Voluntary user participation through clear opt-in mechanisms Regular audits of data collection methods to ensure ongoing compliance Collaboration with privacy experts to implement best practices in data anonymization Continuous monitoring of regulatory landscapes to adapt our processes as needed

Primary Use Cases and Verticals TagX Web Browsing clickstream Data serves a multitude of industries and use cases, including but not limited to:

Digital Marketing and Advertising:

Audience segmentation and targeting Campaign performance optimization Competitor analysis and benchmarking

E-commerce and Retail:

Customer journey mapping Product recommendation enhancements Cart abandonment analysis

Media and Entertainment:

Content consumption trends Audience engagement metrics Cross-platform user behavior analysis

Financial Services:

Risk assessment based on online behavior Fraud detection through anomaly identification Investment trend analysis

Technology and Software:

User experience optimization Feature adoption tracking Competitive intelligence

Market Research and Consulting:

Consumer behavior studies Industry trend analysis Digital transformation strategies

Integration with Broader Data Offering TagX Web Browsing clickstream Data is a cornerstone of our comprehensive digital intelligence suite. It seamlessly integrates with our other data products to provide a 360-degree view of online user behavior:

Social Media Engagement Data: Combine clickstream insights with social media interactions for a holistic understanding of digital footprints. Mobile App Usage Data: Cross-reference web browsing patterns with mobile app usage to map the complete digital journey. Purchase Intent Signals: Enrich clickstream data with purchase intent indicators to power predictive analytics and targeted marketing efforts. Demographic Overlays: Enhance web browsing data with demographic information for more precise audience segmentation and targeting.

By leveraging these complementary datasets, businesses can unlock deeper insights and drive more impactful strategies across their digital initiatives. Data Quality and Scale We pride ourselves on delivering high-quality, reliable data at scale:

Rigorous Data Cleaning: Advanced algorithms filter out bot traffic, VPNs, and other non-human interactions. Regular Quality Checks: Our data science team conducts ongoing audits to ensure data accuracy and consistency. Scalable Infrastructure: Our robust data processing pipeline can handle billions of daily events, ensuring comprehensive coverage. Historical Data Availability: Access up to 24 months of historical data for trend analysis and longitudinal studies. Customizable Data Feeds: Tailor the data delivery to your specific needs, from raw clickstream events to aggregated insights.

Empowering Data-Driven Decision Making In today's digital-first world, understanding online user behavior is crucial for businesses across all sectors. TagX Web Browsing clickstream Data empowers organizations to make informed decisions, optimize their digital strategies, and stay ahead of the competition. Whether you're a marketer looking to refine your targeting, a product manager seeking to enhance user experience, or a researcher exploring digital trends, our cli...

Abstract copyright UK Data Service and data collection copyright owner.

The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).

Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules.

The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain.

From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers.

In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access.

From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable.

The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.

Secure Access Opinions and Lifestyle Survey data

Other Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details.

Cookie and Website Tracker Scanning Software Market Outlook

The global cookie and website tracker scanning software market is poised for significant growth, with its market size valued at approximately $1.5 billion in 2023 and projected to reach around $4.2 billion by 2032, reflecting a compound annual growth rate (CAGR) of approximately 12.5%. This market's expansion is largely driven by the increasing emphasis on data privacy regulations and compliance, which necessitates businesses to implement robust solutions for monitoring and managing cookies and website trackers. The growing digitalization across various sectors and the rising consumer awareness regarding data privacy are also contributing significantly to the market's upward trajectory.

One of the primary growth factors propelling the cookie and website tracker scanning software market is the proliferation of stringent data privacy regulations worldwide. Laws such as the General Data Protection Regulation (GDPR) in Europe, the California Consumer Privacy Act (CCPA) in the United States, and other similar legislation globally mandate businesses to enhance their data protection measures. These regulations require organizations to provide transparency regarding data collection practices and ensure that users have control over their personal information. As a result, companies are increasingly adopting cookie and tracker scanning solutions to comply with these legal requirements and avoid potential penalties and reputational damage, thus driving market growth.

Another significant factor contributing to the market's expansion is the escalating awareness and concern among consumers regarding their online privacy. In an era where digital interactions are part and parcel of daily life, consumers are becoming more vigilant about how their data is collected, stored, and utilized by websites. This heightened awareness compels businesses to adopt ethical data practices and implement technologies that offer consumers clear insights into cookie usage and tracking activities. Consequently, organizations are integrating cookie and website tracker scanning software into their operations to enhance user trust and ensure transparency, thereby fostering market growth.

The rapid advancement of technology, leading to increased digitalization, is also a key driver for this market. As businesses across various industries embrace digital transformation, the online ecosystem becomes more complex with an influx of data tracking methods. This complexity necessitates the use of sophisticated tools to monitor, analyze, and manage website trackers effectively. The integration of advanced analytics and AI capabilities into scanning software enables organizations to gain deeper insights into user behavior while ensuring compliance with privacy regulations. This technological evolution is anticipated to further fuel the market's growth over the forecast period.

As the digital landscape continues to evolve, the role of a Consent Management Platform (CMP) becomes increasingly crucial in the realm of data privacy. A CMP serves as a centralized solution for managing user consent across various digital platforms, ensuring that businesses comply with data protection regulations such as GDPR and CCPA. By providing users with clear options to manage their consent preferences, these platforms enhance transparency and trust. Organizations are increasingly integrating CMPs into their operations to streamline consent management processes and reduce the risk of non-compliance. This integration not only helps in maintaining regulatory compliance but also strengthens the relationship between businesses and their users by respecting their privacy choices.

Regionally, North America holds a substantial share in the global cookie and website tracker scanning software market, owing to the early adoption of technology and stringent data privacy regulations in the region. The presence of major technology companies further fuels innovation and development in this market. Europe is also a significant market player, driven by the stringent GDPR regulations that necessitate robust compliance solutions. Meanwhile, the Asia Pacific region is expected to witness the fastest growth rate due to increasing internet penetration, digitalization initiatives, and growing awareness regarding data privacy. As economies in the region continue to develop, the demand for effective data protection solutions is likely to surge, contributing to the market's overall growth.

C

The motivation of this study is to create a dataset that allows researchers to explore the online visibility and activities of all mosques and their (online) followers in the Netherlands. Data were collected from personal websites, Facebook, Twitter, Instagram, and YouTube. The data collection took place between 15th September 2018 and 1st July 2019. During this period, we collected data on the online activity of mosques in the Netherlands as well as data on their online followers.

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As of the third quarter of 2024, more than 48 percent of online users in the United States declined cookies on websites sometimes. Furthermore, an earlier survey found that over four in 10 respondents were concerned about how companies might use their online data. About a quarter said they used a virtual private network (VPN) to access the internet at least some of the time.

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, domain-specific databases, and the top journals compare how much data is in institutional vs. domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

This data about nola.gov provides a window into how people are interacting with the the City of New Orleans online. The data comes from a unified Google Analytics account for New Orleans. We do not track individuals and we anonymize the IP addresses of all visitors.

The paid online survey market, encompassing platforms like Pawns.app, Freecash, and Swagbucks, is experiencing robust growth. While precise market size figures for 2025 are unavailable, a reasonable estimate, considering the presence of numerous established players and ongoing technological advancements, suggests a market value exceeding $1.5 billion. The Compound Annual Growth Rate (CAGR) is likely in the range of 8-10%, indicating a steadily expanding market driven by increased demand for market research data and consumer insights from businesses. Key drivers include the rising popularity of online surveys as a supplementary income stream for consumers, coupled with the growing sophistication of market research methodologies that leverage the reach and diversity of online panels. Trends show a shift towards mobile-first survey platforms, gamified reward systems, and an increasing focus on data privacy and security. Constraints include survey fatigue among participants, challenges in maintaining data quality, and the prevalence of fraudulent activities. Segmentation within the market is evident, with variations in pricing models, reward structures (cash, gift cards, points), and target demographics. The forecast period from 2025 to 2033 points towards sustained growth, driven by increasing internet penetration globally and enhanced technological capabilities allowing for more targeted and efficient data collection. The competitive landscape is characterized by a blend of large established companies and smaller niche players. While the listed companies represent a significant portion of the market, the presence of numerous smaller, regional operators adds complexity. Future growth will depend on companies' ability to adapt to evolving consumer preferences, enhance data security measures, and navigate the regulatory landscape surrounding data privacy. Expansion into emerging markets, particularly in regions with rapidly growing internet penetration, presents significant opportunities. The market's success hinges on continuous innovation in survey design, participant engagement, and data analytics to ensure the accuracy, reliability, and relevance of the data collected, thus maintaining value for both businesses and individual participants.

This dataset includes observations of trackers present on the top 500 pages popular among Finnish web users as per Alexa. The data collection was conducted using TrackerTracker in five separate requests for five subsets of 100 sites each between 19.8.2017 and 20.8.2017. The tool used a tracker database from March 24, 2017. More methodology details are described in the associated journal article https://doi.org/10.23978/inf.87841

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Web Analytics Market Size 2025-2029

The web analytics market size is forecast to increase by USD 3.63 billion, at a CAGR of 15.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the rising preference for online shopping and the increasing adoption of cloud-based solutions. The shift towards e-commerce is fueling the demand for advanced web analytics tools that enable businesses to gain insights into customer behavior and optimize their digital strategies. Furthermore, cloud deployment models offer flexibility, scalability, and cost savings, making them an attractive option for businesses of all sizes. However, the market also faces challenges associated with compliance to data privacy and regulations. With the increasing amount of data being generated and collected, ensuring data security and privacy is becoming a major concern for businesses.
Regulatory compliance, such as GDPR and CCPA, adds complexity to the implementation and management of web analytics solutions. Companies must navigate these challenges effectively to maintain customer trust and avoid potential legal issues. To capitalize on market opportunities and address these challenges, businesses should invest in robust web analytics solutions that prioritize data security and privacy while providing actionable insights to inform strategic decision-making and enhance customer experiences.

What will be the Size of the Web Analytics Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with dynamic market activities unfolding across various sectors. Entities such as reporting dashboards, schema markup, conversion optimization, session duration, organic traffic, attribution modeling, conversion rate optimization, call to action, content calendar, SEO audits, website performance optimization, link building, page load speed, user behavior tracking, and more, play integral roles in this ever-changing landscape. Data visualization tools like Google Analytics and Adobe Analytics provide valuable insights into user engagement metrics, helping businesses optimize their content strategy, website design, and technical SEO. Goal tracking and keyword research enable marketers to measure the return on investment of their efforts and refine their content marketing and social media marketing strategies.

Mobile optimization, form optimization, and landing page optimization are crucial aspects of website performance optimization, ensuring a seamless user experience across devices and improving customer acquisition cost. Search console and page speed insights offer valuable insights into website traffic analysis and help businesses address technical issues that may impact user behavior. Continuous optimization efforts, such as multivariate testing, data segmentation, and data filtering, allow businesses to fine-tune their customer journey mapping and cohort analysis. Search engine optimization, both on-page and off-page, remains a critical component of digital marketing, with backlink analysis and page authority playing key roles in improving domain authority and organic traffic.

The ongoing integration of user behavior tracking, click-through rate, and bounce rate into marketing strategies enables businesses to gain a deeper understanding of their audience and optimize their customer experience accordingly. As market dynamics continue to evolve, the integration of these tools and techniques into comprehensive digital marketing strategies will remain essential for businesses looking to stay competitive in the digital landscape.

How is this Web Analytics Industry segmented?

The web analytics industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Deployment

  Cloud-based
  On-premises


Application

  Social media management
  Targeting and behavioral analysis
  Display advertising optimization
  Multichannel campaign analysis
  Online marketing


Component

  Solutions
  Services


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

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By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period.

In today's digital landscape, web analytics plays a pivotal role in driving business growth and optimizing online performance. Cloud-based deployment of web analytics is a game-changer, enabling on-demand access to computing resources for data analysis. This model streamlines business intelligence processes by collecting,

Satisfaction, loyalty, and likelihood of referral are regarded by marketers and the Big Three diagnostics leading to retail profitability. However, as yet no-one has developed a model to capture all three of these constructs in the context of the internet. Moreover, although several attempts have been made to develop models to measure quality of website experience, no-one has sought to develop an instrument short enough to be of practical use as a quick customer satisfaction feedback form. In this research we sought to fill this void by developing and psychometrically testing a parsimonious model to capture the Big Three diagnostics, brief enough to be used in a commercial environment as a modal popup feedback form.

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The data represent web-scraping of hyperlinks from a selection of environmental stewardship organizations that were identified in the 2017 NYC Stewardship Mapping and Assessment Project (STEW-MAP) (USDA 2017). There are two data sets: 1) the original scrape containing all hyperlinks within the websites and associated attribute values (see "README" file); 2) a cleaned and reduced dataset formatted for network analysis. For dataset 1: Organizations were selected from from the 2017 NYC Stewardship Mapping and Assessment Project (STEW-MAP) (USDA 2017), a publicly available, spatial data set about environmental stewardship organizations working in New York City, USA (N = 719). To create a smaller and more manageable sample to analyze, all organizations that intersected (i.e., worked entirely within or overlapped) the NYC borough of Staten Island were selected for a geographically bounded sample. Only organizations with working websites and that the web scraper could access were retained for the study (n = 78). The websites were scraped between 09 and 17 June 2020 to a maximum search depth of ten using the snaWeb package (version 1.0.1, Stockton 2020) in the R computational language environment (R Core Team 2020). For dataset 2: The complete scrape results were cleaned, reduced, and formatted as a standard edge-array (node1, node2, edge attribute) for network analysis. See "READ ME" file for further details. References: R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Version 4.0.3. Stockton, T. (2020). snaWeb Package: An R package for finding and building social networks for a website, version 1.0.1. USDA Forest Service. (2017). Stewardship Mapping and Assessment Project (STEW-MAP). New York City Data Set. Available online at https://www.nrs.fs.fed.us/STEW-MAP/data/. This dataset is associated with the following publication: Sayles, J., R. Furey, and M. Ten Brink. How deep to dig: effects of web-scraping search depth on hyperlink network analysis of environmental stewardship organizations. Applied Network Science. Springer Nature, New York, NY, 7: 36, (2022).