A natural user interface to integrate citizen science and physical exercise.
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ABSTRACT:
SUBMITTER: Palermo E
PROVIDER: S-EPMC5322974 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMosquitoes and the diseases they transmit pose a significant public health threat worldwide, causing more fatalities than any other animal. To effectively combat this issue, there is a need for increased public awareness and mosquito control. However, traditional surveillance programs are time-consuming, expensive, and lack scalability. Fortunately, the widespread availability of mobile devices with high-resolution cameras presents a unique opportunity for mosquito surveillance. In response to this, the Global Mosquito Observations Dashboard (GMOD) was developed as a free, public platform to improve the detection and monitoring of invasive and vector mosquitoes through citizen science participation worldwide.MethodsGMOD is an interactive web interface that collects and displays mosquito observation and habitat data supplied by four datastreams with data generated by citizen scientists worldwide. By providing information on the locations and times of observations, the platform enables the visualization of mosquito population trends and ranges. It also serves as an educational resource, encouraging collaboration and data sharing. The data acquired and displayed on GMOD is freely available in multiple formats and can be accessed from any device with an internet connection.ResultsSince its launch less than a year ago, GMOD has already proven its value. It has successfully integrated and processed large volumes of real-time data (~ 300,000 observations), offering valuable and actionable insights into mosquito species prevalence, abundance, and potential distributions, as well as engaging citizens in community-based surveillance programs.ConclusionsGMOD is a cloud-based platform that provides open access to mosquito vector data obtained from citizen science programs. Its user-friendly interface and data filters make it valuable for researchers, mosquito control personnel, and other stakeholders. With its expanding data resources and the potential for machine learning integration, GMOD is poised to support public health initiatives aimed at reducing the spread of mosquito-borne diseases in a cost-effective manner, particularly in regions where traditional surveillance methods are limited. GMOD is continually evolving, with ongoing development of powerful artificial intelligence algorithms to identify mosquito species and other features from submitted data. The future of citizen science holds great promise, and GMOD stands as an exciting initiative in this field.
| S-EPMC10612222 | biostudies-literature
Project description:Over the years, the various mediums available for storytelling have progressively expanded, from spoken to written word, then to film, and now to Virtual Reality (VR) and Augmented Reality (AR). In 2016, the cutting-edge Head-Mounted Display (HMD) AR Microsoft HoloLens was released. However, though it has been several years, the quality of the user experience with narration using HMD-based AR technology has been rarely discussed. The present study explored interactive narrative in HMD-based AR regarding different user interfaces and their influence on users' presence, narrative engagement and reflection. Inspired by an existing exhibition at the National Holocaust Centre and Museum in the U.K., a HoloLens narrative application, entitled The AR Journey, was developed by the authors using two different interaction methods, Natural User Interface (NUI) and Graphical User Interface (GUI), which were used to perform an empirical study. As revealed from the results of the between-subject design experiment, NUI exhibited statistically significant advantages in creating presence for users without 3D Role Playing Game (RPG) experience, and GUI was superior in creating presence and increasing narrative engagement for users with 3D RPG experience. As indicated by the results of the interviews, the overall narrative experience in HMD-based AR was acceptable, and the branching narrative design was engaging. However, HoloLens hardware issues, as well as virtuality and reality mismatch, adversely affected user experience. Design guidelines were proposed according to the qualitative results.Supplementary informationThe online version contains supplementary material available at 10.1007/s11042-021-11723-0.
| S-EPMC8717307 | biostudies-literature
Project description:PurposeWhile technology is a major driver of many of society's comforts, conveniences, and advances, it has been responsible, in a significant way, for engineering regular physical activity and a number of other positive health behaviors out of people's daily lives. A key question concerns how to harness information and communication technologies (ICT) to bring about positive changes in the health promotion field. One such approach involves community-engaged "citizen science," in which local residents leverage the potential of ICT to foster data-driven consensus-building and mobilization efforts that advance physical activity at the individual, social, built environment, and policy levels.MethodThe history of citizen science in the research arena is briefly described and an evidence-based method that embeds citizen science in a multi-level, multi-sectoral community-based participatory research framework for physical activity promotion is presented.ResultsSeveral examples of this citizen science-driven community engagement framework for promoting active lifestyles, called "Our Voice", are discussed, including pilot projects from diverse communities in the U.S. as well as internationally.ConclusionsThe opportunities and challenges involved in leveraging citizen science activities as part of a broader population approach to promoting regular physical activity are explored. The strategic engagement of citizen scientists from socio-demographically diverse communities across the globe as both assessment as well as change agents provides a promising, potentially low-cost and scalable strategy for creating more active, healthful, and equitable neighborhoods and communities worldwide.
| S-EPMC4978140 | biostudies-literature
Project description:Assessing the value of a citizen science approach for ctenophore identification
| PRJEB48037 | ENA
Project description:Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.
| S-EPMC5972590 | biostudies-literature
Project description:Citizen science involves a range of practices involving public participation in scientific knowledge production, but outcomes evaluation is complicated by the diversity of the goals and forms of citizen science. Publications and citations are not adequate metrics to describe citizen-science productivity. We address this gap by contributing a science products inventory (SPI) tool, iteratively developed through an expert panel and case studies, intended to support general-purpose planning and evaluation of citizen-science projects with respect to science productivity. The SPI includes a collection of items for tracking the production of science outputs and data practices, which are described and illustrated with examples. Several opportunities for further development of the initial inventory are highlighted, as well as potential for using the inventory as a tool to guide project management, funding, and research on citizen science.
| S-EPMC5972569 | biostudies-literature
Project description:A citation study of a sample of earth science projects in citizen science from the FedCats Catalog was undertaken to assess whether citizen science projects are as productive and as impactful as conventional research that does not employ volunteer participation as a part of their data gathering and analysis protocols. From the 783 peer-reviewed papers produced by 48 projects identified from project bibliographies, 12,380 citations were identified using the Web of Science archive and their citation search engine to the end of 2018. Various conventional productivity and impact measures were applied including the Impact Factor, H and M-indices, and entry into the Top-1000 papers in cited research. The earth science projects tend to under-perform in terms of Impact Factor (IF = 14-20) and the M-index (M<0.5) but perform at the level of a 'tenured professor' with <H> = 23. When compared to non-citizen science research in general, there is a ten-fold higher probability of the earth science papers reaching the Top-1000 threshold of most-cited papers in natural science research. Some of the reasons for the lower performance by some indicators may have to do with the down-turn in published papers after 2010 for the majority of the earth science projects, which itself could be related to the fact that 52% of these projects only became operational after 2010 compared to the more successful 'Top-3' projects, whose impacts resemble the general population of non-citizen science research.
| S-EPMC7365449 | biostudies-literature
Project description:Biomedical literature represents one of the largest and fastest growing collections of unstructured biomedical knowledge. Finding critical information buried in the literature can be challenging. To extract information from free-flowing text, researchers need to: 1. identify the entities in the text (named entity recognition), 2. apply a standardized vocabulary to these entities (normalization), and 3. identify how entities in the text are related to one another (relationship extraction). Researchers have primarily approached these information extraction tasks through manual expert curation and computational methods. We have previously demonstrated that named entity recognition (NER) tasks can be crowdsourced to a group of non-experts via the paid microtask platform, Amazon Mechanical Turk (AMT), and can dramatically reduce the cost and increase the throughput of biocuration efforts. However, given the size of the biomedical literature, even information extraction via paid microtask platforms is not scalable. With our web-based application Mark2Cure (http://mark2cure.org), we demonstrate that NER tasks also can be performed by volunteer citizen scientists with high accuracy. We apply metrics from the Zooniverse Matrices of Citizen Science Success and provide the results here to serve as a basis of comparison for other citizen science projects. Further, we discuss design considerations, issues, and the application of analytics for successfully moving a crowdsourcing workflow from a paid microtask platform to a citizen science platform. To our knowledge, this study is the first application of citizen science to a natural language processing task.
| S-EPMC6226017 | biostudies-literature
Project description:Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature-for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes-short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from 'not citizen science' (0%) to 'citizen science' (100%). The survey included 50 vignettes, of which five were developed as clear cases of not-citizen science activities, five as widely accepted citizen science activities and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field.
| S-EPMC8385385 | biostudies-literature
Project description:This paper introduces a hybrid robotic swarm system architecture that combines virtual and physical components and enables human-swarm interaction through mixed reality (MR) devices. The system comprises three main modules: (1) the virtual module, which simulates robotic agents, (2) the physical module, consisting of real robotic agents, and (3) the user interface (UI) module. To facilitate communication between the modules, the UI module connects with the virtual module using Photon Network and with the physical module through the Robot Operating System (ROS) bridge. Additionally, the virtual and physical modules communicate via the ROS bridge. The virtual and physical agents form a hybrid swarm by integrating these three modules. The human-swarm interface based on MR technology enables one or multiple human users to interact with the swarm in various ways. Users can create and assign tasks, monitor real-time swarm status and activities, or control and interact with specific robotic agents. To validate the system-level integration and embedded swarm functions, two experimental demonstrations were conducted: (a) two users playing planner and observer roles, assigning five tasks for the swarm to allocate the tasks autonomously and execute them, and (b) a single user interacting with the hybrid swarm consisting of two physical agents and 170 virtual agents by creating and assigning a task list and then controlling one of the physical robots to complete a target identification mission.
| S-EPMC10485072 | biostudies-literature