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One Step Closer to Mars with Aquaponics: Cultivating Citizen Science in K12 Schools
The Microbial Ecology and Biogeochemistry Research Laboratory at NASA Ames Research Center focuses primarily on the nutrient cycling and diversity of complex microbial communities. NASA is interested in the composition and functioning of microbial mat communities as these processes fundamentally shape the form and function of these analogs for the earliest forms of life on Earth (3.6 billion years ago), and likely will on other planets as well. Aquaponics systems are supported by microbial communities who perform many complex ecosystem services, including cycling nitrogen. Microbes are integral to the stability and productivity of aquaponics systems, which are analogous to microbial communities in food production systems that are essential for building efficient life support systems for long-distance space travel. Students at Meadow Park Middle School created 10 parallel aquaponics systems and took temporal microbial samples to characterize whether any macro-ecology variables impacted or changed the microbial diversity of these systems. Students additionally created a website so that other classrooms can pursue similar projects in their own schools (https://go.nasa.gov/2uJhxmF). Our lab at NASA Ames has sequenced water samples from each of the 10 tanks at 3 timepoints using a MinION sequencer. MPMS students will be involved in the analysis of the bioinformatics data generated through this collaboration. Our ongoing collaboration aims to collect and analyze data in the classroom setting that has utility for research scientists, while involving students as collaborators in the research process.
Citizen Science as a Tool for Scientific Research and Societal Benefit at NASA
NASA's strategic goals include advancing knowledge and opportunity in space and improving life on Earth. We support these goals through extensive programs in space and Earth science research accomplished via space-based missions and research funding. NASA's "system" is configured to conduct science using (1) in-house personnel and (2) grants, contracts, and agreements with external entities (academia, industry, international space agencies.
Surveying Outreach and Citizen Science Opportunities for Planetary Defense
Planetary defense stands out among the various topics of space science as an endeavour which the general public can understand, for which they can readily appreciate the value, and in which they can find significant relevance to their own lives. This is well illustrated in the extensive coverage that the international general media continues to give to the IAA Planetary Defense Conferences and their hypothetical NEO/Earth impact event scenarios. However, frequent doomsday predictions and bad movie plots illustrate that this is also an area for misinformation, misconceptions, and misunderstanding. In an endeavour as high-profile and critical as planetary defense, a campaign of accurate and effective public outreach is essential. In this presentation, we will survey some of the existing programs and opportunities that are particularly applicable to planetary defense outreach. This is done to stimulate discussion about how to best leverage existing resources and how to use lessons learned in creating new resources.
Citizen Science Twitter Data Management for Earth Science Applications
Social media data can provide useful real-time and historical information relating to the natural world, but managing this data poses challenges. Scientists at GES DISC are exploring the potential of Twitter data to augment precipitation data from the Global Precipitation Measurement (GPM) mission. However, the format of Twitter data is unconventional in the context of NASA data centers, resulting in frustration for scientists who need to work with the data. This study investigated procedures and standards needed to properly manage Twitter data to make them compatible with these data centers. After comparing databases, the study found that the MongoDB database was best suited for the storage of raw Twitter data due to its flexibility, ability to be accessed by multiple users, and querying functionality. The study used the Python package Zarr to transform processed Twitter data into a gridded format similar to that of satellite data. Each Tweet was mapped onto a time-space grid; each grid location contained information about Tweet attributes and precipitation. The study developed a pipeline for downloading, storing, and gridding Twitter data and transformed Twitter data into an understandable format for users of NASA satellite data.
Colorado River Basin Water Resources: Pairing Citizen Science Observations with NASA Earth Observations to Monitor Riparian Vegetation
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Leveraging citizen science and artificial intelligence for monitoring and estimating hazardous events
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Activating the Untapped Potential in Ground Validation for Localized Air Quality Events Using the Citizen Science GLOBE Community
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NASA Langley's Past and Current Research on Solar Eclipses Using Citizen Science Data
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The potential of citizen science data to complement satellite and airborne lidar tree height measurements: lessons from The GLOBE Program
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Managing a large citizen science project to monitor wildlife
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Galaxy Zoo: Clump Scout – Design and first application of a two-dimensional aggregation tool for citizen science
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Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons
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TPSAS-NF1676L-31966-DND
Solar eclipses provide the scientific community with a natural experiment of the processes within the Earth system. Through the rapid reduction and recovery of surface insolation, the short-term interrelationships between surface fluxes, clouds, temperature, and other meteorological components. Past observations of the eclipse-induced temperature perturbation show a wide range of values dependent on multiple factors. One of the primary factors is prevailing cloud cover, which is challenging to quantify. The large public interest in the 21 August 2017 eclipse provided an opportunity for a study of the eclipse using citizen science. Inspired by past citizen science efforts, the GLOBE Observer (GO) program organized a citizen science campaign for the 2017 eclipse. The large number of observers combined with their ability to travel to meteorologically important areas provided nearly unbroken coverage of the path of totality, and provides a useful complementary view of the eclipse with the automated networks. Primary questions: 1) What is the quantitative relationship between prevailing cloud cover and eclipse-induced temperature perturbation according to citizen scientist observations? 2) How well do the results from the citizen scientist observations compare with those from conventional ground observing stations?
The FEWSION for Community Resilience (F4R) Process: Building Local Technical and Social Capacity for Critical Supply Chain Resilience
Local business leaders, policy makers, elected officials, city planners, emergency managers, and private citizens are responsible for, and deeply affected by, the performance of critical supply chains and related infrastructures. At the center of critical supply chains is the food-energy-water nexus (FEW); a nexus that is key to a community’s wellbeing, resilience, and sustainability. In the 21st century, managing a local FEW nexus requires accurate data describing the function and structure of a community’s supply chains. However, data is not enough; we need data-informed conversation and technical and social capacity building among local stakeholders to utilize the data effectively. There are some resources available at the mesoscale and for food, energy, or water, but many communities lack the data and tools needed to understand connections and bridge the gaps between these scales and systems. As a result, we currently lack the capacity to manage these systems in small and medium sized communities where the vast majority of people, decisions, and problems reside. This study develops and validates a participatory citizen science process for FEW nexus capacity building and data-driven problem solving in small communities at the grassroots level. The FEWSION for Community Resilience (F4R) process applies a Public Participation in Scientific Research (PPSR) framework to map supply chain data for a community’s FEW nexus, to identify the social network that manages the nexus, and then to generate a data-informed conversation among stakeholders. F4R was piloted and co-developed with participants over a 2-year study, using a design-based research process to make evidence-based adjustments as needed. Results show that the F4R model was successful at improving volunteers’ awareness about nexus and supply chain issues, at creating a network of connections and communication with stakeholders across state, regional, and local organizations, and in facilitating data-informed discussion about improvements to the system. In this paper we describe the design and implementation of F4R and discuss four recommendations for the successful application of the F4R model in other communities: 1) embed opportunities for co-created PPSR, 2) build social capital, 3) integrate active learning strategies with user-friendly digital tools, and 4) adopt existing materials and structure.
New Science in Plain Sight: Citizen Scientists Lead to the Discovery of Optical Structure in the Upper Atmosphere
A glowing ribbon of purple light running east-west in the night sky has recently been observed by citizen scientists. This narrow, subauroral, visible structure, distinct from the traditional auroral oval, was largely undocumented in the scientific literature and little was known about its formation. Amateur photo sequences showed colors distinctly different from common types of aurora and occasionally indicated magnetic field aligned substructures. Observations from the Swarm satellite as it crossed the arc have revealed an unusual level of electron temperature enhancement and density depletion, along with a strong westward ion flow, indicating that a pronounced subauroral ion drift (SAID) is associated with this structure. These early results suggest the arc is an optical manifestation of SAID, presenting new opportunities for investigation of the dynamic SAID signatures from the ground. On the basis of the measured ion properties and original citizen science name, we propose to identify this arc as a Strong Thermal Emission Velocity Enhancement (STEVE).
Galaxy and Mass Assembly: A Comparison between Galaxy–Galaxy Lens Searches in KiDS/GAMA
Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies—such as mixed spectroscopy of multiple galaxies along the line of sight, machine-learning algorithms, and citizen science—have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine-learning, and citizen-science identification of galaxy–galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the Galaxy and Mass Assembly survey. In these, we have the opportunity to compare high completeness spectroscopic identifications against high-fidelity imaging from the Kilo Degree Survey used for both machine-learning and citizen-science lens searches. We find that the three methods—spectroscopy, machine learning, and citizen science—identify 47, 47, and 13 candidates, respectively, in the 180 square degrees surveyed. These identifications barely overlap, with only two identified by both citizen science and machine learning. We have traced this discrepancy to inherent differences in the selection functions of each of the three methods, either within their parent samples (i.e., citizen science focuses on low redshift) or inherent to the method (i.e., machine learning is limited by its training sample and prefers well-separated features, while spectroscopy requires sufficient flux from lensed features to lie within the fiber). These differences manifest as separate samples in estimated Einstein radius, lens stellar mass, and lens redshift. The combined sample implies a lens candidate sky density of ∼0.59 deg{sup −2} and can inform the construction of a training set spanning a wider mass–redshift space. A combined approach and refinement of automated searches would result in a more complete sample of galaxy–galaxy lens candidates for future surveys.