Explore the vast range of titles available.

The Neotoma Paleoecology Database is a community-curated data resource that supports interdisciplinary global change research by enabling broad-scale studies of taxon and community diversity, distributions, and dynamics during the large environmental changes of the past. By consolidating many kinds of data into a common repository, Neotoma lowers costs of paleodata management, makes paleoecological data openly available, and offers a high-quality, curated resource. Neotoma’s distributed scientific governance model is flexible and scalable, with many open pathways for participation by new members, data contributors, stewards, and research communities. The Neotoma data model supports, or can be extended to support, any kind of paleoecological or paleoenvironmental data from sedimentary archives. Data additions to Neotoma are growing and now include >3.8 million observations, >17,000 datasets, and >9200 sites. Dataset types currently include fossil pollen, vertebrates, diatoms, ostracodes, macroinvertebrates, plant macrofossils, insects, testate amoebae, geochronological data, and the recently added organic biomarkers, stable isotopes, and specimen-level data. Multiple avenues exist to obtain Neotoma data, including the Explorer map-based interface, an application programming interface, the neotoma R package, and digital object identifiers. As the volume and variety of scientific data grow, community-curated data resources such as Neotoma have become foundational infrastructure for big data science.

Technology has transformed maps into interactive tools for exploring and understanding the world. In this article, we present the user experience (UX) design process for Flyover Country ( http://flyovercountry.io ), a mobile mapping application that visualizes information about the Earth's geology and history, allowing users to save and then access the information offline while flying, driving, or hiking. Specifically, the paper presents a UX design study that tracks the conceptualization, implementation, and revision of Flyover Country, and employs scenario-based design to walk through a pair of use case scenarios that informed our UX design: science outreach to the general public and field trip guides for geoscience education. In the paper, we note UX design insights that are potentially transferable to other mobile mapping contexts, organizing insights by mobile representation design (scale, projection, symbolization, and typography) versus mobile interaction design (map entry point, bottom navigation, floating action button, and pull-up information panel).

In this paper, we address the topic of user-centered design (UCD) for cartography, GIScience, and visual analytics. Interactive maps are ubiquitous in modern society, yet they often fail to “work” as they could or should. UCD describes the process of ensuring interface success—map-based or otherwise—by gathering input and feedback from target users throughout the design and development of the interface. We contribute to the expanding literature on UCD for interactive maps in two ways. First, we synthesize core concepts on UCD from cartography and related fields, as well as offer new ideas, in order to organize existing frameworks and recommendations regarding the UCD of interactive maps. Second, we report on a case study UCD process for GeoVISTA CrimeViz, an interactive and web-based mapping application supporting visual analytics of criminal activity in space and time. The GeoVISTA CrimeViz concept and interface were improved iteratively by working through a series of user→utility→usability loops in which target users provided input and feedback on needs and designs (user), prompting revisions to the conceptualization and functional requirements of the interface (utility), and ultimately leading to new mockups and prototypes of the interface (usability) for additional evaluation by target users (user… and so on). Together, the background review and case study offer guidance for applying UCD to interactive mapping projects, and demonstrate the benefit of including target users throughout design and development.

HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America ( http://geography.wisc.edu/hazardouswaste/map/ ). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade.

Geographically referenced faunal surveys are essential for land managers, conservation biologists, and entomologists to understand the distribution and diversity of organisms in the landscape. Further, the provision of faunal surveys through online and interactive mapping tools may generate new insights into species occurrence and location, ultimately leading to better informed decisions about how best to manage these species and their habitats. With these considerations in mind, we developed Weevil Viewer, an online, interactive mapping application for displaying the results of a faunal survey conducted on the four primitive weevil families found in Wisconsin. Design of Weevil Viewer was informed by Shneiderman's information seeking mantra, providing a pair of map overviews that can be filtered or zoomed iteratively by species, location, and time to glean new insights into the faunal distribution and diversity as well as to identify potential sites for future surveys. Weevil Viewer continues to be populated with new survey information and serves as a proof-of-concept application that can be extended to support the visual exploration of other biodiversity surveys.

Background While high-risk geographic clusters of cervical cancer mortality have previously been assessed, factors associated with this geographic patterning have not been well studied. Once these factors are identified, etiologic hypotheses and targeted population-based interventions may be developed and lead to a reduction in geographic disparities in cervical cancer mortality. Methods The authors linked multiple data sets at the county level to assess the effects of social domains, behavioral risk factors, local physician and hospital availability, and Chlamydia trachomatis infection on overall spatial clustering and on individual clusters of cervical cancer mortality rates in 2000-2004 among 3,105 US counties in the 48 states and the District of Columbia. Results During the study period, a total of 19,898 cervical cancer deaths occurred in women aged 20 and older. The distributions of county-level characteristics indicated wide ranges in social domains measured by demographics and socioeconomic status, local health care resources, and the rate of chlamydial infection. We found that overall geographic clustering of increased cervical cancer mortality was related to the high proportion of black population, low socioeconomic status, low Papanicolaou test rate, low health care coverage, and the high chlamydia rate; however, unique characteristics existed for each individual cluster, and the Appalachian cluster was not related to a high proportion of black population or to chlamydia rates. Discussion This study indicates that local social domains, behavioral risk, and health care sources are associated with geographic disparities in cervical cancer mortality rates. The association between the chlamydia rate and the cervical cancer mortality rate may be confounded by other factors known to be a risk for cervical cancer mortality, such as the infection with human papillomavirus. The findings will help cancer researchers examine etiologic hypotheses and develop tailored, cluster-specific interventions to reduce cervical cancer disparities.

Here we present Tambopata: Who Owns Paradise?, a map-centric, multimedia website created to enrich an educational role playing exercise about biodiversity, conservation, and development in the Amazon ( www.geography.wisc.edu/tambopata ). The exercise assigns students a character from the Tambopata region of the Peruvian Amazon, and asks them to evaluate four proposed zoning plans from their assigned perspective. Using principles of web cartography, we designed the four proposal maps to communicate complex information and allow for increased exploration. Compared to the previously used static maps, the website increases opportunities for student engagement with the material, incorporates multimedia, and clarifies spatial relationships and land use patterns. The website is available publicly and can be integrated freely into other university and high school courses.

Predictors of teachers' responsible environmental behavior (REB) were assessed. A 9-page questionnaire was mailed to 300 randomly selected secondary teachers in Hualien County, Taiwan. The response rate was 78.7%. Stepwise multiple regression analyses showed that the most parsimonious set of predictors of REB for all teachers included perceived knowledge of environmental action strategies (KNOW), intention to act (IA), and perceived skill in using environmental action strategies (SKILL; total R 2 = .3236). For urban teachers, the most parsimonious set of predictors included IA, SKILL, and environmental responsibility (total R 2 = .3705). For rural teachers, the most parsimonious set of predictors included KNOW, IA, and perceived knowledge of environmental problems and issues (total R 2 = .3001). Implications for program development and instructional practice are presented, and recommendations for further research are provided.

This descriptive, correlational study examined associations between the level of teacher (K-6) preparation in environmental education and the level of implementation of EE in elementary school classrooms in Wisconsin (mandated pre-service competence) and Ohio (no preservice competence mandate). The study also measured elementary schoolteachers' attitudes toward EE. Findings from this study indicated that Wisconsin elementary teachers received more preservice EE preparation and implemented more EE than Ohio teachers. Attitudes toward EE were similar, but the Wisconsin teachers seemed more confident about teaching EE concepts. Wisconsin responses indicate that, despite the preservice requirement, some teachers received little or no EE preparation. Wisconsin teachers achieved a higher rate of EE implementation in the elementary school classroom than Ohio teachers achieved. The authors concluded that for Grades K-6, successful implementation of EE includes teacher preparation and emphasis on teacher attitudes.

The past decade has witnessed the rapid development of geospatial artificial intelligence (GeoAI) primarily due to the ground-breaking achievements in deep learning and machine learning. A growing number of scholars from cartography have demonstrated successfully that GeoAI can accelerate previously complex cartographic design tasks and even enable cartographic creativity in new ways. Despite the promise of GeoAI, researchers and practitioners have growing concerns about the ethical issues of GeoAI for cartography. In this paper, we conducted a systematic content analysis and narrative synthesis of research studies integrating GeoAI and cartography to summarize current research and development trends regarding the usage of GeoAI for cartographic design. Based on this review and synthesis, we first identify dimensions of GeoAI methods for cartography such as data sources, data formats, map evaluations, and six contemporary GeoAI models, each of which serves a variety of cartographic tasks. These models include decision trees, knowledge graph and semantic web technologies, deep convolutional neural networks, generative adversarial networks, graph neural networks, and reinforcement learning. Further, we summarize seven cartographic design applications where GeoAI have been effectively employed: generalization, symbolization, typography, map reading, map interpretation, map analysis, and map production. We also raise five potential ethical challenges that need to be addressed in the integration of GeoAI for cartography: commodification, responsibility, privacy, bias, and (together) transparency, explainability, and provenance. We conclude by identifying four potential research directions for future cartographic research with GeoAI: GeoAI-enabled active cartographic symbolism, human-in-the-loop GeoAI for cartography, GeoAI-based mapping-as-a-service, and generative GeoAI for cartography.