scholarly journals Developing a Data-Literate Workforce through BLUE: Biodiversity Literacy in Undergraduate Education

2019 ◽  
Vol 3 ◽  
Author(s):  
Elizabeth R. Ellwood ◽  
Anna Monfils ◽  
Lisa White ◽  
Debra Linton ◽  
Natalie Douglas ◽  
...  
Keyword(s):  
Undergraduate Education ◽  
Disease Transmission ◽  
Large Scale ◽  
Science Curriculum ◽  
Ecological Data ◽  
Biodiversity Data ◽  
Undergraduate Biology ◽  
Data Literacy ◽  
Biodiversity Science ◽  
Science Community

The biodiversity sciences have experienced a rapid mobilization of data that has increased our capacity to investigate large-scale issues of critical importance (e.g., climate change and its impacts, zoonotic disease transmission, sustainable resource management, impacts of invasive species, and biodiversity loss). Several initiatives are underway to aggregate and mobilize these biodiversity, environmental, and ecological data resources (iDigBio, NEON, GBIF, iNaturalist, etc.). This requires a new set of skills for the 21st century biodiversity scientist; who is required to be fluent in integrative fields spanning evolutionary biology, systematics, ecology, geology, and environmental science and possess the quantitative, computational, and data skills to conduct research using large and complex datasets. The biodiversity science community has recognized a need to unite biodiversity and data sciences and improve data literacy in the emerging science workforce. The NSF-funded Biodiversity Literacy in Undergraduate Education (BLUE; biodiversityliteracy.com) is working to bridge a gap between efforts that currently exists to promote data literacy pre-college and professional development for those pursuing careers in biodiversity science. The BLUE network is developing strategies and materials to infuse biodiversity data into the core of the undergraduate science curriculum, facilitating broad-scale adoption of biodiversity data literacy competencies, and improving undergraduate biology training to meet increasing workforce demands in data and biodiversity sciences. The BLUE network has four major goals: 1) Cultivate a diverse and inclusive network of biodiversity researchers, data scientists, and biology educators focused on undergraduate data-centric biodiversity education; 2) build community consensus on core biodiversity data literacy competencies; 3) develop strategies and exemplar materials to guide the integration of biodiversity data literacy competencies into introductory undergraduate biology curricula; and 4) extend the network to engage a broader community of undergraduate educators in biodiversity data literacy efforts. The BLUE community continues to grow and build new partnerships and initiatives across the biodiversity science community. In year two of the BLUE network we have been focusing efforts building the community, developing and disseminating exemplar educational materials, and defining core biodiversity data literacy skills and competencies. We will present our current and ongoing work and ways in which members of the biodiversity_next community can be involved in shaping the biodiversity science of the future, while addressing the needs of a changing planet.

scholarly journals Preparing the Next Generation of Data-Driven Scientists through the Biodiversity Literacy in Undergraduate Education – Data Initiative (BLUE Data)

2018 ◽  
Vol 2 ◽  
pp. e27162
Author(s):  
Anna Monfils ◽  
Elizabeth Ellwood ◽  
Debra Linton ◽  
Molly Phillips ◽  
Lisa White ◽  
...  
Keyword(s):  
Undergraduate Students ◽  
Undergraduate Education ◽  
Data Science ◽  
Literacy Skills ◽  
Biodiversity Data ◽  
Undergraduate Biology ◽  
Data Literacy ◽  
Education Data ◽  
One Year ◽  
Scale Integration

The Biodiversity Literacy in Undergraduate Education - Data Initiative (BLUE Data) is a US National Science Foundation-funded Research Coordination Network in Undergraduate Biology (RCN-UBE) working to generate community consensus around biodiversity data literacy skills. This diverse network brings together biodiversity, data, and education specialists to identify core biodiversity data competencies for undergraduate students, develop strategies for integrating these competencies into the introductory biology curriculum, and build capacity for sustained development and implementation of biodiversity and data literacy education. Since the start of funding one year ago, BLUE Data has been working to review the current landscape of data literacy competencies from primary to graduate education in biodiversity data science, identify gaps in student learning related to data and biodiversity science core skills, and generate community consensus on defined biodiversity data literacy standards. At a recent BLUE Data workshop associated with the Emerging Innovations for Biodiversity Data conference in Berkeley, California, participants worked together to define competencies and identify strategies to facilitate broad-scale integration of transferrable data literacy skills and knowledge to improve undergraduate biology training and meet increasing workforce demands in both data and biodiversity sciences. This discussion also identified current efforts and explored existing resources in order to identify gaps that should be targeted in our efforts moving forward. In this presentation, we will introduce the SPNHC and TDWG communities to BLUE Data, and describe our vision and goals, partners, and educational modules. We will share results from our recent activities, including the outcomes of the Emerging Innovations for Biodiversity Data workshop. BLUE Data welcomes new partnerships with those also interested in defining the undergraduate biodiversity data literacy landscape and charting future efforts of this network.

scholarly journals Emerging Education Resources and Initiatives: Harnessing the Potential of Disciplinary Societies to advance Biodiversity literacy

2018 ◽  
Vol 2 ◽  
Author(s):  
Teresa Mourad
Keyword(s):  
Undergraduate Education ◽  
Culturally Responsive ◽  
Core Competencies ◽  
Biology Education ◽  
Biodiversity Data ◽  
Faculty Professional Development ◽  
Undergraduate Biology ◽  
Scientific Endeavor ◽  
Open The Doors ◽  
Education Conference

Symposium “Completing the Data Pipeline: Collections Data Use in Research, Education and Outreach. The conference theme, Collections and Data in an Uncertain World, turns the spotlight on a number of opportunities that can advance the experience of undergraduate biology education. Today, millions of records from Natural History Collections worldwide are available to students and educators through portals such as iDigBio, https://www.idigbio.org/portal/search. These records facilitate explorations for disciplinary and interdisciplinary understanding of a changing and uncertain biodiversity landscape across space and time. Biological and paleontological specimens data can be combined with ecological or geological data to investigate large scale questions related to climate change, invasive species or resource management. This session highlights resources and initiatives of the Ecological Society of America (ESA) for undergraduate students and faculty that focus on emerging developments in core competencies, careers and diversity. For too long, undergraduate biology/ecology education has centered primarily round mastery of disciplinary content often involving rote learning. The Vision and Change in Undergraduate Biology Education conference organized by the American Association for the Advancement of Science (AAAS) in 2009 identified a set of core competencies that include understanding of the nature of science, communication, collaboration, and quantitative skills. These skills, and the fluency across disciplines such as ecology, environmental science, evolutionary biology and systematics are the hallmarks of the 21st century biologist. www.visionandchange.org ESA has long advocated active learning in the classroom. In 2006, ESA education leaders launched, Teaching Issues and Experiments in Ecology (TIEE), an education journal designed to promote inquiry, scientific thinking, collaborative work, formative evaluation, and alternative assessment in the college classroom. Today, the LifeDiscoveryEd Digital Library (LDDL), www.lifediscoveryed.org, built on the metadata architecture of ESA’s EcoEd Digital Library established in 2006, serves three disciplinary society communities including ESA, Botanical Society of America (BSA) and Society for the Study of Evolution (SSE), encouraging cross-dissemination of resources. Together, the three societies form the LifeDiscovery partners and co-organize the Life Discovery – Doing Science Biology Education conference (LDC) every 18 months, www.esa.org/ldc. A unique feature of the LDC is the Education Share Fair where participants may present teaching ideas at any stage of development to solicit feedback from their peers. In a response to a need for a more robust approach to advancing data literacy, ESA joined with the Quantitative Undergraduate Biology Education and Synthesis (QUBES) project, to offer a series of Faculty Mentoring Networks (FMN) launched in 2016, https://qubeshub.org, http://esa.org/fed/fmn/. Additionally, ESA is a pioneer in undergraduate diversity mentoring through the Strategies for Ecology Education, Diversity and Sustainability (SEEDS) program, www.esa.org/seeds which has a campus chapter network in 100 campuses developed since 1996. In 2016, ESA became involved in the 3dnaturalists project, led by Colorado State University, that seeks to understand how bioblitzes might make a difference in recruiting and retaining underrepresented minorities in ecology and sustainability sciences. In 2017, ESA joined the Core Team of the Biodiversity Literacy in Undergraduate Education (BLUE) network project to liaise with relevant scientific and professional societies and to provide input on engaging diverse participants in the project This session will discuss: how ESA’s education initiatives can be leveraged for faculty professional development in the Biodiversity Literacy in Undergraduate Education (BLUE) project. the ways that engaging students in biodiversity data in ecology research will open the doors to building key biological science competencies and 21st century careers the potential of using place-based specimen data through bioblitzes to engage minority students in a culturally responsive scientific endeavor. how ESA’s education initiatives can be leveraged for faculty professional development in the Biodiversity Literacy in Undergraduate Education (BLUE) project. the ways that engaging students in biodiversity data in ecology research will open the doors to building key biological science competencies and 21st century careers the potential of using place-based specimen data through bioblitzes to engage minority students in a culturally responsive scientific endeavor.

scholarly journals Tools and Techniques of Implementation Science to Support Wide-Spread Adoption of Biodiversity Literacy Standards

2018 ◽  
Vol 2 ◽  
pp. e27160
Author(s):  
Natalie Douglas ◽  
Anna Monfils ◽  
Elizabeth R. Ellwood
Keyword(s):  
Best Practices ◽  
Implementation Science ◽  
Core Competencies ◽  
Biology Education ◽  
Wide Spread ◽  
Biodiversity Data ◽  
Undergraduate Biology ◽  
Data Literacy ◽  
Literacy Standards ◽  
Tools And Techniques

Implementation science boasts tools and techniques to increase the chances of adoption of best practices to a wide variety of users. Theoretical roots of implementation science are present in education, mental health and health services research. This talk will highlight the application of implementation science principles to the wide-spread adoption of biodiversity data literacy standards. Perspectives from key stakeholders including biology instructors of all ranks at community colleges, minority serving institutions, primarily undergraduate institutions, research intensive universities, biodiversity researchers, and scientific society leaders and policy makers, will be presented according to need, fit, resources, capacity and readiness to support the implementation of biodiversity data literacy standards in undergraduate biology curriculums. Through systematic exploration of the facilitators and barriers to the implementation of biodiversity data literacy standards across multiple participants and people groups, specific action steps will be highlighted to address such barriers. Consistent with the Vision and Change in Undergraduate Biology Education: A Call to Action, this talk will describe the collaborations completed and in-process by the BLUE network that support an accessible student and data-centered pedagogy, designed to support diverse and underrepresented learners. For example, core biodiversity data literacy competencies will be described according to field leaders and perceived barriers to implementation of these competencies will provide a springboard for further discussion and action. Principles of implementation science explicitly recognize that best practices such as biodiversity data literacy standards, are useful only if they reach diverse intended users – otherwise, best practices and core competencies may have the opposite effect – contributing to educational and health disparities. This talk will highlight the active implementation strategies BLUE has employed to support engagement across distinct people groups to support implementation of these standards. As opposed to developing standards and having a “wait and hope” approach to these standards distilling to undergraduate biology curriculums, strategies discussed in this talk will serve as a catalyst for wide-spread adoption of the standards scientists have worked so rigorously to foster.

scholarly journals Biodiversity Observations Miner: A web application to unlock primary biodiversity data from published literature

2019 ◽  
Vol 7 ◽  
Author(s):  
Gabriel Muñoz ◽  
W. Daniel Kissling ◽  
E. Emiel van Loon
Keyword(s):  
Text Mining ◽  
Knowledge Discovery ◽  
Web Application ◽  
Large Scale ◽  
Biotic Interactions ◽  
Rapid Screening ◽  
Biodiversity Data ◽  
Biodiversity Science ◽  
Automated Discovery ◽  
Machine Readable

A considerable portion of primary biodiversity data is digitally locked inside published literature which is often stored as pdf files. Large-scale approaches to biodiversity science could benefit from retrieving this information and making it digitally accessible and machine-readable. Nonetheless, the amount and diversity of digitally published literature pose many challenges for knowledge discovery and retrieval. Text mining has been extensively used for data discovery tasks in large quantities of documents. However, text mining approaches for knowledge discovery and retrieval have been limited in biodiversity science compared to other disciplines. Here, we present a novel, open source text mining tool, the Biodiversity Observations Miner (BOM). This web application, written in R, allows the semi-automated discovery of punctual biodiversity observations (e.g. biotic interactions, functional or behavioural traits and natural history descriptions) associated with the scientific names present inside a corpus of scientific literature. Furthermore, BOM enable users the rapid screening of large quantities of literature based on word co-occurrences that match custom biodiversity dictionaries. This tool aims to increase the digital mobilisation of primary biodiversity data and is freely accessible via GitHub or through a web server.

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

scholarly journals Presence of subclinical infection in gene-targeted human prion protein transgenic mice exposed to atypical bovine spongiform encephalopathy

2013 ◽  
Vol 94 (12) ◽  
pp. 2819-2827 ◽  
Author(s):  
Rona Wilson ◽  
Karen Dobie ◽  
Nora Hunter ◽  
Cristina Casalone ◽  
Thierry Baron ◽  
...  
Keyword(s):  
Human Health ◽  
Bovine Spongiform Encephalopathy ◽  
Prion Protein ◽  
Disease Transmission ◽  
Large Scale ◽  
Single Agent ◽  
Diagnostic Methods ◽  
Transmissible Spongiform Encephalopathies ◽  
Spongiform Encephalopathy ◽  
Human Prion Protein

The transmission of bovine spongiform encephalopathy (BSE) to humans, leading to variant Creutzfeldt–Jakob disease has demonstrated that cattle transmissible spongiform encephalopathies (TSEs) can pose a risk to human health. Until recently, TSE disease in cattle was thought to be caused by a single agent strain, BSE, also known as classical BSE, or BSE-C. However, due to the initiation of a large-scale surveillance programme throughout Europe, two atypical BSE strains, bovine amyloidotic spongiform encephalopathy (BASE, also named BSE-L) and BSE-H have since been discovered. To model the risk to human health, we previously inoculated these two forms of atypical BSE (BASE and BSE-H) into gene-targeted transgenic (Tg) mice expressing the human prion protein (PrP) (HuTg) but were unable to detect any signs of TSE pathology in these mice. However, despite the absence of TSE pathology, upon subpassage of some BASE-challenged HuTg mice, a TSE was observed in recipient gene-targeted bovine PrP Tg (Bov6) mice but not in HuTg mice. Disease transmission from apparently healthy individuals indicates the presence of subclinical BASE infection in mice expressing human PrP that cannot be identified by current diagnostic methods. However, due to the lack of transmission to HuTg mice on subpassage, the efficiency of mouse-to-mouse transmission of BASE appears to be low when mice express human rather than bovine PrP.

scholarly journals Integrating multiple species criteria and species hypotheses in subterranean biology

2018 ◽  
Vol 1 ◽  
Author(s):  
Florian Malard ◽  
Philippe Grison ◽  
David Eme ◽  
Cene Fiser ◽  
Jean-François Flot ◽  
...  
Keyword(s):  
Large Scale ◽  
Species Concept ◽  
Genetic Isolation ◽  
Scientific Rigor ◽  
Geographic Range Size ◽  
Biodiversity Science ◽  
Multiple Species ◽  
Methodological Advance ◽  
New Generation ◽  
Scientific Hypotheses

Decades of debates around the species problem have resulted in the emergence of a unified species concept with multiple criteria to delimit species taxa. Many biologists now agree to consider species as separately evolving segments of metapopulation lineages (i.e. the species concept), and to consider species taxa (i.e. the elementary units used in biodiversity science) as scientific hypotheses of separately evolving entities. In this framework, sets of species hypotheses are generated using different criteria (i.e. morphological distinguishability, genetic isolation) that mirror the properties expressed by species at different times and sequential orders during the extended and heterogeneous process of speciation. This conceptual and methodological advance in taxonomy has several implications for biodiversity science. First, species taxa represent a heterogeneous set of hypotheses whose properties are contingent on the heterogeneous, continuous and extended nature of speciation. Second, species databases need to integrate information on the diverse properties of species by attributing specimens to multiple species hypotheses generated using different delimitation criteria. Third, biodiversity science at large can provide novel insights into biodiversity processes by incorporating multiple species hypotheses into the analysis of biodiversity patterns. Here, we show how these implications have been taken into account by subterranean biologists. First, we briefly review the criteria and methods used to delimit species in subterranean biology and the diverse sets of species hypotheses they generated. Second, we present a new generation of species occurrence databases that integrate different species criteria and hypotheses while fully respecting the scientific rigor of taxonomy. Last, we show how incorporating multiple species hypotheses into macroecological analyses of European groundwater fauna bolsters our under­standing of the factors shaping large-scale patterns of species richness and geographic range size.

scholarly journals The Opportunities and Limitations of Using Artificial Neural Networks in Social Science Research

Politologija ◽  
2019 ◽  
Vol 94 (2) ◽  
pp. 56-80
Author(s):  
Lukas Pukelis ◽  
Vilius Stančiauskas
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Social Science ◽  
Large Scale ◽  
Social Science Research ◽  
Complex Data ◽  
Social Science Community ◽  
The Social ◽  
Science Community ◽  
Artificial Neural

Artificial Neural Networks (ANNs) are being increasingly used in various disciplines outside computer science, such as bibliometrics, linguistics, and medicine. However, their uptake in the social science community has been relatively slow, because these highly non-linear models are difficult to interpret and cannot be used for hypothesis testing. Despite the existing limitations, this paper argues that the social science community can benefit from using ANNs in a number of ways, especially by outsourcing laborious data coding and pre-processing tasks to machines in the early stages of analysis. Using ANNs would enable small teams of researchers to process larger quantities of data and undertake more ambitious projects. In fact, the complexity of the pre-processing tasks that ANNs are able to perform mean that researchers could obtain rich and complex data typically associated with qualitative research at a large scale, allowing to combine the best from both qualitative and quantitative approaches.

scholarly journals Potential for community based surveillance of febrile diseases: Feasibility of self-administered rapid diagnostic tests in Iquitos, Peru and Phnom Penh, Cambodia

2021 ◽  
Vol 15 (4) ◽  
pp. e0009307
Author(s):  
Amy C. Morrison ◽  
Julia Schwarz ◽  
Jennie L. Mckenney ◽  
Jhonny Cordova ◽  
Jennifer E. Rios ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Disease Transmission ◽  
Diagnostic Tests ◽  
Large Scale ◽  
Health Workers ◽  
Rapid Diagnostic Tests ◽  
Community Members ◽  
Phnom Penh ◽  
Local Public Health ◽  
At Home

Rapid diagnostic tests (RDTs) have the potential to identify infectious diseases quickly, minimize disease transmission, and could complement and improve surveillance and control of infectious and vector-borne diseases during outbreaks. The U.S. Defense Threat Reduction Agency’s Joint Science and Technology Office (DTRA-JSTO) program set out to develop novel point-of-need RDTs for infectious diseases and deploy them for home use with no training. The aim of this formative study was to address two questions: 1) could community members in Iquitos, Peru and Phnom Penh, Cambodia competently use RDTs of different levels of complexity at home with visually based instructions provided, and 2) if an RDT were provided at no cost, would it be used at home if family members displayed febrile symptoms? Test kits with written and video (Peru only) instructions were provided to community members (Peru [n = 202]; Cambodia [n = 50]) or community health workers (Cambodia [n = 45]), and trained observers evaluated the competency level for each of the several steps required to successfully operate one of two multiplex RDTs on themselves or other consenting participant (i.e., family member). In Iquitos, >80% of residents were able to perform 11/12 steps and 7/15 steps for the two- and five-pathogen test, respectively. Competency in Phnom Penh never reached 80% for any of the 12 or 15 steps for either test; the percentage of participants able to perform a step ranged from 26–76% and 23–72%, for the two- and five-pathogen tests, respectively. Commercially available NS1 dengue rapid tests were distributed, at no cost, to households with confirmed exposure to dengue or Zika virus; of 14 febrile cases reported, six used the provided RDT. Our findings support the need for further implementation research on the appropriate level of instructions or training needed for diverse devices in different settings, as well as how to best integrate RDTs into existing local public health and disease surveillance programs at a large scale.

scholarly journals To increase trust, change the social design behind aggregated biodiversity data

Database ◽  
2018 ◽  
Vol 2018 ◽  
Author(s):  
Nico M Franz ◽  
Beckett W Sterner
Keyword(s):  
Large Scale ◽  
Syntactic Structure ◽  
Original Data ◽  
Quality Data ◽  
Systematic Research ◽  
Aggregation Process ◽  
Biodiversity Data ◽  
Social Design ◽  
The Social ◽  
Accountability Gap

Abstract Growing concerns about the quality of aggregated biodiversity data are lowering trust in large-scale data networks. Aggregators frequently respond to quality concerns by recommending that biologists work with original data providers to correct errors ‘at the source.’ We show that this strategy falls systematically short of a full diagnosis of the underlying causes of distrust. In particular, trust in an aggregator is not just a feature of the data signal quality provided by the sources to the aggregator, but also a consequence of the social design of the aggregation process and the resulting power balance between individual data contributors and aggregators. The latter have created an accountability gap by downplaying the authorship and significance of the taxonomic hierarchies—frequently called ‘backbones’—they generate, and which are in effect novel classification theories that operate at the core of data-structuring process. The Darwin Core standard for sharing occurrence records plays an under-appreciated role in maintaining the accountability gap, because this standard lacks the syntactic structure needed to preserve the taxonomic coherence of data packages submitted for aggregation, potentially leading to inferences that no individual source would support. Since high-quality data packages can mirror competing and conflicting classifications, i.e. unsettled systematic research, this plurality must be accommodated in the design of biodiversity data integration. Looking forward, a key directive is to develop new technical pathways and social incentives for experts to contribute directly to the validation of taxonomically coherent data packages as part of a greater, trustworthy aggregation process.

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