Despite growing calls to develop data science students’ ethical awareness and expand human-centered approaches to data science education, introductory courses in the field remain largely technical. A new interdisciplinary data science program aims to merge STEM and humanities perspectives starting at the very beginning of the data science curriculum. Existing literature suggests that humanities integration can make STEM courses more appealing to a wider range of students, including women and students of color, and enhance student learning of essential concepts and foundational reasoning skills, such as those collectively known as data acumen. Cultivating students’ data acumen requires a more inclusive vision of how the knowledge and insights generated through computational methods and statistical analysis relates to other ways of knowing.
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Collections Education: The Extended Specimen and Data Acumen
Abstract Biodiversity scientists must be fluent across disciplines; they must possess the quantitative, computational, and data skills necessary for working with large, complex data sets, and they must have foundational skills and content knowledge from ecology, evolution, taxonomy, and systematics. To effectively train the emerging workforce, we must teach science as we conduct science and embrace emerging concepts of data acumen alongside the knowledge, tools, and techniques foundational to organismal biology. We present an open education resource that updates the traditional plant collection exercise to incorporate best practices in twenty-first century collecting and to contextualize the activities that build data acumen. Students exposed to this resource gained skills and content knowledge in plant taxonomy and systematics, as well as a nuanced understanding of collections-based data resources. We discuss the importance of the extended specimen in fostering scientific discovery and reinforcing foundational concepts in biodiversity science, taxonomy, and systematics.
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- NSF-PAR ID:
- 10336284
- Date Published:
- Journal Name:
- BioScience
- Volume:
- 72
- Issue:
- 2
- ISSN:
- 0006-3568
- Page Range / eLocation ID:
- 177 to 188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Societal Impact Statement The practice of writing science blogs benefits both the scientist and society alike by providing professional development opportunities and delivering information in a format that is accessible to large and diverse audiences. By designing a project that introduced upper‐level undergraduate students to science blog writing with a focus on plant biology, we piqued students' interest in science writing and the content of a popular plant science blog website. If adopted more widely, this work could broaden the scope of science education and promote the development of effective science communication skills for the next generation of scientists.
Summary Successful scientists must communicate their research to broad audiences, including distilling key scientific concepts for the general public. Students pursuing careers in Science, Technology, Engineering, and Mathematics (STEM) fields benefit from developing public communication skills early in their careers, but opportunities are limited in traditional biology curricula.
We created the “Plant Science Blogging Project” for a Plant Biology undergraduate course at the University of Pittsburgh in Fall 2018 and 2019. Students wrote blog posts merging personal connections with plants with plant biology concepts for the popular science blogs
Plant Love Stories andEvoBites . By weaving biology into their narratives, students learned how to share botanical knowledge with the general public.The project had positive impacts on student learning and public engagement. In post‐assignment surveys, the majority of students reported that they enjoyed the assignment, felt it improved their understanding of plant biology, and piqued their interest in reading and writing science blogs in the future. Approximately one‐third of the student‐authored blogs were published, including two that rose to the top 10 most‐read posts on Plant Love Stories. Some dominant themes in student blogs, including medicine and culture, differed from common story themes published on the web, indicating the potential for students to diversify science blog content.
Overall, the Plant Science Blogging Project allows undergraduate students to engage with plant biology topics in a new way, sharpen their scientific communication skills in accordance with today's world of mass information sharing, and contribute to the spread of scientific knowledge for public benefit.
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As we look to the future of natural history collections and a global integration of biodiversity data, we are reliant on a diverse workforce with the skills necessary to build, grow, and support the data, tools, and resources of the Digital Extended Specimen (DES; Webster 2019, Lendemer et al. 2020, Hardisty 2020). Future “DES Data Curators” – those who will be charged with maintaining resources created through the DES – will require skills and resources beyond what is currently available to most natural history collections staff. In training the workforce to support the DES we have an opportunity to broaden our community and ensure that, through the expansion of biodiversity data, the workforce landscape itself is diverse, equitable, inclusive, and accessible. A fully-implemented DES will provide training that encapsulates capacity building, skills development, unifying protocols and best practices guidance, and cutting-edge technology that also creates inclusive, equitable, and accessible systems, workflows, and communities. As members of the biodiversity community and the current workforce, we can leverage our knowledge and skills to develop innovative training models that: include a range of educational settings and modalities; address the needs of new communities not currently engaged with digital data; from their onset, provide attribution for past and future work and do not perpetuate the legacy of colonial practices and historic inequalities found in many physical natural history collections. Recent reports from the Biodiversity Collections Network (BCoN 2019) and the National Academies of Science, Engineering and Medicine (National Academies of Sciences, Engineering, and Medicine 2020) specifically address workforce needs in support of the DES. To address workforce training and inclusivity within the context of global data integration, the Alliance for Biodiversity Knowledge included a topic on Workforce capacity development and inclusivity in Phase 2 of the consultation on Converging Digital Specimens and Extended Specimens - Towards a global specification for data integration. Across these efforts, several common themes have emerged relative to workforce training and the DES. A call for a community needs assessment: As a community, we have several unknowns related to the current collections workforce and training needs. We would benefit from a baseline assessment of collections professionals to define current job responsibilities, demographics, education and training, incentives, compensation, and benefits. This includes an evaluation of current employment prospects and opportunities. Defined skills and training for the 21st century collections professional: We need to be proactive and define the 21st century workforce skills necessary to support the development and implementation of the DES. When we define the skills and content needs we can create appropriate training opportunities that include scalable materials for capacity building, educational materials that develop relevant skills, unifying protocols across the DES network, and best practices guidance for professionals. Training for data end-users: We need to train data end-users in biodiversity and data science at all levels of formal and informal education from primary and secondary education through the existing workforce. This includes developing training and educational materials, creating data portals, and building analyses that are inclusive, accessible, and engage the appropriate community of science educators, data scientists, and biodiversity researchers. Foster a diverse, equitable, inclusive, and accessible and professional workforce: As the DES develops and new tools and resources emerge, we need to be intentional in our commitment to building tools that are accessible and in assuring that access is equitable. This includes establishing best practices to ensure the community providing and accessing data is inclusive and representative of the diverse global community of potential data providers and users. Upfront, we must acknowledge and address issues of historic inequalities and colonial practices and provide appropriate attribution for past and future work while ensuring legal and regulatory compliance. Efforts must include creating transparent linkages among data and the humans that create the data that drives the DES. In this presentation, we will highlight recommendations for building workforce capacity within the DES that are diverse, inclusive, equitable and accessible, take into account the requirements of the biodiversity science community, and that are flexible to meet the needs of an evolving field.more » « less
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Abstract Natural history, loosely defined as the observational study of organisms in the habitats where they occur, is recognized at the roots of ecology. Although the centrality of natural history in ecology has shifted over time, natural history is currently in resurgence: many again consider it to be the foundation of ecological and evolutionary inquiry and advocate the value of organism‐centered approaches to address contemporary ecological challenges. Educators identify natural history as the foundational entryway into the practice of ecology, for example in the Ecological Society of America's Four‐Dimensional Ecology Education (4DEE) framework. A strong natural history foundation can help generate testable hypotheses to refine mechanistic understanding of the drivers regulating species distributions and abundances and to inform restoration and conservation efforts. Given the resurgence of natural history as the foundation for ecological knowledge and practice, it is important to recognize that natural history has a long history of racism that has impacted ecological thought and priorities. This history shapes not only who conducts ecological science but also foundational ecological concepts. For example, natural history's emphasis on pristine nature untouched by humans disregards or appropriates stewardship and knowledge of most of the world's population. Because of the legacy of chattel slavery, this exclusion is particularly strong for people of African descent. This exclusion narrows ecological inquiry, limits the capacity to find solutions to ecological problems, and risks interventions that perpetuate the relation between eugenics, ecological knowledge, and natural systems. If ecology is to become an inclusive, responsive, and resilient discipline, this knowledge gap must be addressed. We here present the colonial and racist underpinnings of natural history and offer strategies to expand inclusion in the study of nature. Natural history was steeped in racism, providing a hierarchy of cultures and a taxonomy of races. Complementing growing interest in traditional and Indigenous ecological knowledge, we focus on Black ecological knowledge, for example in the study of “maroon ecologies.” Addressing the racist history of natural history is necessary for removing structural and racist barriers to diverse participation and expanding ecological knowledge bases in service of better and more just science.
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Translating information between the domains of systematics and conservation requires novel information management designs. Such designs should improve interactions across the trading zone between the domains, herein understood as the model according to which knowledge and uncertainty are productively translated in both directions (cf. Collins et al. 2019). Two commonly held attitudes stand in the way of designing a well-functioning systematics-to-conservation trading zone. On one side, there are calls to unify the knowledge signal produced by systematics, underpinned by the argument that such unification is a necessary precondition for conservation policy to be reliably expressed and enacted (e.g., Garnett et al. 2020). As a matter of legal scholarship, the argument for systematic unity by legislative necessity is principally false (Weiss 2003, MacNeil 2009, Chromá 2011), but perhaps effective enough as a strategy to win over audiences unsure about robust law-making practices in light of variable and uncertain knowledge. On the other side, there is an attitude that conservation cannot ever restrict the academic freedom of systematics as a scientific discipline (e.g., Raposo et al. 2017). This otherwise sound argument misses the mark in the context of designing a productive trading zone with conservation. The central interactional challenge is not whether the systematic knowledge can vary at a given time and/or evolve over time, but whether these signal dynamics are tractable in ways that actors can translate into robust maxims for conservation. Redesigning the trading zone should rest on the (historically validated) projection that systematics will continue to attract generations of inspired, productive researchers and broad-based societal support, frequently leading to protracted conflicts and dramatic shifts in how practioners in the field organize and identify organismal lineages subject to conservation. This confident outlook for systematics' future, in turn, should refocus the challenge of designing the trading zone as one of building better information services to model the concurrent conflicts and longer-term evolution of systematic knowledge. It would seem unreasonable to expect the International Union for Conservation of Nature (IUCN) Red List Index to develop better data science models for the dynamics of systematic knowledge (cf. Hoffmann et al. 2011) than are operational in the most reputable information systems designed and used by domain experts (Burgin et al. 2018). The reasonable challenge from conservation to systematics is not to stop being a science but to be a better data science. In this paper, we will review advances in biodiversity data science in relation to representing and reasoning over changes in systematic knowledge with computational logic, i.e., modeling systematic intelligence (Franz et al. 2016). We stress-test this approach with a use case where rapid systematic signal change and high stakes for conservation action intersect, i.e., the Malagasy mouse lemurs ( Microcebus É. Geoffroy, 1834 sec. Schüßler et al. 2020), where the number of recognized species-level concepts has risen from 2 to 25 in the span of 38 years (1982–2020). As much as scientifically defensible, we extend our modeling approach to the level of individual published occurrence records, where the inability to do so sometimes reflects substandard practice but more importantly reveals systemic inadequacies in biodiversity data science or informational modeling. In the absence of shared, sound theoretical foundations to assess taxonomic congruence or incongruence across treatments, and in the absence of biodiversity data platforms capable of propagating logic-enabled, scalable occurrence-to-concept identification events to produce alternative and succeeding distribution maps, there is no robust way to provide a knowledge signal from systematics to conservation that is both consistent in its syntax and acccurate in its semantics, in the sense of accurately reflecting the variation and uncertainty that exists across multiple systematic perspectives. Translating this diagnosis into new designs for the trading zone is only one "half" of the solution, i.e., a technical advancement that then would need to be socially endorsed and incentivized by systematic and conservation communities motivated to elevate their collaborative interactions and trade robustly in inherently variable and uncertain information.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/biosci/biab109
