EDSIN 2019 Lightning Presentations


Broadening Participation with Bioinformatics, Big Data, and Data Science

Jason Williams, Cold Spring Harbor Laboratory; Tuesday April 2, 2019 1:45 PM

This talk highlights challenges and opportunities surrounding bioinformatics training and aims to spark conversation reshaping the training landscape. As new methods such as machine learning/deep learning become more relevant to biology, we risk widening the intelligibility gap between the training “haves” and “have-nots.” The community has a need for extensive discussion on this topic and support for development of alternatives to classroom training that can bridge gaps between the large numbers of existing researchers who need to understand and apply data science skills, but who are unlikely to return to formal schooling. Findings by NIBLSE (pronounced “nibbles”) – Network for Integrating Bioinformatics in Life Sciences Education – revealed that 95% of faculty believe bioinformatics should be taught, but only 40% manage to do so (with clear disparities for faculty at less-resourced institutions). Input from the survey and a NIBLSE working group has also generated a set of bioinformatics competencies for undergraduate bioinformatics (Sayers et.al. 2018). A a survey of NSF-funded investigators in the biological sciences (Barone et.al. 2017) conclude that training in several areas of bioinformatics are the most unmet need for established researchers. Improving the bioinformatics curriculum opens up opportunities for broadened participation by equipping students and teachers with the skills needed for 21st century careers in STEM. Examples of CyVerse and Cold Spring Harbor DNA Learning Center programs that integrate bioinformatics, big data, and data science will illustrate effective ways to engage diverse students with in-demand skills.

 


Expanding the pipeline: Engaging urban secondary school and college students in science and the environment

Yael Wyner, City College of New York, City University of New York and Janice Koch, American University; Tuesday April 2, 2019 1:50 PM

This speed talk will describe three education projects that engage urban minority students in science and the environment.
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This speed talk will describe three education projects that engage urban minority students in science and the environment. Two projects focus on secondary school ecology and evolutionary biology learning in New York City science classrooms. The third project is a new science learning and public engagement major for City College of New York undergraduate students. Each of these projects seeks to increase access to science learning and science careers. With NSF funding, we created curricular resources grounded in published scientific data to connect the daily lives of New York City high school students to ecological concepts learned in school. We also created curricular resources for New York City middle school students to help them notice the evolutionary patterns of the sidewalk trees they pass daily. We are currently designing a new undergraduate program to prepare City College graduates to deliver STEM learning at botanical gardens, museums, zoos, environmental education centers, community-based organizations, educational, and science and environmental non-profits. The new City College program is a response to the unmet need to expand the science engagement pipeline to members of underrepresented groups.


Using spatial data and GIS for remote internships through the EcologyPlus program

Travis Belote, The Wilderness Society, Edem Yevoo, University of Maryland, and Teresa Mourad, Ecological Society of America; Tuesday April 2, 2019 1:55 PM

The EcologyPlus program recruits and supports a cohort of diverse students to pursue a variety of professional development opportunities through a diverse network of organizations. The Wilderness Society, as a partner organization, hosted three EcologyPlus student interns in the fall of 2018. The internship began with a week-long trip to Montana to visit Yellowstone National Park, meet local scientists, receive a short-course on geographic information systems (GIS) and spatial data, and develop research questions. Each student developed separate but related questions requiring various spatial datasets, data management, and analytical approaches. The students completed most of the work at their home institutions throughout the fall semester of 2018. The remote internship included biweekly check-ins including “shadowing” via screenshares to work through data analysis challenges. Students presented their work during a one-hour presentation and webinar at the end of the semester. We will discuss the value of spatial data and GIS in undergraduate education and provide recommendation for a successful remote internship. Our key recommendations include spending time together in-person for a kick-off event, regular check-in meetings with video conferencing and screenshares, and developing clear deliverables (report or professional presentation) to bookend the experience.


Impact of Urban Development in DC

Edem Yevoo, University of Maryland and Travis Belote, The Wilderness Society; Tuesday April 2, 2019 2:00 PM

As the global population continues to increase, more people are moving from rural to urban areas. In the next decades, most of the world's population will be living in urban areas. Utilizing geospatial data from the United States Geological Survey (USGS), a predictive visual model was created using geographic information systems (GIS) software. The model was used to predict the change in the District of Columbia's (DC) urban landscape over time. The use of GIS and data analysis systems hold the key to tackling current and future environmental issues. I will discuss the use of spatial data and how it can be used to impact policy, climate change, and socioeconomic conditions in our urban environments.


What is Big Data For?

Jennifer Balch, Earth Lab/University of Colorado-Boulder and  Kirsten Rowell, University of Colorado-Boulder; Tuesday April 2, 2019 2:05 PM

What are we actually harnessing the data revolution for? It's for humanity. Ultimately, big data should help improve people's lives and help society live more sustainably with our planet. It's not anyone's data, it's everyone's data. This makes it critical to involve, encourage, and support a diversity of people in owning the data and ultimately owning the solutions that come from that data.


Data science teaching alternatives from The Carpentries 

Tracy Teal, Kari L. Jordan and SherAaron Hurt, The Carpentries; Wednesday April 3, 2019 9:15 AM

Training for data skills is more critical now than ever before. In the past decade, we've seen the creation of certification and graduate programs for data science, as well as a plethora of interactive, self-paced online learning platforms. Today's learners are often learning on the job and need the flexibility of short, or self-paced learning experiences. Research results, however, stress the importance of guided instruction and learner-instructor interaction.
    We've taken a distinctive approach to this problem, combining the power of guided instruction with the flexibility of short, focused learning experiences. Two-day, interactive, hands-on coding workshops train researchers to work with data, and have impacted over 27,500 researchers, ranging from biologists to physicists to engineers and economists. Researchers have benefited from evidence-based teaching approaches to learning data organization (spreadsheets), cleaning (OpenRefine), management (SQL), analysis and visualization (R and Python).
    This talk focuses on implications and growth opportunities for incorporating data science curriculum at the university level, from the perspective of The Carpentries. We explore tips and best-practices in data science curriculum development including assessment strategies, accessibility, and equity and inclusion.


Building a diverse undergraduate community of learners in data science and biology

Sarah R. Supp, Denison University; Wednesday April 3, 2019 9:20 AM

This talk will use two examples to discuss inclusive pedagogical strategies for training in data science skills. Building a new interdisciplinary program for undergraduates in data analytics, we have a project-based pedagogy, and as a unit have considered ways in which we can spark interest and build academic successes for students more broadly, including students that are traditionally underrepresented in the Computer Sciences, or other related technical fields. This talk will also discuss an ongoing project to address gaps in training for undergraduate instructors, to enhance data education in biology curriculum, thus also broadening access to technical skills for students in these courses.


Centering Historically Underrepresented Voices in the Salish Sea

Melissa Watkinson, Salish Sea DEI Community of Practice; Wednesday April 3, 2019 9:25 AM

Addressing inequity and working toward environmental justice is essential to a successful environmental movement. Currently, there are significant disparities in the representation, content, and processes for implementing diversity, equity, and inclusion (DEI) within the environmental field across the Salish Sea and the Pacific Northwest Coast. Although professionals in this field are aware and concerned about issues related to DEI, there is an overall lack of understanding for how to integrate these concepts into the environmental workforce. Addressing inequity and working toward environmental justice is essential to a successful environmental movement. We believe that by creating and fostering a Salish Sea DEI Community of Practice (CoP), we can begin to build this critical foundation together.


UW Data Science for Social Good

Sarah Stone, University of Washington and Anissa Tanweer, University of Washington; Wednesday April 3, 2019 1:45 PM

UW Data Science for Social Good program

Sarah A Stone

Version: 1.0

The UW Data Science for Social Good (DSSG) program partners eScience Data Scientists and Student Fellows from across the country with Project Leads from academia, government, and the private sector to find data-driven solutions to societal challenges.
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Launched in Summer 2015, the UW Data Science for Social Good (DSSG) program partners eScience Data Scientists and Student Fellows from across the country with Project Leads from academia, government, and the private sector to find data-driven solutions to pressing societal challenges. Previous projects (15 over the past 4 summers) have involved data analysis and visualization on topics such as transportation, public health, sustainable urban planning, homelessness, and disaster response. Several projects have led to long-term collaborations and funding opportunities. Integrated project-based discussions and training around data science ethics, human-centered design and stakeholder collaboration are keystones of our DSSG program. Differences in prior experience and training among student fellows can pose a challenge, but often become a strength in the context of project work. Our experience running this program supports the notion that DSSG programs can both effectively impact social good and provide "real world" data science training for students from diverse disciplinary backgrounds.


Asset Mapping: A Simple Tool for Recruiting and Retaining Underrepresented Populations in STEM

Adrienne Smith, Cynosure Consulting and Rebecca Zulli Lowe, Cynosure Consulting; Wednesday April 3, 2019 1:50 PM 

Asset maps serve as a simple, yet impactful tool for helping underrepresented groups connect with important people, programs, and resources that would support their recruitment and retention in STEM. In contrast to a traditional deficit-focused mindset, asset mapping was born out of an approach that seeks out existing strengths and works to build capacity by leveraging current resources as a foundation for further innovation. At the end of this talk, individuals will walk away with a list of steps that they can use to develop a comprehensive map that could be distributed immediately to current and future STEM (including high school seniors). These steps include identifying current assets within an array of existing categories (e.g., tutoring centers, individual faculty mentors, local chapters of STEM associations) designed to help mappers think expansively about existing supports. Additional steps involve reviewing contact lists and asking others to assist in the identification of assets, performing internet searches of the school/organization website looking for key words, and reading through the university directory to highlight offices that work on diversity issues or support the individuals targeted. The assets can be plotted directly onto a campus map and supplied to underrepresented groups, so they are aware of and can locate the resources and supports available to them. Additionally, the formation of the maps can be a beneficial exercise for departments to use to assess their own assets and strategically plan for the development of new assets.


Possibility or Pitfall: Looking at Emerging Tech and Inaccessibility

Urooj Raja, University of Colorado-Boulder; Wednesday April 3, 2019 1:55 PM 

This presentation was not live streamed or recorded. 

Emerging technologies are proliferating at a rapid pace. Scholars use the broad term emerging technologies as a catchall phrase to describe those technologies that show massive innovative potential, can be rapidly absorbed into the market place, and have the power to disrupt the status quo. Artificial intelligence, nanotechnology, robotics, and virtual reality are all examples of emerging technology. A byproduct of emerging technologies is emerging inequality, for example, advances in automation will cut down the need for blue collar workers, whereas educational advances in artificial intelligence will help the most affluent school districts that have the ability to pay for the expensive tech retain the technology. It also remains that despite the pervasive use of emerging tech, scholars have been slow to investigate the social implications of these technologies. For example, little research considers the racial, gender, institutional and class disparity effects of emerging technology. Of the handful of studies that do consider these effects, many researchers study these impacts in isolation, and subsequently do not understand the intersecting nature of these disparities. Nonetheless, it remains that emerging technology is going to exert a momentous impact on how society is and will be shaped in the years to come. In this backdrop, it is essential that scholars discuss new ideas on how we can study the resultant inequity impacts of emerging tech on society. The ultimate goal of this presentation is to provide a snapshot of these new directions to the study of emerging tech and inequality, and perhaps more ambitiously to discuss how we can bring this issue to the consciousness of others. Questions to consider: How do we consider the benefits and potential pitfalls of emergent tech across disciplines and methodologies? What roles and responsibilities do scholars have in studying emerging tech? How does emerging tech magnify the already preexisting biases in our society? Is emerging tech making our society more or less unequal, what are the implications of such an occurrence?


Storytelling: a restorative practice and identity building tool for youth

Kirsten Rowell, University of Colorado-Boulder and Carolyn Finney, Independent Scholar; Thursday April 4, 2019 9:15 AM

This presentation was not live streamed or recorded. 

The stories of environmental stewardship that have been historically championed in the U.S. have been woefully exclusive and homogenous - not very representative of national demographics. The impact and efficacy of environmental work is severely limited when communities don’t see themselves in language, curriculum, and media related to environmental work. Recruiting, retaining and enabling future professionals from across the many communities that represent the U.S. will require multiple approaches and restorative work within the environmental field, curriculum, and programming. We use storytelling as a tool for building identity within the field, a restorative and empowering practice, and even a learning tool for those stuck in normative culture. Through this process, a new generation of environmental professionals form their own authentic connections to the environment, built the intercultural trust necessary to talk across differences, and challenged our understanding of the boundaries in the field of conservation.


Make student thought process visible using video recording

Hong Qin, University of Tennessee at Chattanooga; Thursday April 4, 2019 9:20 AM

The author will present his experience of integrate screen-recording to enhance student learning experience of computational biology. Students were required to screen-recording their process of solving computational problems. These screen-recordings can be used to identify the learning hurdles of students and improve student learning experiences.


Summary of the National Academies Report on Data Science for Undergraduates

Louis Gross, University of Tennessee; Thursday April 4, 2019 9:25 AM

Under the auspices of the National Academies, a Committee developed a consensus report regarding means to enhance undergraduate programs in the emerging discipline of data science.
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Under the auspices of the National Academies, a Committee developed a consensus report regarding means to enhance undergraduate programs in the emerging discipline of data science. Building upon advice from a variety of on-line and in-person interactions with a broad spectrum of experts, the report provides a collection of findings and recommendations for initiating, developing and evaluating programs that prepare students for careers in data science as well as encouraging methods for all undergraduates to be exposed to basic concepts in this field. I will summarize the suggestions made regarding development of data acumen, incorporation of real-world examples, enhancing teamwork and communication, ethical considerations, and assessment and evaluation of data science programs. I will emphasize the potential for such programs to broaden participation in quantitative science and the benefit of utilizing environmental data and examples that align with the interests of diverse students.


Diversity, Inclusion, and Data Science at the National Ecological Observatory Network

Megan Jones, Battelle/NEON; Thursday April 4, 2019 9:30 AM 

NEON, the National Ecological Observatory Network, is an NSF-funded large science facility, operated by Battelle, is designed to collect extensive ecological and environmental data from across the U.S. for the next 30 years. A primary product of NEON is freely available, open access data for use by the scientific research community as well as by students and others who will explore the petabytes of information that will be available during the lifetime of the Observatory. Using NEON data, however, may not be an easy task for researchers, faculty, and students who are not familiar with “big data” access, management and analytic methods. Many ecologists are transitioning to using data science and big data methods including programming-based data management and analysis, complex data portals and APIs that provide access to lots of different types of data, and diverse analytical methods beyond those classically used in their individual research area. Furthermore, ecological data is usually messy in the sense that variability and uncertainty are important components of data analysis and interpretation. Given these challenges, how do we accelerate the use of big data in ecological research and education?  How to we create equitable opportunities for data and resource access to all interested individuals? How do we engage communities that have not traditionally been drawn to careers in ecology but for which data science focused careers may provide new opportunities?


NSF INCLUDES Coordination Hub

Gary Silverstein, Westat and Coordination Hub Team; Thursday April 4, 2019 9:35 AM