Data Without Borders ICE 2016: Difference between revisions
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| Preventing Bugs in Data Analysis: Data Skills to Improve the Reliability and Effectiveness of Entomological Research | | Preventing Bugs in Data Analysis: Data Skills to Improve the Reliability and Effectiveness of Entomological Research | ||
::Our increasing capacity to collect data is changing science. This is particularly true as specimen data is being digitized and availability of data is no longer the bottleneck. There is great potential for discovery, but we are primarily failing to translate this sea of data into scientific advances, because researchers are not trained in the skills needed for effective management and analysis. The question then becomes, in addition to scaling data production and computation, how do we develop and deliver training to scale data literate researchers? Course curriculums are slow to change, need qualified instructors and are already full. Short courses are oversubscribed and reach a limited number of participants. To provide scalable and distributed training, Data Carpentry develops and teaches domain-specific hands-on workshops in data organization, management, and analysis. This is a grassroots training effort developed by practitioners for practitioners, who identify core skills and collaboratively develop lessons. All lessons are open source, and workshops are taught by volunteers trained by the Software Carpentry Foundation. With iDigBio, a focus has been on training in the biodiversity community. Workshops are designed for people with little to no prior computational experience and teach in two days how to organize and clean data, manage data in SQL and analyze and visualize data in R – the full data lifecycle. Workshops are in high demand, but this model allows for scaling of training and teaches the foundational skills to get biologists started managing and analyzing their data effectively. | |||
| '''Tracy Teal''' (tkteal@datacarpentry.org), Michigan State University, East Lansing, MI | | '''Tracy Teal''' (tkteal@datacarpentry.org), Michigan State University, East Lansing, MI | ||
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Revision as of 13:11, 11 December 2015
Digitizing the Past and Present for the Future | |
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Quick Links for Data Without Borders ICE 2016 | |
[Agenda] | |
[Biblio] | |
[Report] |
ICE 2016 Symposium Abstract
Summary Statement: Many new and updated methods for collecting biological specimens now result in faster access for everyone to richer, more robust data for research. Scientists are learning new skills for collecting and managing field and lab data using relevant data standards, and publishing enhanced data sets as a result. Best practices for describing data sets with metadata are leading to improved data discovery. Researchers now have access to ever larger data sets for visualization, analysis, and modeling. In our symposium, we present a broad array of examples of the latest developments in biodiversity research using biological specimen data, including genomics, habitat, and trait data. We present current trends in collecting and vouchering of specimens and field data, methods and tools for digitizing the specimen data, and tools and skills needed for visualizing the data. We then highlight how the data are being used, especially for research that expands our understanding of biodiversity. Our Data without Borders session naturally fits the Entomology without Borders theme, addressing the world-wide need for fit-for-research-use data. An underlying theme for Data without Borders is International Collaboration for Biodiversity. In the last ten years, many changes such as powerful hand-held devices, apps, and computing in-the-cloud have made it possible to collect, use, and share data more easily, and in ways that support re-use. Collaboration makes it possible not only to document biodiversity more quickly but also to provide better tools and better data. We will provide examples of this type of collaboration in this symposium.
Short Description
Description: In Data without Borders, we feature talks about collecting museum specimens and digitizing the specimen data to support biodiversity research. Scientists show us how they are using biological specimen data in their research and we include presentations on career skills needed for 21st century digital collections and collaborative research.
time | talk | presenter / authors |
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Specimen Data in Integrated Biodiversity Research | Pamela Soltis (psoltis@flmnh.ufl.edu), University of Florida, Gainesville, FL | |
Cross-pollination in the 21st Century: Integrating entomologists and botanists to explore the island biogeography and conservation of Caribbean orchids | Peter Houlihan (phoulihan@ufl.edu), Florida Museum of Natural History, Gainesville, FL | |
Like blood from that stone we always hear about: a quest to extract meaningful data from historical grasshopper specimens | Derek Woller (asilid@gmail.com) and Hojun Song, Texas A & M University, College Station, TX | |
Acquisition, management, and analysis of historical and contemporary data to discern legacy effects of ecological extinction on insect biodiversity | Robert Kula (Robert.Kula@ars.usda.gov), USDA - ARS, Washington, DC | |
Digitizing natural history collection specimens to investigate the future of species conservation | Jonathan Koch (jonathan.koch@usu.edu), Utah State University, Logan, UT | |
Harnessing specimen data to visualize and investigate the ecology of species | Sarah Schmidt (schmidts@ku.edu), University of Kansas, Lawrence, KS | |
The usefulness of DNA-barcoding databases for routine taxonomic research and identification of Lepidoptera | Andrei Sourakov (asourakov@flmnh.ufl.edu), University of Florida, Gainesville, FL | |
The intersection of data domains underlying insect systematics: case studies in parasitic Hymenoptera
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Norman Johnson (johnson.2@osu.edu), The Ohio State University, Columbus, OH | |
Preventing Bugs in Data Analysis: Data Skills to Improve the Reliability and Effectiveness of Entomological Research
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Tracy Teal (tkteal@datacarpentry.org), Michigan State University, East Lansing, MI | |
Developing Best Practices for Data Management Across all Stages of the Data Life Cycle
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Amber Budden (aebudden@dataone.unm.edu), DataONE, Albuquerque, NM | |
Data capture methodologies in digitisation of bee pollinators
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Nicole Fisher (Nicole.Fisher@csiro.au), Australian National Insect Collection (ANIC), Clayton, Australia | |
Arthropod collection digitization and networking across the New World
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Neil Cobb Northern Arizona University (NAU), Edward Gilbert (egbot@asu.edu), Arizona State University, School of Life Sciences, Tempe, AZ | |
Database before you label – the key to a digitized collections future
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Derek S. Sikes (dssikes@alaska.edu), University of Alaska, Fairbanks, AK | |
Troubleshooting industrial insect digitisation
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Vladimir Blagoderov (vlab@nhm.ac.uk) and Laurence Livermore, The Natural History Museum, Cromwell Road, London, England | |
Bulk samples, is crowd sourced tagging useful in making them more accessible? | Paul Flemons (Paul.Flemons@austmus.gov.au), Atlas of Living Australia DigiVol, Sydney, Australia | |
DAMmed If You Do or Don’t: Life Cycles of Digital Assets
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Lawrence Gall (lawrence.gall@yale.edu), Yale University, New Haven, CT | |
Involving undergraduates in the digital community: Leveraging collections preservation, research, and outreach through a network of natural history collections clubs
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Kari Harris (kari.panhorst@smail.astate.edu), Arkansas State University, Jonesboro, AR |