Scalable and Computationally Reproducible Approaches to Arctic Research
Dates: March 25-29, 2024
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. This includes working in cloud computing environments, docker containers, and parallel processing using tools like parsl and dask. The workshop will also cover concrete methods for documenting and uploading data to the Arctic Data Center, advanced approaches to tracking data provenance, responsible research and data management practices including data sovereignty and the CARE principles, and ethical concerns with data-intensive modeling and analysis.
Reproducible Practices for Arctic Research Using R
Dates: February 26 - March 1, 2024
Location: Online
This 5-day remote workshop will provided researchers with an overview of best data management practices, data science tools for cleaning and analyzing data, and concrete steps and methods for more easily documenting and preserving their data at the Arctic Data Center. Example tools included R, Rmarkdown, and git/GitHub. This course provided background in both the theory and practice of reproducible research, spanning all portions of the research life cycle, from ethical data collection following the CARE principles to engage with local stakeholders, to data publishing.
Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
Dates: January 22 - 26, 2024
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an overview of reproducible and ethical research practices, steps and methods for more easily documenting and preserving their data at the Arctic Data Center, and an introduction to programming in R. Special attention will be paid to qualitative data management, including practices working with sensitive data. Example datasets will draw from natural and social sciences, and methods for conducting reproducible research will be discussed in the context of both qualitative and quantitative data.
NCEAS Learning Hub coreR Course
Dates: October 2-6, 2023
Location: NCEAS Venue: Santa Barbara, CA
Previously called the Reproducible Research Techniques for Synthesis course
A five-day immersion in R programming for environmental data science. Researchers will gain experience with essential data science tools and best practices to increase their capacity as collaborators, reproducible coders, and open scientists. This course is taught both in-person and virtually.
Materials Link to course book
Instructors Name Email Halina Do-Linh dolinh@nceas.
NCEAS openS for the USGS Climate Adaptation Postdoctoral (CAP) Fellows: Future of Aquatic Flows Cohort
Dates: August 21-23, 2023 Location: NCEAS Venue: Santa Barbara, CA
openS was previously called Open Science for Synthesis (OSS)
The NCEAS openS Program consists of three 1-week long workshops, geared towards early career researchers. Participants engage in a mix of lectures, exercises, and synthesis research activities to conduct synthesis science and implement best practices in open data science.
openS has been adapted to coincide with each USGS CAP training, for a total of four training sessions across 2 years.
Open Science Synthesis for the Delta Science Program
In collaboration with the Delta Science Program, we are running a 12-month facilitated research synthesis activity, supported by 3 one-week intensive training events. Curriculum material will focus on introducing Delta Researchers to best practices in, and application of, scientific computing and scientific software for reproducible science. In addition to developing and delivering learning curriculum, this collaboration will include the provision of data consulting, synthesis facilitation, and a remote workshop to conclude the group synthesis activities.
NCEAS Learning Hub coreR Course
Dates: April 3-7, 2023
Location: NCEAS Venue: Santa Barbara, CA
Previously called the Reproducible Research Techniques for Synthesis course
A five-day immersion in R programming for environmental data science. Researchers will gain experience with essential data science tools and best practices to increase their capacity as collaborators, reproducible coders, and open scientists. This course is taught both in-person and virtually.
Materials Link to course book
Instructors Name Email Halina Do-Linh dolinh@nceas.
Scalable and Computationally Reproducible Approaches to Arctic Research
Dates: March 27-31, 2023
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. This includes working in cloud computing environments, docker containers, and parallel processing using tools like parsl and dask. The workshop will also cover concrete methods for documenting and uploading data to the Arctic Data Center, advanced approaches to tracking data provenance, responsible research and data management practices including data sovereignty and the CARE principles, and ethical concerns with data-intensive modeling and analysis.
Reproducible Practices for Arctic Research Using R
Dates: February 27 - March 3, 2023
Location: Online
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara
This 5-day remote workshop will provided researchers with an overview of best data management practices, data science tools for cleaning and analyzing data, and concrete steps and methods for more easily documenting and preserving their data at the Arctic Data Center. Example tools included R, Rmarkdown, and git/GitHub. This course provided background in both the theory and practice of reproducible research, spanning all portions of the research lifecycle, from ethical data collection following the CARE principles to engage with local stakeholders, to data publishing.
Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
Dates: January 30 - February 3, 2023
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an overview of reproducible and ethical research practices, steps and methods for more easily documenting and preserving their data at the Arctic Data Center, and an introduction to programming in R. Special attention will be paid to qualitative data management, including practices working with sensitive data. Example datasets will draw from natural and social sciences, and methods for conducting reproducible research will be discussed in the context of both qualitative and quantitative data.
Scalable and Computationally Reproducible Approaches to Arctic Research
Dates: September 19 - 23, 2022
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. This includes working in cloud computing environments, docker containers, and parallel processing using tools like parsl and dask. The workshop will also cover concrete methods for documenting and uploading data to the Arctic Data Center, advanced approaches to tracking data provenance, responsible research and data management practices including data sovereignty and the CARE principles, and ethical concerns with data-intensive modeling and analysis.
Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
Dates: April 18 - 22, 2022
Location: NCEAS Venue: Santa Barbara, CA
This 5-day in-person workshop will provide researchers with an overview of reproducible and ethical research practices, steps and methods for more easily documenting and preserving their data at the Arctic Data Center, and an introduction to programming in R. Special attention will be paid to qualitative data management, including practices working with sensitive data. Example datasets will draw from natural and social sciences, and methods for conducting reproducible research will be discussed in the context of both qualitative and quantitative data.
Arctic Data Center Training (February 2022)
Dates: February 14 - February 19, 2022
Location: Online
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Open Science: Best Practices, Data Sovereignty and Co-production
Dates: March 29, 2022
Location: Arctic Science Summit Week
Venue: Tromso, Norway
This workshop is a collaboration between the Arctic Data Center, ELOKA and the NNA Community Office, and will focus on the presentation of open science principles and best practices. Open science will be explored from the lens of reproducibility of research, Indigenous data sovereignty, and community data management. A combination of presentation and discussion will introduce participants to key topics, detail current recommended practices and highlight areas for future research.
Reproducible Research Techniques for Synthesis (November 2021)
Dates: November 15-19, 2021
Location: Remote
This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
Curriculum at a glance: Enable data reuse through better data management Metadata - what is it and how to write a quality data description Data modeling - tidy data for efficient access and storage Data publishing, citation, and credit Build reproducible scientific workflows Data munging with R tidyverse Working collaboratively - git and GitHub Writing functions in R Building packages for publishing reproducible research Communicate results effectively Literate analysis with RMarkdown Publishing analytical web pages with GitHub pages Data visualization with ggplot and leaflet For more detailed information on how to prepare for the workshop, see preparing for the workshop (below).
Managing Ecological Data for Effective Use and Re-Use
Friday, August 6th, 2021 10:30 AM - 1:30 PM
Session Description While graduate students in ecology learn about methods for collecting and analyzing ecological data, there is less emphasis on managing and using the resulting data effectively. This is an increasingly important skill set as the research landscape changes. Researchers are increasingly engaging in collaboration across networks, many funding agencies require data management plans, journals are requiring that data and code be accessible, and society is increasingly expecting that research be reproducible.
Open Science Synthesis for the Delta Science Program
In collaboration with the Delta Science Program we are running a 12 month facilitated research synthesis activity, supported by 3 one-week intensive training events. Curriculum material will focus on introducing Delta Researchers to best practices in, and application of, scientific computing and scientific software for reproducible science. In addition to developing and delivering learning curriculum, this collaboration will include the provision of data consulting, synthesis facilitation, and a remote workshop to conclude the group synthesis activities.
Reproducible Research Techniques for Synthesis (July 2021)
Dates: July 8-9, 12-14, 2021
Location: Remote
This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
Reproducible Research Techniques for Synthesis (February 2021)
Dates: February 25-26, March 1-3, 2021
Location: Remote
This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
NEON Onboarding
Dates: December, 2020 Location: Virtual NEON Onboarding A self guided learning curricula to support new NEON postdocs as part of their onboarding experience. The curricula builds from the experience of ecological researchers, trainers, developers and information managers to provide resources and training in support of collaborative, reproducible research practices.
Materials Link to onboarding materials
Reproducible Research Techniques for Synthesis (November 2020)
Dates: November 12 - November 18, 2020
Location: Remote
This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
Arctic Data Center Training (October 2020)
Dates: October 19 - October 23, 2020
Location: Online
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Tools and practices for collaborative, reproducible data science
Dates: May 8, 2020
Location: Remote This module is an introduction to the data science support NCEAS is providing to LTER and SNAPP working groups followed by a discussion on best practices about data management in a distributed team setup. Participants will have the opportunity to brainstorm on their data and computing needs. In the second part of the workshop, an introduction to the use of NCEAS analytical server and the concept of collaborative coding as a distributed team will be demonstrated to empower participants to develop their analytical workflows in a remote setup.
Efficient virtual collaboration & facilitation for synthesis science
Dates: April 24, 2020
Location: Remote This 3-hour module provides mentorship and facilitation training for Working Groups to develop skill sets, habits, and mindsets to make remote work and collaborative synthesis science more efficient and resilient.
Openscapes Champions Workshop with NOAA
Dates: February 26 - February 27, 2020
Location: Woods Hole, Massachusetts. NOAA Northeast Fisheries Science Center. Through in-person Workshops, cohorts of research groups participate over a 2 full days. Workshops are designed to be engaging, requiring active participation through discussion, live-notetaking in Google Docs, and breakout group activities.
Openscapes is operated by the National Center for Ecological Analysis & Synthesis (NCEAS) and is being incubated by a Mozilla Fellowship awarded to Julia Stewart Lowndes.
Data Science and Collaboration Skills for Integrative Conservation Science
Dates: February 18 - February 21, 2020
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara
This intensive 4-day workshop on Data Science and Collaboration Skills for Integrative Conservation Science will be held at NCEAS, Santa Barbara, CA from Feb 18 to Feb 21, 2020.
This training, sponsored by SNAPP, aims to bring together the SNAPP and NCEAS postdoctoral associates to foster communities and collaboration, as well as promote scientific computing and open science best practices.
Reproducible Research Techniques for Synthesis (February 2020)
Dates: February 3 - February 7, 2020
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
Reproducible Research Techniques for Synthesis (November 2019)
Dates: November 4 - November 8, 2019
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara This 5-day workshop will provide researchers with an overview of best data management practices, data science tools, and concrete steps and methods for more easily producing transparent, reproducible workflows. This opportunity is for researchers from across career stages and sectors who want to gain fundamental data science skills that will improve their reproducible research techniques, particularly for the purposes of synthesis science.
Arctic Data Center Training (October 2019)
Dates: October 7 - October 11, 2019
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Arctic Data Center Training (February 2019)
Dates: February 11 - February 15, 2019
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Arctic Data Center Training (January 2019)
Dates: January 14 - January 18, 2019
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Openscapes Champions Cohort sponsored by Mozilla
Dates: January 10 - May 24, 2019
Location: Remote In the Long-term Remote Program, Cohorts of research groups participate over a four-month period, with two Cohort Calls each month. Calls are designed to be engaging, requiring discussion and active participation through live-notetaking in Google Docs and video Zoom (group and breakouts).
Openscapes is operated by the National Center for Ecological Analysis & Synthesis (NCEAS) and is being incubated by a Mozilla Fellowship awarded to Julia Stewart Lowndes.
Arctic Data Center Training (August 2018)
Dates: August 13 - August 17, 2018
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Dataset Publishing with the Arctic Data Center (June 2018)
Dates: June 22, 2018 12:30 to 14:00
Location: Davos, Switzerland
Venue: POLAR 2018 Open Science Conference
This hands-on session will cover (1) Open data archives, especially the Arctic Data Center; (2) What science metadata is and how it can be used; (3) How data and code can be documented and published in open data archives; (4) Web-based submission, and (5) Submission using R (pending sufficient time).
Course overview The Arctic Data Center conducts training in data science and management, both of which are critical skills for stewardship of data, software, and other products of research that are preserved at the Arctic Data Center.
Tools for Data Science in Arctic Research (July 2017)
Dates: July 31 - Aug 1, 2017
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara The Arctic Data Center provides training in data science and data management, as these are critical skills for the stewardship of the data, software, and other research products that are preserved in the Arctic Data Center. A goal of the Arctic Data Center is to advance data archiving and promote reproducible science and data reuse.
Open Science for Synthesis: Gulf Research Program Workshop
Dates: July 10 - July 28, 2017
Location: Santa Barbara, CA
Venue: NCEAS, 735 State St., Suite 300, UC Santa Barbara
The primary goal of the Open Science for Synthesis: Gulf Research Program Workshop is to provide hands-on experience with contemporary open science tools from command line to data to communication. Team science is promoted. Practice and real data are used in groups to apply skills we explore.
Week 1.
NCEAS openS for UCSB Faculty Seminar Series: Grow Your Data & Team Science Skills
Dates: September 11-15, 2023 Location: NCEAS Venue: Santa Barbara, CA
openS was previously called Open Science for Synthesis (OSS)
The NCEAS openS Program consists of three 1-week long workshops, geared towards early career researchers. Participants engage in a mix of lectures, exercises, and synthesis research activities to conduct synthesis science and implement best practices in open data science.
openS has been adapted to coincide with each UCSB Faculty Seminar Series session, for a total of three training sessions across six months.