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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.