2019 ESIP Winter Meeting

Session Abstract:
Researchers, data repositories, publishers, funders, and other stakeholders are increasingly obligated to ensure that data are not only open, but also FAIR - findable, accessible, interoperable, and re-usable. Various initiatives, projects, and working groups are working to advance the implementation of the FAIR principles, among them the AGU project "Enabling FAIR Data", the European GOFAIR initiative, and Working Groups within the RDA and WDS. This efforts are making it increasingly clear that many aspects of FAIRness, specifically reusability, are highly context and domain specific. The original FAIR guiding principles explicitly point to “domain-relevant community standards (R1.3.)”, but there are many open questions regarding such domain-relevant community standards: Who develops and maintains them? Who has the authority to approve them and govern them? How granular do domain-specific standard definitions need to be?
This session is intended to foster a dialog between data repositories, researchers, and other stakeholders to clarify and address the above listed questions for the Earth, Space, and Environmental informatics community.


Agenda:

1. Welcome & Introduction (Kerstin Lehnert)
2. The role of the International Science Unions in endorsing standards for interoperability (Lesley Wyborn)
3. Domain metadata (Ted Habermann)
4. Discussion in breakout groups
5. Synthesis and explore next steps

Session Takeaways (post-meeting):
1) Interoperability and Reusability are driven by community, and conventions are an important part of communities.
2) Interesting analogies with power adapters and rail gauges. As long as I’m within one country, I have a standard and everything works together. It’s only when I cross into other countries that interoperability enters in.

Session Abstract:
Across industries and government, there are many groups working with virtual, augmented, and mixed reality technologies inside and outside of the realm of Earth science. In this dynamic panel, we will hear from scientists and researchers working with VR/AR/MR from various scientific disciplines about their approach to data visualization techniques. Interdisciplinary work and complex data sets will provide interesting perspective to the ongoing exploration of how immersive technologies can be used for Earth science and beyond.

Session Takeaways (post-meeting):
1) Presently, we can see the opportunities for AR/VR. The term “magic moments” is expressed to describe the peaks in using technology like this, where we are fully immersed in the activity we are doing and forget the layer of technology connecting us to the activity.
2) There are many key limitations with this technology, worthy of consideration. Data ingestion pipelines, standardization of data for VR visualization pipelines, hardware limitations (Field of View, physical strain on users), Costs, evaluating how this visualization technique is beneficial
3) Simplicity is a wholly necessary element of UI with VR/AR because input modalities with this technology are very simple as well, like gestures or voice commands. It’s a rich area of research at present and we need to find the basic elements which can be standardized.

Session Abstract:
The majority of scientific programming workflows are developed in isolation by graduate students and postdoctoral researchers. While packages and libraries in R and Python help support the advancement of scientific discovery, researchers are often challenged with combining and analysing data in new ways. Regardless, code use and re-use in the Earth Sciences is often complicated by the fact that few well-developed workflows exist as templates. Most code examples in R packages for example, use well-worn datasets that are not well suited to extrapolation for Earth Science applications. For this reason, the discovery and analysis of existing code resources, such as those undertaken by the FUNding Friday grant, become critical to providing resources to scientific programmers in the Earth Sciences.
This Session will introduce early-career researchers to the principle workflows for sharing code publicly, including discussion of some of the pros and cons of sharing code before it is “good enough”. The session will then provide an overview of work that has been undertaken to analyse a large number of Jupyter notebooks on GitHub, and then provide session members with an opportunity to help build the web of examples for coding resources, discussing what makes code useful as a “cookbook recipe” for Earth Sciences, what particular libraries or data resources are of interest, and how further automation might be undertaken.

Session Notes:
https://docs.google.com/document/d/1S5p4v77B3kCdWSKbxKw3gkPFTotMeS9_pm5ic9rYhak/edit?usp=sharing

Session Takeaways (post-meeting):
1) Cultural knowledge around data use and storage can impact usage and keep data and use in ‘silos.’
2) There are a lot of people now that are putting notebooks on GitHub that are associated with a specific publication. The people that are doing this well are associating the DOI with the original publication and the people doing really well are setting this up so that the repository also has its own DOI.
3) Earth science data cookbook has an easy form to fill out information for earth science datasets and resources. This is intended to make these resources more accessible and clearly labeled. This thing is not live yet, but users can input keywords etc. available at https://bitly.com/esip2019-cookbook