[CODATA-international] Fwd: [ESSI] AGU 2018 Call for abstracts: Software, Machine Learning, PIDs, Data Publication
Simon Hodson, ED CODATA
simon at codata.org
Thu Jul 5 09:14:45 EDT 2018
Some very interesting sessions at AGU (Washingon DC, 10-14 December 2018) are calling for abstracts. Descriptions and links below. Deadline for abstracts is 1 August.
Call for CODATA Task Groups 2018-2020: Deadline 18 July. <http://www.codata.org/events/general-assembly/general-assembly-2018/call-for-task-groups-2018-2020>
Turning FAIR Data into Reality - EC Expert Group Report and Action Plan: consultation and feedback until 5 August <http://www.codata.org/news/254/62/Turning-FAIR-Data-into-Reality-Report-and-Action-Plan-Consultation-until-5-August>
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> Begin forwarded message:
> From: <Jens.Klump at csiro.au>
> Subject: [ESSI] AGU 2018 Call for abstracts: Software, Machine Learning, PIDs, Data Publication
> Date: 4 July 2018 at 03:34:45 CEST
> To: <gis-user at gfz-potsdam.de>, <forschungsdaten at listserv.dfn.de>, <agu-essi at googlegroups.com>, <earth-space-science-informatics at lists.nasa.gov>, <software-source-code-ig at rda-groups.org>, <agu-ossi at googlegroups.com>, <wiss-software at listserv.dfn.de>
> [Apologies for cross-posting]
> Dear Colleagues,
> The deadline for abstracts to the AGU Fall Meeting 2018 in Washington, DC, is coming up in the not too distant future (1 August 2018, 23.59 EDT). AGU Earth and Space Science Informatics has, again, proposed some exciting sessions and is now calling for abstract submissions. I would like to draw your attention to the following sessions:
> Machine Learning and Big Data
> IN023: Data-intensive Analytical Workflows for Scalable Earth System Science
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/50958 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/50958>
> In the geosciences, we are facing an explosion of data volumes from datasets, models, in-situ observations, and remote sensing platforms. Data-intensive scientific workflows are at a pivotal time as the resulting data volumes are beyond the scale of desktop computers and workstations, storage and bandwidth. In addition to limitations set by commonly available hardware, there is a growing recognition that the fragmentation of software tools and environments renders most geoscientific research effectively unreproducible. How can researchers utilise the unprecedented volume of data with metadata-aware analysis tools to answer tomorrow's data-intensive questions? This session will demonstrate state-of-the-art approaches to gigabyte- through petabyte-scale data analysis, and explore growing ecosystems for developing scalable and extensible workflows.
> T023: Geospatial Artificial Intelligence: Machine Learning in Earth Sciences
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/50531 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/50531>
> Amount and variety of data created in the process of measuring and modelling Earth’s sub-systems is drastically increasing with ever-improving computational and data acquisition capabilities. Gaining insight into a wide array of Earth processes from diverse data sources that are vast in size and variety requires new methods. Machine learning (ML) methods have enabled the analysis of big data in geosciences that would not have been possible otherwise, and have allowed new insights from data used in traditional analysis. The ability to integrate big data into scientific workflows and emerging new ML methods has opened new avenues of research and may fill in the gaps where traditional approaches fall short.
> Software and Tools
> IN053: Opening the Black Box: Open Software, Open Hardware, Open Formats
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/52681 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/52681>
> The Free and Open Source Software (FOSS) paradigm has changed the way we develop and use software. Whole industries are now founded on using FOSS. However, it is only one aspect of applying informatics in geoscience research. Steep declines in the prices for manufacturing by 3D printing, bespoke electronic and sensor components, compute resources, and open source machine learning frameworks have pushed the boundaries of “open” further. Interoperability and reuse of software also depend on open formats and open data. Progress in machine learning will depend on open training datasets. This session invites contributions describing projects that leverage FOSS, open formats, open data, or open hardware to advance the earth and space sciences.
> NS004: A tour of open-source software packages for the geosciences
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/51989 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/51989>
> This session will be a rapid-fire tour of open source tools freely available for researchers in the geosciences. The fast-growing open-source software ecosystem is creating new tools and changing paradigms for how computers and collaborations are used to study Earth processes. If you have written open-source software that could be useful to others, we look forward to seeing your submission. This session will not only be an opportunity to showcase your own packages and learn about other available tools, we also hope it will be an opportunity to connect with others working on related problems and lead to new collaborations. The session will be accompanied by posters where the audience can engage individually with the presenters.
> IN002: Achieving FAIR and Sustainable Software: What are the Current Trends?
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/52761 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/52761>
> Software source code is an integral part of modern research and has many roles: it inevitably generates new research outputs but is used in cleaning, processing and visualising data. It is an increasingly important input to scientific publications and needs to be sustainably accessible to evaluate the quality of published research and to enable reproducibility and reusability. Software source code, like data, needs to be Findable, Accessible, Interoperable and Reusable (FAIR): it also needs to be properly versioned, curated and archived to ensure research outcomes can be validated. Both developers and organisations that support software development need to participate, and their contributions should be properly credited and attributed.
> Data Publication
> IN055: Persistent Identifiers Demystified: Increase the Impact and Reach of Your Research
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/52728 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/52728>
> Persistent Identifiers have become important elements of the infrastructure of science communication and information management. Most stakeholders are familiar with Digital Object Identifiers (DOI), but what about ORCID, IGSN, and other Identifiers? What are Handles and Cool URLs? How can they be used? Who provides them? What problems are they supposed to address, and what are their long-term benefits going to be - to researchers, funders, and institutions? This session invites contributions on the use of Persistent Identifiers, their role in the scientific communications universe, and new emerging applications. We are keen to hear from active researchers, repository managers, PID minting organisations, funders, publishers and tool makers.
> IN059: Tools, Recommended Practices and Workflows for Data Publication to Help Researchers
> https://agu.confex.com/agu/fm18/prelim.cgi/Session/52284 <https://agu.confex.com/agu/fm18/prelim.cgi/Session/52284>
> The ability to address global environmental challenges requires availability, rich metadata and efficient sharing of data. Reproducibility and trust in transdisciplinary, stakeholder-driven science build upon this. Hence government mandates require that data be made available to the broader community; funders require data management plans; journals require that data and other digital research outputs be citable; and society increasingly expects that research be reproducible. Data publication enables researchers to share their data and other research products with the scientific community, benefitting from their re-use by others. Yet navigating the process of data publication can be onerous and time-consuming. Increasingly, tools, good practices and workflows are emerging, as community initiatives or through commercial responses to perceived demand, that support the collection, preparation and publication of research data. This session invites contributions from developers, funders, policy makers and active researchers with a view to raising awareness, increasing usage, and facilitating further collaborations.
> Carrot: You may be eligible to win a $100.00 USD gift card by submitting your abstract early: 25 July 2018, 11:59 P.M. EDT.
> Please take note of AGU’s author policy: https://fallmeeting.agu.org/2018/abstract-submissions/author-policy/ <https://fallmeeting.agu.org/2018/abstract-submissions/author-policy/>
> First authors can have a maximum of one (1) contributed and one (1) invited abstract or two (2) invited abstracts. The only exemption to this policy is the submission of one (1) additional contributed abstract to a GeoHealth (GH), Education (ED) or Public Affairs (PA) session.
> The first author, including invited authors, MUST be an AGU member. Coauthors or presenting authors who are different than the first author are not required to be an AGU member.
> Looking forward to seeing you at the AGU Fall Meeting 2018 in Washington, DC.
> Jens Klump
> Dr Jens Klump
> Science Leader Earth Science Informatics
> Geoscience Analytics Team Leader
> Mineral Resources
> E jens.klump at csiro.au <mailto:jens.klump at csiro.au> T +61 8 6436 8828
> CSIRO ARRC, 26 Dick Perry Avenue, Kensington, WA 6151, Australia
> www.csiro.au <http://www.csiro.au/>
> http://ORCID.org/0000-0001-5911-6022 <http://orcid.org/0000-0001-5911-6022>
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