2012 AGU ESSI Session Ideas
This wiki is intended to help the AGU Earth and Space Science Informatics (ESSI) Focus Group collaborate on themes and topics for the December 2012 AGU Fall Meeting. Please be sure to submit your session proposals to the official AGU Fall Meeting Session Proposal Site by the April 20, 2012 deadline. Additional information on submission policies and guidelines can be found here. Recent session titles and statistics from past AGU Informatics sessions can be found here. (add link to child page with the text below)
How to add content: To contribute to an idea to this page, login or request an account. Once logged in, on this page copy the session template below and click the edit tab. Paste the template into the wiki text box and then fill out the requested information.
=== Replace with Suggested Session Title=== * Description: * Name/Contact: * Others interested in similar session? If you are interested in co-convening or support this session add your name here.
Earth and Space Science Informatics General Contributions
- Description: Each AGU section and focus group has a general purpose session where members can submit abstracts when their work does not appear to fit in the other session topics.
- Name/Contact: Karen Moe/[email protected]
- Others interested in similar session?
Environmental Sensor networks and informatics
- Description: sensor network innovations and deployments plus closely related informatics
- Contacts: Kirk Martinez, Jane Hart, Steve Foley
Linked Data for Earth and space science
- Description: The interdisciplinary nature of science is leading to an increasing need to integrate data from multiple sources. Linked Data is a methodology that addresses this problem and one that is becoming increasing popular within the Earth and space sciences. This session aims to discuss the range of research approaches leveraging Linked Data. Submissions are encouraged in, but not limited to:
- Outcomes of using Linked Data within the Earth and space sciences
- Discussions of open source tools that aid/facilitate Linked Data
- Reusable scientific vocabularies
- Methods for computing similarity across linked data sets
- Entity Disambiguation
- User Interfaces/User interactions with Linked Data
- Contacts: Tom Narock ([email protected]), Eric Rozell ([email protected])
Data and Service Brokering: mediating interactions across diverse resources in network-based systems
- Description: Papers will be solicited that describe implementations of the brokering architectural style in which brokering services (mediation, services composition, distribution, etc.) facilitate the interconnection of clients and servers without the need for modifications on the part of the owners of those services.
- Name/Contact: SiriJodha Khalsa ([email protected]), Stefano Nativi, Jay Pearlman
- Others interested in similar session? If you are interested in co-convening or support this session add your name here.
Knowledge Networks and Collaborative Platforms in the Earth Sciences
- Description: Increasingly interdisciplinary Earth science research requires infrastructures that can support knowledge integration on larger scales. This session will discuss novel use or case studies of cyberinfrastructure to facilitate collaboration, community building, governance, or knowledge sharing. Examples of possible submissions include:
- Hubs or forges for Earth science software development, particularly if they integrate multiple projects
- Knowledge sharing platforms deploying social networking tools
- Portals designed to promote community participation in integrating models, data, or knowledge
- Name/Contact: Sylvia Murphy ([email protected]), Paul Edwards ([email protected])
- Others interested in similar session?
Data Prospecting, Exploration and Mining – “big data” exploitation challenges and applications in Earth Science
There are typically two categories of data analysis, namely, data exploration and data mining. Data exploration focuses on manual methods brought to bear on data analysis such as standard statistical analysis and visualization. Data exploration usually requires small datasets. Data mining, on the other hand, is defined as "the nontrivial extraction of implicit, previously unknown, and potentially useful information from data" (Fayyad et al, 2008). Data Mining uses automated algorithms to extract useful information. Humans guide these automated algorithms and specify algorithm parameters (training samples, clustering size, etc.). Large datasets typically require data mining.
A new approach for exploiting "big data" is now possible with the availability of high performance computing and the advent of new techniques for efficient distributed file access. This new approach coined as “data prospecting” combines methods from both data exploration and mining. Just as prospecting focuses on locating the site within the vast land and determining the type of deposit that is located at that site. Data prospecting focuses on finding the right subset of data amongst all the data files and determining the value of the information contained within the subset. Papers on Web-initiated high-volume computational intensive data analysis capabilities on distributed peta-scale data archives extracting information at the source are also being sought. Such papers may include non-linear dynamics in search of signals within climate archives.
This session invites talks focusing on applications and challenges of exploiting “big data” using different data exploration, prospecting and mining approaches. Talks on tools addressing any of these topics are also welcome.
NASA Open Source Summit for Science Data Systems
The consumption and production of open source software (OSS) is a widespread meme in the science data systems domain. These systems are long-lived, and are responsible for collecting, processing, distributing, discovering, reusing, and preserving scientific data. Open source components and software help NASA construct these systems at low-cost, and at low-risk, for Earth science, planetary science, astronomy and a number of other scientific domains. There are many opportunities for fostering broader community support, for exchanging ideas, and for collaboratively developing the next generation of science data systems in the open source domain. In this proposed session, we encourage reports of case studies, lessons learned, theories, experiences, challenges, and related topics in the development and use of OSS for scientific data systems. This session builds on last year’s widely successful oral AGU session IN30: Software Reuse and Open Source Software in Earth Science.
Name/Contacts - Chris A. Mattmann and Robert R. Downs
Data Scientists Come of Age
A continuation of "Rise of the Data Scientist" from 2011.
Many earth scientists are adapting their skills to effectively manage and curate complex digital data. Such skills are becoming the domain of data professionals, but such people rarely have an understanding of some special needs of earth science data. They are data scientists: people who are both specialists in data management and also have domain expertise on earth science data structures, formats, vocabularies, ontologies, etc. New programs are emerging in universities to develop and train such people. These experts and those connected with them, are now developing formal professional structures to enable sharing of expertise and more importantly gain formal recognition, promotion and stable career paths. We seek contributions from these scientists.
Name - Peter Fox and others welcome
Technology Enabling Earth Science from Big Data to Small Satellites
New technology will play a key role in enabling future Earth-observing missions. We welcome abstracts from scientists and technologists in the areas of satellite systems, advanced data processing and management that utilize information system advances to enable the scientific objectives of the NRC decadal survey for NASA and NOAA. The informatics domain stretches from techniques to capture, store, access, & analyze very large remote sensing data to technology for satellite control & dynamic sensor processing. Areas of interest include autonomy, onboard computing, data mining/fusion/assimilation, software tools & services, OSSE, uncertainty analysis, sensor webs, and community frameworks.
Name/Contacts - Karen Moe, Jacqueline LeMoigne, Charles Norton