Letters of Intent for 2015
Citizen Science, Social Machines and Open Science in Astronomy
||3 August 2015 to 14 August 2015
||An IAU GA 2015 Symposium, United Kingdom
||Robert Simpson (firstname.lastname@example.org)
||Division B Facilities, Technologies and Data Science
Co-Chairs of SOC:
||Robert Simpson (University of Oxford)
|Karen Masters (University of Portsmouth)|
Chair of LOC:
Existing citizen science projects: lessons learned, successes and failures for research. Citizen science and machine learning. Human computer interactions. Platforms for enabling online research in astronomy.
We propose a symposium to gather the world’s leaders in astronomical citizen science to share results, research methodology and discuss ways forward for this growing field of inquiry.
Citizen Science is a growing area of interest across the many research disciplines which are dealing with big data, and astronomy is a leader in this emerging way of doing research. Through projects such as Stardust at Home , Galaxy Zoo  and Planet Hunters , the public have been able to contribute and participate in astronomical research over the internet for almost a decade.
Public participation in astronomy is not new, but modern web browsers and the rise in the number of connected devices have changed the scope of what is possible through crowdsourcing and volunteer activity. These advances have allowed the creation of engaging interfaces that allow anyone to not just view a plethora of astronomical data and imagery, but also to annotate it, providing valuable source of additional data for researchers. There are now large-scale programmes to coordinate star-counts, meteor observations, and other kinds of citizen data collection that can help further astronomy.
Citizen science has never been just simple public outreach, but rather represents a way to conduct outreach, education and cutting-edge research all at once. The Zooniverse platform  alone (e.g. Galaxy Zoo, the Milky Way Project) has more than 55 peer-reviewed research papers directly resulting from it’s growing array of online citizen science projects in astronomy .
Citizen science is an excellent approach to many of the issues created by so-called ‘Big Data’. Projects like the SKA, LSST, Euclid and JWST will all create enormous stores of data. To bring the public into the process of processing and exploring these datasets is already being discussed within various consortia around the world.
Citizen science is also an avenue into advancing Machine Learning techniques in astronomy. The vast datasets of human classifications created by online projects can inform machine learning code, for example data from the Milky Way Project  is being used to inform machine identification of HII regions in Spitzer data ; and Galaxy Zoo: Supernova enabled such accurate automated identification of candidate supernovae as to make the citizen science project obsolte .
Online technologies continue to advance, as do ideas about Open Science. Tools are in development today that may enable not just true, open collaboration between researchers online - e.g. group LaTeX-writing tools like Authorea  - but also the potential of astronomical research in a web browser - e.g. AstroJS, which allows FITS files to be opened and manipulated online . We propose to bring together the creators of these new, open tools, along with the astronomers that may eventually adopt them them - or perhaps who will argue that they will never do so.
Citizen science has shown that is a reliable platform for productive astronomy. Publications resulting directly and indirectly from crowdsourced work by the public are increasingly frequent and the tools for undertaking such large-scale experiments are becoming better understood and further developed. 2015 feels like the perfect time for an IAU symposium on Citizen Science in Astronomy.
 Lintott, Schawinski, Bamford, et al. 2011, MNRAS, 410, 166; http://www.galaxyzoo.org
 Fischer, Schwamb, Schawinski, et al. 2012, MNRAS, 419, 2900; http://www.planethunters.org
 Simpson, Povich, Kendrew et al. 2012, MNRAS, 424, 2442; http://www.milkywayproject.org
 Beautmont, C., et al, 2013 (in prep.)
 Smith, Lynn, Sullivan, et al. 2011, MNRAS, 412, 1309