11 Nov 2009IVOA Garching: Apps II1 Crowdsourcing and the VO Matthew J. Graham (Caltech, NVO) et Roy Williams, Andrew Drake, George Djorgovski Ashish Mahabal,

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11 Nov 2009IVOA Garching: Apps II1 Crowdsourcing and the VO Matthew J. Graham (Caltech, NVO) et Roy Williams, Andrew Drake, George Djorgovski Ashish Mahabal, Ciro Donalek T HE US N ATIONAL V IRTUAL O BSERVATORY

Humans as CPUs Unique juncture in history of science: –technological capability exists to network large numbers of people –data volumes and complexity are still desktop manageable –class of problems that are resistant to present machine learning solutions Crowdsourcing/human computation/citizen science projects exploit efforts of volunteers to attack particular areas, e.g. image analysis Axes: –Sweat shop vs. GWAP –Idiot vs. savant 11 Nov 2009IVOA Garching: Apps II2

Tonight a galaxy, tomorrow the Zoo Initial questions: –Are galaxies elliptical or spiral? –If spiral, rotating clockwise or anticlockwise? clicks done by users Main result: –Spiral galaxies which share a neighbourhood (a region defined as 65 million light years across) are likely to rotate in the same direction – but only if they formed the vast majority of their stars more than 10 billion years ago. Other results: –Hannys Voorweerp –Green Peas 11 Nov 2009IVOA Garching: Apps II3

Galaxy Zoo 2 11 Nov 2009IVOA Garching: Apps II4

Things that go BANG! in the night Catalina Real-Time Transient Survey ( –Repeatedly surveys ~26000 deg 2 –3 telescopes: MLS (1.5m), CSS (0.7m), SSS (0.5m) –1067 new discoveries to date –Only completely public transient survey SkyAlert ( –enables users to perform complex queries about discoveries in order to receive personally tailored and filtered event streams. The VO is useful for: –data discovery –semantics –data mining 11 Nov 2009IVOA Garching: Apps II5

Citizen science with CRTS 11 Nov 2009IVOA Garching: Apps II6

AstroCollation - I Next generation collaborative science venture Data mining algorithms applied to transient event data to produce conceptual models describing them Models presented to citizen scientists for value judgements, deciding which of a set of models provides the best description Citizen scientists can also provide contextual information to aid the classification process 11 Nov 2009IVOA Garching: Apps II7

AstroCollation - II Decisions and information factored back into the system and consolidated to produce a consensus description of an event that can always be retrieved (and reused) Produce better (ideal) training sets Built upon semantic technologies, CRTS and SkyAlert Issues to address: –How to formally represent uncertainty in data and description in a machine-processible fashion –Optimal method to achieve consensus opinion 11 Nov 2009IVOA Garching: Apps II8