Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors

Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Galaxy Zoo Green Peas: discovery of a class of compact extremely star-forming galaxies

‘The definitive version is available at www3.interscience.wiley.com '. Copyright Royal Astronomical Society. DOI: 10.1111/j.1365-2966.2009.15383.xWe investigate a class of rapidly growing emission line galaxies, known as 'Green Peas', first noted by volunteers in the Galaxy Zoo project because of their peculiar bright green colour and small size, unresolved in Sloan Digital Sky Survey imaging. Their appearance is due to very strong optical emission lines, namely [O iii]λ5007 Å, with an unusually large equivalent width of up to ∼1000 Å. We discuss a well-defined sample of 251 colour-selected objects, most of which are strongly star forming, although there are some active galactic nuclei interlopers including eight newly discovered narrow-line Seyfert 1 galaxies. The star-forming Peas are low-mass galaxies (M∼ 108.5–1010 M⊙) with high star formation rates (∼10 M⊙ yr−1) , low metallicities (log[O/H]+ 12 ∼ 8.7) and low reddening [ E(B−V) ≤ 0.25 ] and they reside in low-density environments. They have some of the highest specific star formation rates (up to ∼10−8 yr−1 ) seen in the local Universe, yielding doubling times for their stellar mass of hundreds of Myr. The few star-forming Peas with Hubble Space Telescope imaging appear to have several clumps of bright star-forming regions and low surface density features that may indicate recent or ongoing mergers. The Peas are similar in size, mass, luminosity and metallicity to luminous blue compact galaxies. They are also similar to high-redshift ultraviolet-luminous galaxies, e.g. Lyman-break galaxies and Lyα emitters, and therefore provide a local laboratory with which to study the extreme star formation processes that occur in high-redshift galaxies. Studying starbursting galaxies as a function of redshift is essential to understanding the build up of stellar mass in the Universe.Peer reviewe

Galaxy Zoo : Building the low-mass end of the red sequence with local post-starburst galaxies

We present a study of local post-starburst galaxies (PSGs) using the photometric and spectroscopic observations from the Sloan Digital Sky Survey and the results from the Galaxy Zoo project. We find that the majority of our local PSG population have neither early- nor late-type morphologies but occupy a well-defined space within the colour-stellar mass diagram, most notably, the low-mass end of the 'green valley' below the transition mass thought to be the mass division between low-mass star-forming galaxies and high-mass passively evolving bulge-dominated galaxies. Our analysis suggests that it is likely that local PSGs will quickly transform into 'red', low-mass early-type galaxies as the stellar morphologies of the 'green' PSGs largely resemble that of the early-type galaxies within the same mass range. We propose that the current population of PSGs represents a population of galaxies which is rapidly transitioning between the star-forming and the passively evolving phases. Subsequently, these PSGs will contribute towards the build-up of the low-mass end of the 'red sequence' once the current population of young stars fade and stars are no longer being formed. These results are consistent with the idea of 'downsizing' where the build-up of smaller galaxies occurs at later epochs.Peer reviewe

The Revolution in Astronomy Education: Data Science for the Masses

As our capacity to study ever-expanding domains of our science has increased (including the time domain, non-electromagnetic phenomena, magnetized plasmas, and numerous sky surveys in multiple wavebands with broad spatial coverage and unprecedented depths), so have the horizons of our understanding of the Universe been similarly expanding. This expansion is coupled to the exponential data deluge from multiple sky surveys, which have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into Petabytes (even hundreds of Petabytes) in the next decade. With this increased vastness of information, there is a growing gap between our awareness of that information and our understanding of it. Training the next generation in the fine art of deriving intelligent understanding from data is needed for the success of sciences, communities, projects, agencies, businesses, and economies. This is true for both specialists (scientists) and non-specialists (everyone else: the public, educators and students, workforce). Specialists must learn and apply new data science research techniques in order to advance our understanding of the Universe. Non-specialists require information literacy skills as productive members of the 21st century workforce, integrating foundational skills for lifelong learning in a world increasingly dominated by data. We address the impact of the emerging discipline of data science on astronomy education within two contexts: formal education and lifelong learners.Comment: 12 pages total: 1 cover page, 1 page of co-signers, plus 10 pages, State of the Profession Position Paper submitted to the Astro2010 Decadal Survey (March 2009

Galaxy Zoo: Disentangling the Environmental Dependence of Morphology and Colour

We analyze the environmental dependence of galaxy morphology and colour with two-point clustering statistics, using data from the Galaxy Zoo, the largest sample of visually classified morphologies yet compiled, extracted from the Sloan Digital Sky Survey. We present two-point correlation functions of spiral and early-type galaxies, and we quantify the correlation between morphology and environment with marked correlation functions. These yield clear and precise environmental trends across a wide range of scales, analogous to similar measurements with galaxy colours, indicating that the Galaxy Zoo classifications themselves are very precise. We measure morphology marked correlation functions at fixed colour and find that they are relatively weak, with the only residual correlation being that of red galaxies at small scales, indicating a morphology gradient within haloes for red galaxies. At fixed morphology, we find that the environmental dependence of colour remains strong, and these correlations remain for fixed morphology \textit{and} luminosity. An implication of this is that much of the morphology--density relation is due to the relation between colour and density. Our results also have implications for galaxy evolution: the morphological transformation of galaxies is usually accompanied by a colour transformation, but not necessarily vice versa. A spiral galaxy may move onto the red sequence of the colour-magnitude diagram without quickly becoming an early-type. We analyze the significant population of red spiral galaxies, and present evidence that they tend to be located in moderately dense environments and are often satellite galaxies in the outskirts of haloes. Finally, we combine our results to argue that central and satellite galaxies tend to follow different evolutionary paths.Comment: 19 pages, 18 figures. Accepted for publication in MNRA

Limitations of Majority Agreement in Crowdsourced Image Interpretation

Crowdsourcing can efficiently complete tasks that are difficult to automate, but the quality of crowdsourced data is tricky to evaluate. Algorithms to grade volunteer work often assume that all tasks are similarly difficult, an assumption that is frequently false. We use a cropland identification game with over 2,600 participants and 165,000 unique tasks to investigate how best to evaluate the difficulty of crowdsourced tasks and to what extent this is possible based on volunteer responses alone. Inter-volunteer agreement exceeded 90% for about 80% of the images and was negatively correlated with volunteer-expressed uncertainty about image classification. A total of 343 relatively difficult images were independently classified as cropland, non-cropland or impossible by two experts. The experts disagreed weakly (one said impossible while the other rated as cropland or non-cropland) on 27% of the images, but disagreed strongly (cropland vs. non-cropland) on only 7%. Inter-volunteer disagreement increased significantly with inter-expert disagreement. While volunteers agreed with expert classifications for most images, over 20% would have been mis-categorized if only the volunteers’ majority vote was used. We end with a series of recommendations for managing the challenges posed by heterogeneous tasks in crowdsourcing campaigns

Galaxy Zoo: Motivations of Citizen Scientists

Citizen science, in which volunteers work with professional scientists to conduct research, is expanding due to large online datasets. To plan projects, it is important to understand volunteers' motivations for participating. This paper analyzes results from an online survey of nearly 11,000 volunteers in Galaxy Zoo, an astronomy citizen science project. Results show that volunteers' primary motivation is a desire to contribute to scientific research. We encourage other citizen science projects to study the motivations of their volunteers, to see whether and how these results may be generalized to inform the field of citizen science.Comment: 41 pages, including 6 figures and one appendix. In press at Astronomy Education Revie

Supporting citizen inquiry: an investigation of Moon rock

Citizen inquiry is an innovative way for non-professionals to engage in practical scientific activities, in which they take the role of self-regulated scientists in informal learning contexts. This type of activity has similarities to inquiry-based learning and to citizen science, but also important differences. To understand the challenges of supporting citizen inquiry, a prototype system and activity has been developed: the Moon Rock Explorer. Based on the nQuire Toolkit, this offers people without geology expertise an open investigation into authentic specimens of Moon rock, using a Virtual Microscope. The Moon Rock Explorer inquiry has been evaluated in an informal learning context with PhD students from the Open University. Results of the evaluation raise issues related to motivation and interaction between inquiry participants. They also provide evidence that the integration of scientific tools was successful and that the nQuire Toolkit is suitable to deploy and enact citizen inquiries

Galaxy Zoo: Exploring the Motivations of Citizen Science Volunteers

The Galaxy Zoo citizen science website invites anyone with an Internet connection to participate in research by classifying galaxies from the Sloan Digital Sky Survey. As of April 2009, more than 200,000 volunteers had made more than 100 million galaxy classifications. In this paper, we present results of a pilot study into the motivations and demographics of Galaxy Zoo volunteers, and define a technique to determine motivations from free responses that can be used in larger multiple-choice surveys with similar populations. Our categories form the basis for a future survey, with the goal of determining the prevalence of each motivation.Comment: 15 pages, 3 figure