Worldwide telescope

Submitted
Udomprasert P, Goodman A, Sunbury, S., Zhang ZH, Sadler P, Dussault M, Lotridge, E., Jackson J, Constantin A. Visualizing Three-Dimensional Spatial Relationships in Virtual and Physical Astronomy Environments, in International Conference of the Learning Sciences. Boulder, CO ; Submitted.Abstract

We give a brief overview of some key features of WorldWide Telescope and its Ambassadors Program, and we describe two goals for expanding the program in the coming year: scaling up training efforts; and developing “plug and play” Visualization Lab modules that teach key Earth and Space Science concepts to students while emphasizing important scientific processes and skills. We discuss several different ways that members of the astronomy education and outreach community can incorporate WWT-based materials into their work.

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2014
Udomprasert P, Goodman AA, Sunbury S, Zhang Z, Sadler PM, Dussault ME, Lotridge E, Jackson J, Constantin A. Visualizing Moon Phases in the Classroom with WorldWide Telescope, in American Astronomical Society, AAS Meeting #223. Washington, DC: American Astronomical Society ; 2014. Publisher's VersionAbstract

We report results from an NSF-funded project to build, test, and research the impact of a WorldWide Telescope Visualization Lab (WWT Vizlab), meant to offer learners a deeper physical understanding of the causes of the Moon’s phases and eclipses. The Moon Phases VizLab is designed to promote accurate visualization of the complex, 3-dimensional Earth-Sun-Moon relationships required to understand the Moon’s phases, while also providing opportunities for middle school students to practice critical science skills, like using models, making predictions and observations, and linking them in evidence-based explanations. In the Moon Phases VizLab, students use both computer-based models and lamp + ball physical models. The VizLab emphasizes the use of different scales in models, why some models are to scale and some are not, and how choices we make in a model can sometimes inadvertently lead to misconceptions. For example, textbook images almost always depict the Earth and Moon as being vastly too close together, and this contributes to the common misconception that the Moon’s phases are caused by the Earth’s shadow. We tested the Moon Phases VizLab in two separate phases. In Phase 1 (fall 2012), we compared learning gains from the WorldWide Telescope (WWT) VizLab with a traditional 2-dimensional Moon phases simulator. Students in this study who used WWT had overall higher learning gains than students who used the traditional 2D simulator, and demonstrated greater enthusiasm for using the virtual model than students who used the 2D simulator. In Phase 2 (spring 2013), all students in the study used WWT for the virtual model, but we experimented with different sequencing of physical and virtual models in the classroom. We found that students who began the unit with higher prior knowledge of Moon phases (based on the pre-unit assessment) had overall higher learning gains when they used the virtual model first, followed by the physical model, while students who had lower prior knowledge benefited from using the physical model first, then the virtual model.

Udomprasert P, Goodman A, Sunbury S, Zhang ZH, Sadler P, Dussault M, Block S, Lotridge E, Jackson J, Constantin A. Visualizing Moon Phases with WorldWide Telescope, in Cosmos in the Classroom, 125th Annual Meeting. San Jose, CA: Astronomical Society of the Pacific ; 2014.Abstract

We report preliminary results from an NSF-funded project to build, test, and research the impact of a WorldWide Telescope Visualization Lab (WWT Vizlab), meant to oer learners a deeper physical understanding of the causes of the Moon’s phases. The Moon Phases VizLab is designed to promote accurate visualization of the complex, 3-dimensional Earth-Sun-Moon relationships required to understand the Moon’s phases, while also providing opportunities for middle school students to practice critical science skills, like using models, making predictions and observations, and linking them in evidence-based explanations. In the VizLab, students use both computer-based models and lamp + ball physical models.    

We present findings from the first two phases of the study - one where we compared learning gains from the WWT VizLab with a traditional 2-dimensional Moon phases simulator; and another where we experimented with different ways of blending physical and virtual models in the classroom.

Presented July 20-24, 2013.

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Goodman AA, Pepe A, Blocker A, Borgman CL, Cranmer K, Crosas M, Stefano RD, Gil Y, Groth P, Hedstrom M, et al. Ten Simple Rules for the Care and Feeding of Scientific Data. PLoS Computational Biology [Internet]. 2014;10 (4) :e1003542. Publisher's VersionAbstractPDF icon 10simplerules_fromplos_site.pdf
Pepe A, Goodman A, Muench A, Crosas M, Erdmann C. How Do Astronomers Share Data? Reliability and Persistence of Datasets Linked in AAS Publications and a Qualitative Study of Data Practices among US Astronomers. PLoS ONE [Internet]. 2014;9 (8) :e104798. Publisher's VersionAbstract

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date

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Beaumont CN, Goodman AA, Kendrew S, Williams JP, Simpson R. The Milky Way Project: Leveraging Citizen Science and Machine Learning to Detect Interstellar Bubbles. The Astrophysical Journal Supplement Series [Internet]. 2014;214 :3. Publisher's VersionAbstract

We present Brut, an algorithm to identify bubbles in infrared images of the Galactic midplane. Brut is based on the Random Forest algorithm, and uses bubbles identified by >35,000 citizen scientists from the Milky Way Project to discover the identifying characteristics of bubbles in images from the Spitzer Space Telescope . We demonstrate that Brut's ability to identify bubbles is comparable to expert astronomers. We use Brut to re-assess the bubbles in the Milky Way Project catalog, and find that 10%-30% of the objects in this catalog are non-bubble interlopers. Relative to these interlopers, high-reliability bubbles are more confined to the mid-plane, and display a stronger excess of young stellar objects along and within bubble rims. Furthermore, Brut is able to discover bubbles missed by previous searches—particularly bubbles near bright sources which have low contrast relative to their surroundings. Brut demonstrates the synergies that exist between citizen scientists, professional scientists, and machine learning techniques. In cases where "untrained" citizens can identify patterns that machines cannot detect without training, machine learning algorithms like Brut can use the output of citizen science projects as input training sets, offering tremendous opportunities to speed the pace of scientific discovery. A hybrid model of machine learning combined with crowdsourced training data from citizen scientists can not only classify large quantities of data, but also address the weakness of each approach if deployed alone.

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2013
Udomprasert PS, Goodman AA, Wong C. WorldWide Telescope Ambassadors: A Year 3 Update, in Communicating Science: A National Conference on Science Education and Public Outreach. Vol 473. Tuscon, AZ: Astronomical Society of the Pacific ; 2013 :137. Publisher's VersionAbstract

We give a brief overview of some key features of WorldWide Telescope and its Ambassadors Program, and we describe two goals for expanding the program in the coming year: scaling up training efforts; and developing “plug and play” Visualization Lab modules that teach key Earth and Space Science concepts to students while emphasizing important scientific processes and skills. We discuss several different ways that members of the astronomy education and outreach community can incorporate WWT-based materials into their work.

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Beaumont CN, Offner SSR, Shetty R, Glover SCO, Goodman AA. Quantifying Observational Projection Effects Using Molecular Cloud Simulations. The Astrophysical Journal [Internet]. 2013;777 :173. Publisher's VersionAbstract

The physical properties of molecular clouds are often measured using spectral-line observations, which provide the only probes of the clouds' velocity structure. It is hard, though, to assess whether and to what extent intensity features in position-position-velocity (PPV) space correspond to "real" density structures in position-position-position (PPP) space. In this paper, we create synthetic molecular cloud spectral-line maps of simulated molecular clouds, and present a new technique for measuring the reality of individual PPV structures. Using a dendrogram algorithm, we identify hierarchical structures in both PPP and PPV space. Our procedure projects density structures identified in PPP space into corresponding intensity structures in PPV space and then measures the geometric overlap of the projected structures with structures identified from the synthetic observation. The fractional overlap between a PPP and PPV structure quantifies how well the synthetic observation recovers information about the three-dimensional structure. Applying this machinery to a set of synthetic observations of CO isotopes, we measure how well spectral-line measurements recover mass, size, velocity dispersion, and virial parameter for a simulated star-forming region. By disabling various steps of our analysis, we investigate how much opacity, chemistry, and gravity affect measurements of physical properties extracted from PPV cubes. For the simulations used here, which offer a decent, but not perfect, match to the properties of a star-forming region like Perseus, our results suggest that superposition induces a  40% uncertainty in masses, sizes, and velocity dispersions derived from 13 CO ( J = 1-0). As would be expected, superposition and confusion is worst in regions where the filling factor of emitting material is large. The virial parameter is most affected by superposition, such that estimates of the virial parameter derived from PPV and PPP information typically disagree by a factor of  2. This uncertainty makes it particularly difficult to judge whether gravitational or kinetic energy dominate a given region, since the majority of virial parameter measurements fall within a factor of two of the equipartition level α   2.

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Sanders NE, Faesi C, Goodman AA. A New Approach to Developing Interactive Software Modules through Graduate Education. arXiv.org. 2013.Abstract
We discuss a set of fifteen new interactive, educational, online software modules developed by Harvard University graduate students to demonstrate various concepts related to astronomy and physics. Their achievement demonstrates that online software tools for education and outreach on specialized topics can be produced while simultaneously fulfilling project-based learning objectives. We describe a set of technologies suitable for module development and present in detail four examples of modules developed by the students. We offer recommendations for incorporating educational software development within a graduate curriculum and conclude by discussing the relevance of this novel approach to new online learning environments like edX.
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2012
Udomprasert, P. GWAC. WWT Ambassadors: WorldWide Telescope for Interactive Learning, in Annual Meeting of the American Astronomical Society. Austin, TX: AAS ; 2012.Abstract

The WorldWide Telescope Ambassadors Program (WWTA) is new outreach initiative run by researchers at Harvard University, WGBH, and Microsoft Research. WWT Ambassadors are astrophysically-literate volunteers who are trained to be experts in using WWT as teaching tool. Ambassadors and learners alike use WWT to create dynamic, interactive Tours of the Universe, which are shared in schools, public venues, and online. Ambassador-created Tours are being made freely available and will ultimately form a comprehensive learning resource for Astronomy and Astrophysics.
In this short talk, we will describe the results of a Pilot Study where volunteer Ambassadors helped sixth-graders use WWT during their six-week Astronomy unit. The results of the study compare learning outcomes for 80 students who participated in WWTA and 80 students who only used traditional learning materials. In the comparison, we find that, after the six-week unit: twice as many "WWT” as "non-WWT” students understand complex three dimensional orbital relationships; and tremendous gains are seen in student interest in science overall, astronomy in particular, and even in using "real” telescopes.

Plans for WWTA include expansion to five US sites within the coming year, and ultimately to an International Program. Online materials will ultimately be available through several sites (at WGBH, Harvard and Microsoft), and will be integrated with existing online curriculum programs such as WGBH's Teachers’ Domain and Microsoft's Partners in Learning. More inormation is presently available at www.cfa.harvard.edu/WWTAmbassadors/.

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Goodman AA. Principles of High-Dimensional Data Visualization in Astronomy. Astronomische Nachrichten [Internet]. 2012;333 (5-6) :505-514. Astrobites commentary on this articleAbstract

sets, though, interactive exploratory data visualization can give far more insight than an approach where data processing
and statistical analysis are followed, rather than accompanied, by visualization. This paper attempts to charts a course
toward “linked view” systems, where multiple views of high-dimensional data sets update live as a researcher selects,
highlights, or otherwise manipulates, one of several open views. For example, imagine a researcher looking at a 3D volume
visualization of simulated or observed data, and simultaneously viewing statistical displays of the data set’s properties
(such as an x-y plot of temperature vs. velocity, or a histogram of vorticities). Then, imagine that when the researcher
selects an interesting group of points in any one of these displays, that the same points become a highlighted subset in
all other open displays. Selections can be graphical or algorithmic, and they can be combined, and saved. For tabular
(ASCII) data, this kind of analysis has long been possible, even though it has been under-used in Astronomy. The bigger
issue for Astronomy and several other “high-dimensional” fields is the need systems that allow full integration of images
and data cubes within a linked-view environment. The paper concludes its history and analysis of the present situation
with suggestions that look toward cooperatively-developed open-source modular software as a way to create an evolving,
flexible, high-dimensional, linked-view visualization environment useful in astrophysical research.

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Pepe A, Goodman A, Muench A. The ADS All-Sky Survey, in Astronomical Data Analysis Software and Systems XX. Paris, France ; 2012. Publisher's VersionAbstract

The ADS All-Sky Survey (ADSASS) is an ongoing effort aimed at turning the NASA Astrophysics Data System (ADS), widely known for its unrivaled value as a literature resource for astronomers, into a data resource. The ADS is not a data repository per se, but it implicitly contains valuable holdings of astronomical data, in the form of images, tables and object references contained within articles. The objective of the ADSASS effort is to extract these data and make them discoverable and available through existing data viewers. The resulting ADSASS data layer promises to greatly enhance workflows and enable new research by tying astronomical literature and data assets into one resource.

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Goodman A, Fay J, Muench A, Pepe A, Udomprasert P, Wong C. WorldWide Telescope in Research and Education. In: Egret D, Gabriel C ADASS XXI. San Francisco: Astronomical Society of the Pacific ; 2012. pp. tba. Publisher's VersionAbstract

The WorldWide Telescope computer program, released to researchers
and the public as a free resource in 2008 by Microsoft Research, has changed the way
the ever-growing Universe of online astronomical data is viewed and understood. The
WWT program can be thought of as a scriptable, interactive, richly visual browser of
the multi-wavelength Sky as we see it from Earth, and of the Universe as we would
travel within it. In its web API format, WWT is being used as a service to display professional
research data. In its desktop format, WWT works in concert (thanks to SAMP
and other IVOA standards) with more traditional research applications such as ds9, Aladin
and TOPCAT. The WWT Ambassadors Program (founded in 2009) recruits and
trains astrophysically-literate volunteers (including retirees) who use WWT as a teaching
tool in online, classroom, and informal educational settings. Early quantitative
studies of WWTA indicate that student experiences with WWT enhance science learning
dramatically. Thanks to the wealth of data it can access, and the growing number
of services to which it connects, WWT is now a key linking technology in the Seamless
Astronomy environment we seek to oer researchers, teachers, and students alike.

2011
Goodman, A. A.; Udomprasert KSSPS ; B ;. Astronomy Visualization for Education and Outreach, in Astronomical Data Analysis Software and Systems XX. Boston, MA ; 2011. Publisher's VersionAbstract

About 50 participants came to a discussion on the benefits and potential obstacles of using astronomy visualization tools for education and public outreach (EPO). Representatives of five different EPO organizations shared information on their project goals and outcomes. Public users need support to learn how to use these programs effectively for education, but the efforts are worthwhile because the thrill that comes from working with real data and the natural beauty of astronomical imagery are great attractors for new science enthusiasts.

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G. Fabbiano, C. Brogan CDEIFGMPDSGP. Recommendations of the Virtual Astronomical Observatory (VAO) Science Council for the VAO second year activity. Cambridge, MA: VAO; 2011 pp. 6. Publisher's VersionAbstract

The VAO (Virtual Astronomical Observatory) Science Council (VAO-SC) met on July 27-28, 2011 at the Harvard-Smithsonian Center for Astrophysics in Cambridge MA, to review the VAO performance during its first year of operations. In this meeting the VAO demonstrated the new tools for astronomers that are being released in September 2011 and presented plans for the second year of activities, resulting from studies conducted during the first year. This document contains the recommendations of the VAO-SC for the second year of activity of the VAO.

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Beaumont CN, Williams JP, Goodman AA. Classifying Structures in the Interstellar Medium with Support Vector Machines: The G16.05-0.57 Supernova Remnant. The Astrophysical Journal [Internet]. 2011;741 :14. Publisher's VersionAbstract

We apply Support Vector Machines (SVMs)—a machine learning algorithm—to the task of classifying structures in the interstellar medium (ISM). As a case study, we present a position-position-velocity (PPV) data cube of 12 CO J = 3-2 emission toward G16.05-0.57, a supernova remnant that lies behind the M17 molecular cloud. Despite the fact that these two objects partially overlap in PPV space, the two structures can easily be distinguished by eye based on their distinct morphologies. The SVM algorithm is able to infer these morphological distinctions, and associate individual pixels with each object at >90% accuracy. This case study suggests that similar techniques may be applicable to classifying other structures in the ISM—a task that has thus far proven difficult to automate.

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Goodman AA. A Guide to Comparisons of Star Formation Simulations with Observations. Computational Star Formation [Internet]. 2011. Publisher's VersionAbstract

Abstract. We review an approach to observation-theory comparisons we call \Taste-Testing."
In this approach, synthetic observations are made of numerical simulations, and then both real
and synthetic observations are \tasted" (compared) using a variety of statistical tests. We rst
lay out arguments for bringing theory to observational space rather than observations to theory
space. Next, we explain that generating synthetic observations is only a step along the way to
the quantitative, statistical, taste tests that oer the most insight. We oer a set of examples
focused on polarimetry, scattering and emission by dust, and spectral-line mapping in starforming
regions. We conclude with a discussion of the connection between statistical tests used
to date and the physics we seek to understand. In particular, we suggest that the \lognormal"
nature of molecular clouds can be created by the interaction of many random processes, as can
the lognormal nature of the IMF, so that the fact that both the \Clump Mass Function" (CMF)
and IMF appear lognormal does not necessarily imply a direct relationship between them.

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Goodman AA, Strom SE, Udomprasert P, Valva A, Wong C. WWT Ambassadors: Worldwide Telescope For Interactive Learning, in American Astronomical Society Meeting Abstracts 217. Vol 43. ; 2011. Publisher's Version
Accomazzi A, Dave R. Semantic Interlinking of Resources in the Virtual Observatory Era, in Astronomical Data Analysis Software and Systems XX. Boston, MA ; 2011. Publisher's VersionAbstract
In the coming era of data-intensive science, it will be increasingly important to be able to seamlessly move between scientific results, the data analyzed in them, and the processes used to produce them. As observations, derived data products, publications, and object metadata are curated by different projects and archived in different locations, establishing the proper linkages between these resources and describing their relationships becomes an essential activity in their curation and preservation. In this paper we describe initial efforts to create a semantic knowledge base allowing easier integration and linking of the body of heterogeneous astronomical resources which we call the Virtual Observatory (VO). The ultimate goal of this effort is the creation of a semantic layer over existing resources, allowing applications to cross boundaries between archives. The proposed approach follows the current best practices in Semantic Computing and the architecture of the web, allowing the use of off-the-shelf technologies and providing a path for VO resources to become part of the global web of linked data.
2010
Kurtz M  J. The Emerging Scholarly Brain, in Future Professional Communication in Astronomy-II (FPCA-II). Cambridge, MA ; 2010. Publisher's VersionAbstract
It is now a commonplace observation that human society is becoming a coherent super-organism, and that the information infrastructure forms its emerging brain. Perhaps, as the underlying technologies are likely to become billions of times more powerful than those we have today, we could say that we are now building the lizard brain for the future organism.