Web sites mentioned in the talk, all relevant to #AASviz:

  • .Astronomy: dotastronomy.com ‘Dot-astronomy’ aims to bring together an international community of astronomy researchers, developers, educators and communicators to showcase and build upon web-based projects, from outreach and education to research tools and data analysis. #dotastronomy

  • ADS All-Sky Survey: adsass.org Astronomy Papers. On the Sky. Who studies what, when, how, and why? Funded by #NASA. #adsass

  • AstroBetter: astrobetter.com Tips and Tricks for Professional Astronomers. #astrobetter

  • Astronomical Medicine: am.iic.harvard.edu Trading tools between Astronomy and Medicine.

  • Astrometry.net: [astrometry.net] (http://astrometry.net) An astrometric calibration service to create correct, standards-compliant astrometric meta-data for every useful astronomical image ever taken, past and future.

  • astroML: astroML.org Python module for Machine Learning and Data Mining in Astronomy.

  • astropy: astropy A community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages. @astropy

  • Authorea: authorea.com A collaborative platform for research. Write and manage your technical documents in one place. #authorea, @authorea

  • Color Brewer: [colorbrewer2.org] (http://colorbrewer2.org) Color Advice for Cartography (and quantitative graphics more generally!) @ColorBrewer

  • D3: d3.js D3 is a JavaScript library for manipulating documents based on data.

  • d3po: d3po.org Linked views using d3, on the web. Import from Glue, Export to Authorea. #d3po

  • edX: edx.org Great online courses from the world's best universities. Harvard's courses at harvardx.harvard.edu #edX #HarvardX

  • Glue: glueviz.org Multidimensional data exploration. Linked Statistical Graphics. Flexible linking across data. Full scripting capability, in Python. #glueviz

  • Plotly: plot.ly Analyze and visualize data, together. Plotly is a collaborative data analysis and graphing tool. #plotly

  • Seamless Astronomy: [projects.iq.harvard.edu/seamlessastronomy] (http://projects.iq.harvard.edu/seamlessastronomy) Linking scientific data, publications, and communities. #seamlessastronomy

  • Virtual Observatory: usvao.org, www.ivoa.net, cdsportal.u-strasbg.fr Three points of access to official VO tools and infrastructure. #ivoa

  • WorldWide Telescope: worldwidetelescope.org A free Universe Information System from Microsoft Research. Immerse yourself in a seamless beautiful environment. #worldwidetelescope

  • WorldWide Telescope Ambassadors: wwtambassadors.org
    WorldWide Telescope Ambassadors use the free WorldWide Telescope computer program to educate the public about Astronomy and Science. #wwtambassadors

  • yt: yt-project.org Open source, community-developed Analysis and Visualization of Astrophysical simulation data. @yt_astro

  • Zooniverse: zooniverse.org The Zooniverse is home to the internet's largest, most popular and most successful citizen science projects. @the_zooniverse

Many additional relevant (software) links can be found within these papers:

  • Scientific Visualization in Astronomy: Towards the Petascale Astronomy Era (Hassan & Fluke 2011): tinyurl.com/petastroviz Introduces a mapping between astronomical sources of data and data representations used in general-purpose visualization tools.

  • Principles of High-Dimensional Data Visualization in Astronomy (Goodman 2012): [tinyurl.com/datavizprinciples] (http://tinyurl.com/datavizprinciples) 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.

  • A New Approach to Developing Interactive Software Modules Through Graduate Education (Sanders, Faesi & Goodman 2013): [tinyurl.com/eduviz] (http://tinyurl.com/eduviz) Tests whether interactive, educational, online software modules can be developed effectively by students as a curriculum component of an advanced science course. (Answer is yes.)

  • Ten Simple Rules for the Care and Feeding of Scientific Data (Goodman et al. 2014): tinyurl.com/10simpledata This article offers a short guide to the steps scientists can take to ensure that their data and associated analyses continue to be of value and to be recognized.

  • Science you can play with (Pepe & Jenkins 2014): authorea.com/3904 Blog Post showing how to embed d3po (javascript) output and IPython Notebooks inside Authorea.