Kirk Borne

There has been a dramatic revolution in the conduct of science in recent years, primarily triggered by the digital revolution. Online science, collaboratories, data-intensive science, digital libraries, and scientific social networks have changed the character of science practice. Despite this revolution in how scientists do their work, there has been very little change in standard science courses and curricula to match this reality. Numerous professional society working groups, national academies committees, and national agency blue ribbon panels have produced reports that call for dramatic changes in science education at all levels. In one case, a panel of experts produced the special report "Transform Science: Computational Education for Scientists" [1]; and in another case, a landmark journal article on "Computational Thinking" is transforming numerous NSF research programs and proposal requirements [2]. The proposed interactive presentation session for ITL&#...

The remarkable success of Galaxy Zoo as a citizen science project for galaxy classification within a terascale astronomy data collection has led to the development of a broader collaboration, known as the Zooniverse. Activities will include astronomy, lunar science, solar science, and digital humanities. Some features of our program include development of a unified framework for citizen science projects, development

ABSTRACT A ``ring'' galaxy is thought to result from the nearly head-on collision between an intruder galaxy and a spiral. During this collision, an expanding density wave sweeps disk material into a ring form in the target galaxy. The cloud-cloud collisions in the nucleus of the target galaxy result in starburst activity. We present IUE spectra for a sample of 11 ``ring'' galaxies selected on the basis of their morphology and IRAS detections. The remnant nuclei of the target galaxies were observed with the SWP camera. The IUE observations reveal diverse results; i.e., starburst activity (NGC 7714), elevated UV continuum (Arp 144), and Ly-alpha emission with no other UV features (Arp 147). Presumably, the UV activity is dependent upon the dynamics of the initial collision, the strength and duration of the nuclear starburst, and the elapsed time since the collision.

A sample of 19 low redshift (0.03<z<0.07) very luminous infrared galaxy (VLIRG: 10^11L_< L[8-1000 μm] < 10^12 L_) systems (30 galaxies) has been imaged in B, V, and I. These objects cover a luminosity range that is key to linking the most luminous infrared galaxies with the population of galaxies at large. We have obtained photometry for all of these VLIRG systems, the individual galaxies (when detached), and their nuclei, and the relative behavior of these classes has been studied in optical color-magnitude diagrams. The photometric properties of the sample are also compared with previously studied samples of ULIRGs. The mean observed photometric properties of VLIRG and ULIRG samples, considered as a whole, are indistinguishable at optical wavelengths. This suggests that not only ULIRG, but also the more numerous population of VLIRGs, have similar rest-frame optical photometric properties as the submillimeter galaxies (SMG), reinforcing the connection between low- z LIR...

The Scholars of Studying Teaching Collaborative engaged a dozen faculty members from 12 specializations and 4 colleges at a large public university in a 2-year teach-ing and research project with the goal of learning about and enacting a self-study of professional practice. Participants were selected from various disciplines to pro-voke alternative perspectives in whole group and critical friend teams. While we each conducted a self-study, we also designed and enacted a meta-study to assess our professional development within the context of the collaborative. We analyze the potential of engaging in collective self-study and report how the methodologi-cal challenges initiated transformational learning that bridged theory and praxis. Learning the self-study methodology was complex, but such concentration

Science research programs have become massive data producers. This ability to produce large data volumes must be matched by technologies that make better use of the data flood and that facilitate reuse of the data, in order to reap the maximum scientific return from our research investments. In particular, the extraction and integration of knowledge from multiple data sources must become standard practice, both for science-enabled decision support and for scientific discovery. We describe the emerging e-Science paradigm and its application to data-driven knowledge discovery and collaborative knowledge sharing. The Science Data Flood The flood of data in all disciplines poses a critical challenge to the advancement of science. The challenge is manifest in several areas: data discovery, data access, information retrieval, knowledge discovery, knowledge representation, and knowledge sharing. As the quantity of data increases at fantastic rates over the next several years, these challen...

Abstract. We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night); multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

We describe the new data-intensive research paradigm that astronomy and astrophysics is now entering. This is described within the context of the largest data-producing astronomy project in the coming decade – the LSST (Large Synoptic Survey Telescope). The enormous data output, database contents, knowledge discovery, and community science expected from this project will impose massive data challenges on the astronomical research community. One of these challenge areas is the rapid machine learning, data mining, and classification of all novel astronomical events from each 3-gigapixel (6-GB) image obtained every 20 seconds throughout every night for the project duration of 10 years. We describe these challenges and a particular implementation of a classification broker for this data fire hose. 1.

Peer-to-Peer (P2P) networks are appealing for astronomy data mining from virtual observatories because of the large volume of the data, compute-intensive tasks, potentially large number of users, and distributed nature of the data analysis process. This paper offers a brief overview of PADMINI—a Peer-to-Peer Astronomy Data MINIng system. It also presents a case study on PADMINI for distributed outlier detection using astronomy data. PADMINI is a web- based system powered by Google Sky and distributed data mining algorithms that run on a collection of computing nodes. This paper offers a case study of the PADMINI evaluating the architecture and the performance of the overall system. Detailed experimental results are presented in order to document the utility and scalability of the system. As the amount of data available at various geographically distributed sources is increasing rapidly, traditional centralized techniques for performing data analytics are proving to be insufficient f...

This paper represents the consensus view of the 124 participants in the Second Workshop on New Concepts for Far-Infrared/Submillimeter Space Astronomy.We recommend that NASA pursue the vision for far-IR astronomy outlined in the NAS Decadal Survey, which said: A rational coordinated program for space optical and infrared astronomy would build on the experience gained with NGST1 to construct [a JWST-scale filled-aperture far-IR telescope SAFIR, and then ultimately, in the decade 2010 to 2020, build on the SAFIR, TPF, and SIM experience to assemble a space-based, far-infrared interferometer. SAFIR will study star formation in the young universe, the buildup of elements heavier than hydrogen over cosmic history, the process of galaxy formation, and the early phases of star formation, which occur behind a veil of dust that precludes detection at mid IR and shorter wavelengths. The far-infrared interferometer will resolve distant galaxies to study protogalaxy interactions and mergers and...

We present results from an on-going Hubble Space Telescope (HST) survey of a large sample of ULIRGs (Ultra-Luminous IR Galaxies). New ground-based observations are now being used to complement the HST data and to assist in the interpretation of these complex objects. A rich spectroscopic, morphological, and dynamical diversity is found within the ULIRG population, nearly 100% of which are merger and/or collision remnants. The consequences of this diversity may apply to the interpretation of distant submm/FIR sources and their subsequent evolution.

Science research programs have become massive data producers. This ability to produce large data volumes must be matched by technologies that make better use of the data flood and that facilitate reuse of the data, in order to reap the maximum scientific return from our research investments. In particular, the extraction and integration of knowledge from multiple data sources must become standard practice, both for science-enabled decision support and for scientific discovery. We describe the emerging e-Science paradigm and its application to data-driven knowledge discovery and collaborative knowledge sharing.

This Astro2020 State of the Profession Consideration White Paper highlights the growth of astrostatistics and astroinformatics in astronomy, identifies key issues hampering the maturation of these new subfields, and makes recommendations for structural improvements at different levels that, if acted upon, will make significant positive impacts across astronomy.

Data volumes from multiple sky surveys have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into tens (or hundreds) of petabytes in the next decade. This exponential growth of new data both enables and challenges effective astronomical research, requiring new approaches. Thus far, astronomy has tended to address these challenges in an informal and ad hoc manner, with the necessary special expertise being assigned to e-Science or survey science. However, we see an even wider scope and therefore promote a broader vision of this data-driven revolution in astronomical research. For astronomy to effectively cope with and reap the maximum scientific return from existing and future large sky surveys, facilities, and data-producing projects, we need our own information science specialists. We therefore recommend the formal creation, recognition, and support of a major new discipline, which we call Astroinformatics. Astroinformatics includes a set of ...

Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and large astronomical surveys, it is becoming clear that future advances will also rely heavily on how those data are analyzed and interpreted. New methodologies derived from advances in statistics, computer science, and machine learning are beginning to be employed in sophisticated investigations that are not only bringing forth new discoveries, but are placing them on a solid footing. Progress in wide-field sky surveys, interferometric imaging, precision cosmology, exoplanet detection and characterization, and many subfields of stellar, Galactic and extragalactic astronomy, has resulted in complex data analysis challenges that must be solved to perform scientific inference. Research in astrostatistics and astroinformatics will be necess...

Massive amount of time series data are generated daily, in areas as diverse as astronomy, industry, sciences, and aerospace, to name just a few. One obvious problem of handling time series databases concerns with its typically massive size—gigabytes or even terabytes are common, with more and more databases reaching the petabyte scale. Most classic data mining algorithms do not perform or scale well on time series data. The intrinsic structural characteristics of time series data such as the high dimensionality and feature correlation, combined with the measurement-induced noises that beset real-world time series data, pose challenges that render classic data mining algorithms ineffective and inefficient for time series. As a result, time series data mining has attracted enormous amount of attention in the past two decades. In this chapter, we discuss the state-of-the-art techniques for time series pattern recognition, the process of mapping an input representation for an entity or ...

ABSTRACT In the last two years Citizen Scientists from Galaxy Zoo have identified almost 3000 systems of interacting galaxies. The Mergers Zoo Project allows members of the public to further analyze pairs of interacting galaxies in order to determine their dynamical properties. A restricted, three-body simulation using a realistic potential with a dynamical friction approximation has been implemented in a Java Applet. Citizen Scientists are tasked with target galaxy pairs for study. The tool produces simulation output from randomly selected system parameters. Users are able to identify candidate simulations for further study based on how well the output matches the target image. In this manner a wide range of parameters covering the "likely'' region of phase space can be sampled. Using this approach, the Mergers Zoo Project expects to determine the key dynamical properties of hundreds of pairs of interacting galaxies in the next two years. This work presents a brief overview of the results for the systems studied to date.

• As our data volumes grow, especially in the sciences (where scientific funding for research barely grows at all), we will fall farther and farther behind in our ability to analyze, assimilate, and extract knowledge from our data collections... unless we develop and apply ...

Page 1. Distributed Data Mining for Astronomy Catalogs Chris Giannella ¡ ,¢ , Haimonti Dutta ¡ , Kirk Borne£ , Ran Wolff¤ , Hillol Kargupta ¡ ,¥ ¦ Department of Computer Science and Electrical Engineering University of Maryland, Baltimore County ...

A ``ring'' galaxy is thought to result from the nearly head-on collision between an intruder galaxy and a spiral. During this collision, an expanding density wave sweeps disk material into a ring form in the target galaxy. The cloud-cloud collisions in the nucleus of the target galaxy result in starburst activity. We present IUE spectra for a sample of 11 ``ring'' galaxies selected on the basis of their morphology and IRAS detections. The remnant nuclei of the target galaxies were observed with the SWP camera. The IUE observations reveal diverse results; i.e., starburst activity (NGC 7714), elevated UV continuum (Arp 144), and Ly-alpha emission with no other UV features (Arp 147). Presumably, the UV activity is dependent upon the dynamics of the initial collision, the strength and duration of the nuclear starburst, and the elapsed time since the collision.

We present some first results from a GALEX and Spitzer survey of a dozen collisional ring galaxies. The combination of UV and mid-IR imaging and spectroscopy will allow us to investigate the relationship between massive star formation sites, PAH molecular–band strengths, and dust heating in these mainly simultaneous starburst rings. A deep observation of the well-known Cartwheel ring galaxy has revealed a gigantic outer UV disk which extends to at least twice the radius of the outer blue star–forming ring. A lack of UV ...

We present new B-- and I--band WFPC2 images of the peculiar ring galaxy IIZw28 which show considerable new structure in the ring. The galaxy is interesting because it is one of the few well known ring galaxies without an obvious massive companion. The HST observation and new VLA neutral hydrogen observations show that IIZw28 has a number of newly discovered

IMPReSS is one of several new services provided by the Astrophysics Data Facility (ADF) at the NASA Goddard Space Flight Center. It is a graphical interface to astrophysics databases that presents the user with plane of the sky outlines or silhouettes of images obtained by space-based telescopes. Its purpose is to provide a visualisation environment that finds and displays, in detail, mission footprints that lie within a user selected region of the sky. Searches can also be restricted by a range in time of the observations. It is also intended to aid astronomers in retrieving publicly available data by sending requests to data archive sites for detailed information, browse images, and data files of graphically selected observations. The time to search through the logs of many missions is kept to a minimum by holding the essential information in memory in an IDL session continually running in server mode. The primary archive sites for which IMPReSS holds metadata are: the National Space Sciences Data Center (NSSDC), the High Energy Astrophysics Science Archive Research Center (HEASARC), and the Space Telescope Science Institute (STScI). links to and from other browsers are being created. For instance, a link exists from the ADC catalog viewer (discussed at this meeting) allows one to quickly find an entry in a catalog or journal table and immediately find which NASA missions have made observations of the entry object.

The class of Very Luminous IR Galaxies (VLIRGs) is defined by those galaxies whose IR luminosities are between 1011 and 1012 Lo. They represent a key class of objects in the study of galaxy formation and evolution. For example, they offer the opportunity to study how the fundamental astrophysical and morphological properties of galaxies vary with IR luminosity, providing the link between the dynamically diverse Ultra-Luminous IR Galaxies (ULIRGs: LIR > 1012 Lo) and normal galaxies. Furthermore, VLIRGs may be closely related to several recently identified cosmological populations in the sense that VLIRGs may be either their low-redshift analogs or the direct result of their evolution: EROs (Extremely Red Objects), GRB host galaxies, IR-selected AGN, faint SCUBA submm sources, or galaxies comprising the IR background. A prototype analysis of the multi-wavelength properties of VLIRGs is presented, utilizing data and catalogs from a variety of distributed astronomical information sources. This manually intensive research exercise represents one of many possible NVO (National Virtual Observatory) science scenarios that will be greatly facilitated and made much more efficient through the application of planned NVO resources. Support for this work was provided in part by NASA grant NAS5-99226.