High-quality, usable, and effective software is essential for supporting astronomers in the discovery-focused tasks of data analysis and visualisation. As the volume, and perhaps more crucially, the velocity of astronomical data grows, the role of the astronomer is changing. There is now an increased reliance on automated and autonomous discovery and decision-making workflows rather than visual inspection. We assert the need for an improved understanding of how astronomers (humans) currently make visual discoveries from data. This insight is a critical element for the future design, development and effective use of cyber-human discovery systems, where astronomers work in close collaboration with automated systems to gain understanding from continuous, real-time data streams. We discuss how relevant human performance data could be gathered, specifically targeting the domains of expertise and skill at visual discovery, and the identification and management of cognitive factors. By looking to other disciplines where human performance is assessed and measured, we propose four early-stage applications that would: (1) allow astronomers to evaluate, and potentially improve, their own visual discovery skills; (2) support just-in-time coaching; (3) enable talent identification; and (4) result in user interfaces that automatically respond to skill level and cognitive state. Throughout, we advocate for the importance of user studies and the incorporation of participatory design and co-design practices into the planning, implementation and evaluation of alternative user interfaces and visual discovery environments.
Collaborations in astronomy and astrophysics are faced with numerous cyber infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large, heterogeneous data sets with significant processing requirements and complex science software tools. The cyberhubs system is an easy-to-deploy package for small to medium-sized collaborations based on the Jupyter and Docker technology, that allows web-browser enabled, remote, interactive analytic access to shared data. It offers an initial step to address these cha…
As the next decade approaches, it is once again time for the US astronomical community to assess its investment priorities for the coming decade on the ground and in space. This report, created to aid NOAO in its planning for the 2020 Decadal Survey on Astronomy and Astrophysics, reviews the outcome of the previous Decadal Survey (Astro2010); describes the themes that emerged from the 2018 NOAO community planning workshop "NOAO Community Needs for Science in the 2020s"; and based on the above, offers thoughts for the coming review. We find that a balanced set of investments in small- to large-…
Enhancing interoperable data access to radio data has become a science priority within the International Virtual Observatory Alliance (IVOA). This lead to the foundation of the IVOA Radio astronomy Interest Group. Several radio astronomers and project scientists enrolled in various projects (NRAO, ASKAP, LOFAR, JIVE, ALMA, SKA, INAF, NenuFAR, etc.) have joined. Together they are paving the way to a better integration of their services in the virtual observatory (VO) infrastructure and propose extension of IVOA standards to help achieving this goal. Calibrated radio datasets such as cubes, imag…
Experience suggests that structural issues in how institutional Astrophysics approaches data-driven science and the development of discovery technology may be hampering the community's ability to respond effectively to a rapidly changing environment in which increasingly complex, heterogeneous datasets are challenging our existing information infrastructure and traditional approaches to analysis. We stand at the confluence of a new epoch of multimessenger science, remote co-location of data and processing power and new observing strategies based on miniaturized spacecraft. Significant effort w…
In the era of "big data" and with the advent of web 2.0 technologies, ESASky (http://sky.esa.int) aims at providing a modern and visual way to access astronomical science-ready data products and metadata. The main goal of the application is to simplify the interaction between the scientific community and the ever-growing amount of data collected over the past decades from the most important astronomy missions. The ESASky concept is to offer a complementary scientific application to the more-traditional table-oriented exploitation of astronomical data, by allowing a more natural and visual appr…
Astronomy is entering an era of data-driven discovery, due in part to modern machine learning (ML) techniques enabling powerful new ways to interpret observations. This shift in our scientific approach requires us to consider whether we can trust the black box. Here, we overview methods for an often-overlooked step in the development of ML models: building community trust in the algorithms. Trust is an essential ingredient not just for creating more robust data analysis techniques, but also for building confidence within the astronomy community to embrace machine learning methods and results.
The increase in the number of researchers coupled with the ease of publishing and distribution of scientific papers (due to technological advancements) has resulted in a dramatic increase in astronomy literature. This has likely led to the predicament that the body of the literature is too large for traditional human consumption and that related and crucial knowledge is not discovered by researchers. In addition to the increased production of astronomical literature, recent decades have also brought several advancements in computational linguistics. Especially, the machine-aided processing of …
How should we invest our available resources to best sustain astronomy's track record of discovery, established over the past few decades? Two strong hints come from (1) our history of astronomical discoveries and (2) literature citation patterns that reveal how discovery and development activities in science are strong functions of team size. These argue that progress in astronomy hinges on support for a diversity of research efforts in terms of team size, research tools and platforms, and investment strategies that encourage risk taking. These ideas also encourage us to examine the implicati…
Where appropriate repositories are not available to support all relevant astronomical data products, data can fall into darkness: unseen and unavailable for future reference and re-use. Some data in this category are legacy or old data, but newer datasets are also often uncurated and could remain "dark". This paper provides a description of the design motivation and development of Astrolabe, a cyberinfrastructure project that addresses a set of community recommendations for locating and ensuring the long-term curation of dark or otherwise at-risk data and integrated computing. This paper also …
The 2020s will be the most data-rich decade of astronomy in history. As the scale and complexity of our surveys increase, the problem of scheduling becomes more critical. We must develop high-quality scheduling approaches, implement them as open-source software, and begin linking the typically separate stages of observation and data analysis.
SURF is the collaborative ICT organisation for Dutch education & research and coordinates the national e-infrastructure (surf.nl). To accelerate scientific discovery, SURF invests in, operates and explores high-end IT solutions for and with researchers in the Netherlands. In this ADASS 2019 contribution we present our latest developments in high performance and high throughput cloud computing. These developments are particularly relevant for Astronomy, as this science domain: (i) generates large (Petabyte sized) data collections, (ii) uses rapid release and deployment schemes for their softwar…
Some of the most exciting and promising areas of Astronomy research today are found at the boundaries of the discipline: the search for Exoplanets and Multi-Messenger Astronomy. In order to achieve breakthroughs in these research fields over the next decade, innovation and expansion of the digital information infrastructure which supports this research is required. Astronomy has been well-served by the existence of an open, distributed network of data centers and archives. However, institutional barriers and differing research cultures have prevented cross-disciplinary collaborations, creating…
The almost universal availability of electronic connectivity, portable devices, and the web is bringing about a major revolution: information of all kinds is rapidly becoming accessible to everyone, transforming social, economic and cultural life practically everywhere in the world. Internet technologies represent an unprecedented and extraordinary two-way channel of communication between producers and users of data. Open Universe is an initiative proposed to the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) and currently in implementation under the leadership of the Un…
Since its inception in the early 2000, the Virtual Observatory (VO), developed as a collaboration of many national and international projects, has become a major factor in the discovery and dissemination of astronomical information worldwide. The IVOA has been coordinating all these efforts worldwide to ensure a common VO framework that enables transparent access to and interoperability of astronomy resources (data and software) around the world. The VO is not a magic solution to all astronomy data management challenges but it does bring useful solutions in many areas borne out by the fact tha…
The era of data-intensive astronomy is being ushered in with the increasing size and complexity of observational data across wavelength and time domains, the development of algorithms to extract information from this complexity, and the computational power to apply these algorithms to the growing repositories of data. Data-intensive approaches are pushing the boundaries of nearly all fields of astronomy, from exoplanet science to cosmology, and they are becoming a critical modality for how we understand the universe. The success of these approaches range from the discovery of rare or unexpecte…
Harnessing the sheer discovery potential of gravitational wave astronomy will require bold, deliberate, and sustained efforts to train and develop the requisite workforce. The next decade requires a strategic plan to build -- from the ground up -- a robust, open, and well-connected gravitational wave astronomy community with deep participation from traditional astronomers, physicists, data scientists, and instrumentalists. This basic infrastructure is sorely needed as an enabling foundation for research. We outline a set of recommendations for funding agencies, universities, and professional s…
Over the last ten years there has been a large increase in the number of projects using sound to represent astronomical data and concepts. Motivation for these projects includes the potential to enhance scientific discovery within complex datasets, by utilising the inherent multi-dimensionality of sound and the ability of our hearing to filter signals from noise. Other motivations include creating engaging multi-sensory resources, for education and public engagement, and making astronomy more accessible to people who are blind or have low vision, promoting their participation in science and re…
Linking to Data - Effect on Citation Rates in Astronomy
带有数据链接的文章和没有数据链接的文章之间的引用率是否存在差异？除了从纯学术的角度来看是有趣的，这个问题也是高度相关的推进科学的过程。数据共享不仅有助于索赔的核实过程，而且有助于在档案数据中发现新的发现。然而，链接到数据仍然远远没有成为一种“实践”，特别是当作者在写作和提交过程中提供这些链接时。你需要有一个意愿和一个出版机制，以创造这样的做法。显示与数据链接的文章获得更高的引用率可能会增加科学家采取额外步骤将数据源链接到他们的出版物的意愿。在这个演示中，我们将展示这确实是这样的情况：与数据链接的文章比没有这样的链接的文章有更高的引用率。ADS由NASA Grant NNX 09 AB 39 G资助。
California Institute of Technology（加州理工学院）；Heidelberg Institute for Theoretical Studies（海德堡理论研究所）；University of California, Irvine（加州大学尔湾分校）
We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big data era with the first digital sky surveys in the early 1990s and the resulting Terascale data sets, which required automating of many data processing and analysis tasks, for example the star-galaxy separation, with billions of feature vectors in hundreds of dimensions. The exponential data growth continued, with the rise of synoptic sky surveys and the Time Domain Astronomy, with the resulting Petascale data strea…
Toward decision-aware AI for LSST-scale time-domain astronomy
Centro Brasileiro de Pesquisas Físicas（巴西物理研究中心）；Laboratorio Interinstitucional de e-Astronomia-LIneA（跨机构电子天文学实验室）；California Institute of Technology（加州理工学院）；University of Delaware（特拉华大学）；INAF–Osservatorio Astronomico di Palermo（意大利国家天体物理研究所巴勒莫天文台）；University of Minnesota（明尼苏达大学）；Stanford University（斯坦福大学）
NCSA, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校国家超级计算应用中心）；Department of Astronomy, University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校天文学系）；California Institute of Technology（加州理工学院）；Las Cumbres Observatory（拉斯坎布雷斯天文台）；Caltech/IPAC-NExScI（加州理工学院/红外处理与分析中心-系外行星科学研究所）；Department of Physics and Astronomy, University of Delaware（特拉华大学物理与天文学系）；Data Science Institute, University of Delaware（特拉华大学数据科学研究所）；Center for Urban Science and Progress, New York University（纽约大学城市科学与进步中心）；The Oskar Klein Centre for Cosmoparticle Physics, Stockholm University（斯德哥尔摩大学奥斯卡·克莱因宇宙粒子物理中心）；The University of Chicago（芝加哥大学）；IBM Systems（IBM系统部）
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" wor…
