08 November 2020 to 12 November 2020
Location: 
Virtual


The Astronomical Data Analysis Software and Systems (ADASS) conference is held each year at a different hosting astronomical institution. The conference provides a forum for scientists and programmers concerned with algorithms, software and software systems employed in the acquisition, reduction, analysis, and dissemination of astronomical data. An important element of the program is to foster communication between developers and users with a range of expertise in the production and use of software and systems. The program consists of invited talks, contributed oral and display papers, tutorials, user group meetings and special interest group meetings (called BOFs).

The 2020 year edition will consist of 5 day of tutorials, talks, along with more than 40 oral presentations, more than 100 posters and three BoF sessions per day dedicated to astronomy, software, data, algorithms and operations.

ESCAPE will be highly represented at the conference, with a series of BoF sessions, posters and talks, covering different aspects of ESCAPE work being developed during the year.

ESCAPE Open-source scientific Software and Service Repository (OSSR)

The ESCAPE OSSR team, which deals with software services for open science data-analysis of the ESFRI facilities, will present their latest developments regarding open environment to guarantee cross-fertilisation and to develop community-specific data services. See list of presentations below

- Poster Session - Open-source Scientific Software and Service Repository (link) 8 November 2020 | 12:40 UTC

The ESFRI projects in ESCAPE shall provide open access to their data, software and science tools to allow reproducibility of science results and the development of open science analyses across domains and infrastructures, necessary for opening the window to multi-messenger and multi-probe research. Here ESCAPE OSSR presents one of the key component of the ESCAPE to achieve this goal: the ESCAPE OSSR service that aims at providing the tools necessary for the communities to share their science products in a harmonised way respecting the FAIR principles, promoting open science and maximising cross-fertilisation by software re-use and co-development.

- Talk Session - Hangar at VIRGO (link) 8 November 2020 | 15:15

Hangar is an open source data versioning tool that is geared towards reproducibility and collaboration on numerical datasets, with semantics that are similar to git. Its intrinsic adaptability to different data structures make Hangar a valuable tool for any physics data analysis pipeline. It also represents a flexible framework in the context of machine learning projects, allowing to choose the best suited training and test sets for the goal to be achieved.

As a collaboration between VIRGO/EGO and OROBIX during the ESCAPE project, here it is presented the implementation of Hangar into a machine learning pipeline of gravitational wave physics at VIRGO, providing scientists with git-like features to manage and control their experimental data. In the context of the VIRGO Collaboration, data versioning provided by Hangar also is envisioned to be used in general data processing pipeline, to browse among different versions of scientific data, depending on the calibration process.

- Poster Session - Reconstruction of IACT events using deep learning techniques with CTLearn (link) 8 November 2020 | 15:45 UTC

Arrays of imaging atmospheric Cherenkov telescopes (IACT) are superb instruments to probe the very-high-energy gamma-raysky. This type of telescope focuses the Cherenkov light emitted fromair showers, initiated by very-high-energy gamma rays and cosmic rays,onto the camera plane. Then, a fast camera digitizes the longitudinaldevelopment of the air shower, recording its spatial, temporal, andcalorimetric information. The properties of the primary very-high-energyparticle initiating the air shower can then be inferred from thoseimages: the primary particle can be classified as a gamma ray or acosmic ray and its energy and incoming direction can be estimated.This so-called full-event reconstruction, crucial to the sensitivityof the array to gamma rays, can be assisted by machine learningtechniques. Here, ESCAPE presents a deep-learning driven, full-eventreconstruction applied to simulated, IACT events usingCTLearn. CTLearn is a Python package that includes modules for loadingand manipulating IACT data and for running deep learning models withTensorFlow, using pixel-wise camera data as input.

- BoF Session - Best licensing practices (link) 9 November 2020 | 08:00-09:30 UTC

In 2016 the FAIR principles, aimed at improving the Findability, Accessibility, Interoperability, and Reuse of digital assets were postulated. Since then the scientific community has been working on interpreting those standards and applying them to their data. Among these digital assets, software plays a special role, as software as a tool for data exploitation is diversely used and dynamically developed. Therefore, principles that apply to data can not literally be copied to software, especially in relation to licensing and citation. During ADASS XXIX it became clear that several groups worldwide are working on formalising the licensing of software and other digital assets. For this session, ESCAPE OSSR team will coordinate a discussion focused on what policies and tools help in making software open and accessible, and thus more suited for community reuse.

Note: This activity, directly related to ESCAPE, includes contributions from members not part of ESCAPE.

ESCAPE Connecting ESFRI projects to EOSC through VO framework (CEVO)

The ESCAPE Connecting ESFRI projects to EOSC through VO framework (CEVO) is making the seamless connection of ESFRI and other astronomy and astroparticle research infrastructures to the EOSC through the ESCAPE Virtual Observatory (VO).

- Poster Session - Search for Spatial and Temporal Coincidence Between LAT/Fermi Exposure Maps and GW Sky Localizations (link) 8 November | 06:35 UTC

The poster describes a practical method to search for spatial and temporal coincidence of the LAT/Fermi coverage over a gravitational-wave sky localization. The method returns the overlap region between the two sky areas within a proper time window selected by the user. This approach offers a prompt setting of the observational strategies for searching potential electromagnetic candidates as well as a fast cross-matching between the LAT and the LIGO, Virgo and KAGRA databases for dedicated post-processing analysis.
The tasks are performed using the encoded standard method named Multi Order Coverage Map and visualized in the Aladin Desktop.

Note: ESCAPE contributed to this work (it wasnt lead by ESCAPE)

- Poster Session - Radio Astronomy visibility data discovery and access using IVOA standards (link) 8 November 2020 | 07:25 UTC

Radio astronomical archives for large facilities (VLA, ASKAP, LOFAR, JIVE, MeerKAT) used to mostly store raw or calibrated visibility data. However, the situation is changing and some facilities (e.g. ALMA), store and distribute science ready data. This will also be the case for future radio telescopes, like SKA, where calibrated and imaged data products will be provided. Naturally, the major goal of these archives is to make their data discoverable and accessible to the astronomy community. Today, many archives give access to visibility data with project-specific web interfaces in order to allow users to reprocess the data with fine tuned reduction parameters. Science platforms such as ESAP developed within the ESCAPE project will allow this. IVOA decided to make integration of radio astronomy data in the Virtual Observatory (VO) a science priority. Various radio astronomers and projects (NRAO, ASKAP, LOFAR, JIVE, ALMA, SKA, INAF, NenuFAR, etc.) joined the Radio Astronomy Interest Group of the IVOA, which was recently founded. Together they are paving the way to a better integration of their services in the VO infrastructure and are proposing evolution of IVOA standards to help achieving this goal.

In this context CDS created a prototype for exposing visibility data observations, split in a consistent list of datasets in an ObsTAP service, for coarse grain discovery. Additional metadata such as number of antennae, frequency ranges, uv_density plots, frequency-phase and frequency-amplitude plots, primary and synthesized beams are also provided either by adding column metadata or by using the DataLink technique.

This presentation describes the process of metadata integration in the system, explores how to extend the ObsCore data model specification for radio visibility data and details the choices which have been made. We furthermore show results of data selections through various VO applications. We conclude with the possible evolutions of the prototype and lessons learnt from this exercise.

- Poster Session - Spreading the word – current status of VO tutorials and schools (link) 8 November 2020 | 12:35–12:35 UTC

With some telescopes standing still, now more than ever simple access to archival data is vital for astronomers and they need to know how to go about it. Within European Virtual Observatory (VO) projects, such as COSADIE (2013-2015), Asterics (2015-2018) and ESCAPE (since 2019), we have been offering Virtual Observatory schools for many years. The aim of these schools are twofold: teaching (early career) researchers about the functionalities and possibilities within the Virtual Observatory and collecting feedback from the astronomical community. In addition, the VO dissemination team at CDS started to explore more and new ways to interact with the community: a series of blog posts on AstroBetter.com, a lunch time session at the virtual EAS meeting 2020, a Spanish VO school, GAVO supported events and their Virtual Observatory Text Treasures, and contributions to online archive workshops. In the proposed talk we will present the different formats in more detail, and report on the resulting interaction with the community as well as the estimated reach. Based on these we will discuss which methods work well in which setting, where we can still improve in the future and which methods might become more important and interesting in the future.

- Poster Session - ESCAPE - addressing Open Science challenges (link) 8 November 2020 | 13:45 UTC

ESCAPE (European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures) is an EC H2020 project that addresses the Open Science challenges shared by the astronomy, astrophysics and astroparticle physics facilities encompassed within the ESFRI roadmap. This project is being done in the context of the European Open Science Cloud (EOSC) and involves activities to develop a prototype Data Lake and Science Platform, as well as to support an Open Source Software Repository, connect the Virtual Observatory framework to EOSC, and to engage the public in citizen science. We provide an overview of the current status of the project.

- Talk Session - Aladin Lite v3: behind the scenes of a major overhaul (link) 9 November 2020 | 07:30–07:45

Since its first version in 2013, Aladin Lite has gained significant traction and usage as an HiPS viewer running in the browser. Designed to be easy to embed, it is now used in more than fifty websites and portals in the professional astronomy community. Aladin Lite has been adopted as the sky visualisation component of popular applications: ESA Sky, ESO Science Archive or ALMA Science Archive. We present a major overhaul of Aladin Lite taking advantage of the GPU with WebGL, and which responds to requests of users, developers and integrators in a context where browser-based applications and science analysis platforms are increasingly important.

While keeping the strengths of the original code, Aladin version 3 will introduce several new features: support of multiple projections (Aitoff, Mollweide, Orthographic, Mercator), support of FITS tiles, display of FITS images, heatmaps visualisation of catalogue data, improved rendering pipeline and coordinates grids. We will give an overview on the architecture used to develop these new functionalities, based on existing Rust code transpiled to WebAssembly, a portable high-performance low-level bytecode for the web supported in all modern browsers. We will also outline the technical challenges and limitations we encountered. Short video footage sequences will demonstrate the existing prototype throughout the presentation. These improvements have been partially supported by the ESCAPE project and will also benefit to ipyaladin, the widget enabling the usage of Aladin Lite in Jupyter notebooks.

- BoF Session - Practical Provenance in Astronomy (link) 10 November 2020 | 19:00–20:30 UTC

Recently the IVOA released a standard to structure provenance metadata and several implementations are in development in order to capture, store, access and visualize the provenance of astronomy data products. This BoF will be focused on practical needs for provenance in astronomy. A growing number of projects express the requirement to propose FAIR data (Findable, Accessible, Interoperable and Reusable) and thus manage provenance information to ensure the quality, reliability and trustworthiness of this data. The concepts are in place, but now, applied specifications and practical tools are needed to answer concrete use cases. The session will discuss which strategies are considered by your projects (observatories or data providers) to capture provenance in your context and how you consider a end-user might query the provenance information to enhance her/his data selection and retrieval. The objective is to identify the development of tools and formats now needed to make provenance more practical.

Note: This activity, directly related to ESCAPE, includes contributions from members of not part of ESCAPE.

- Talk Session - On the capability to encoding gravitational-wave sky localizations with the Multi Order Coverage data structure: present and future developments (link) 11 November 2020 | 07:15–07:30 UTC

The IVOA standard Multi-Order Coverage map (MOC), a data structure based on the HEALPix tessellation of the sky, can be used to encode the enclosed area within a given probability level contour of a gravitational-wave (credible region) sky localization. MOC encoded credible regions can be created, visualised and manipulated using Aladin Desktop, allowing one to compare them with existing surveys and query the VizieR database. These sets of tasks can also be performed via python using the astropy affiliated package mocpy, efficiently displayed in javascript applications with Aladin Lite, and integrated within Jupyter notebooks through the ipyaladin widget.

In this talk, we present an enhanced MOC structure that allows us to include temporal information about gravitational-wave events. This data structure, the SpaceTime-MOC, provides us with an effective way to develop new multi-messenger data analysis tools that will have a crucial role when the third-generation interferometric gravitational wave observatories, such as the Einstein Telescope (ET), will begin in operation.

- Tutorial Session - On the capability to encoding gravitational-wave sky localizations with the Multi Order Coverage data structure: present and future developments (link) 11 November 2020 | 07:15–07:30 UTC

The Tutorial will have two parts: the first part will be dedicated to data discovery with "ObsTAP", a VO standard that was developed for this exact use case. Participants will get a little insight of how the standard works, and how it can be used from within software like TOPCAT, Splat-VO or Aladin. The second part of the tutorial will focus on how to use ObsTAP within python scripts with the help of the astropy affiliated package pyVO. We will define criteria, and let the script "find" feasable data services, and query those. We will use a multi messenger use case to emphasize the benefits of the used standards and tools.

- BoF Session - Radio/(sub-)mm data archives round table (link) 11 November 2020 | 13:00–14:30 UTC

With SKA precursor and pathfinder operations in full swing, radio and (sub-)mm astronomy is entering the era of super big data. The big questions is how to make (sub-)mm and radio data available to the astronomical community, preferably using FAIR (findable, accessible, interoperable and re-useable) principles. There are already a lot of efforts going on around the globe: facilities such as ALMA, LOFAR, MWA, NRAO and ASKAP are already publishing much of their data in the form of "science ready" image products, SKA regional centres are being formed and a radio astronomy interest group has been initiated within the IVOA. We want to use this BoF to bring everyone interested in this topic around one informal, friendly, virtual table to hear about and discuss the following questions: Where are different groups in their efforts to expose both visibility and science ready data? What is already there, maybe has been used for decades by traditional observatories? Which pieces of information or technology are still missing? Where do we want to go, what needs to happen next?
The BoF starts with short presentations from active players around the world and then look forward to a discussion with all attendees.

Note: This activity, directly related to ESCAPE, includes contributions from members of not part of ESCAPE.

ESCAPE Science Analysis Platform & ESCAPE Engagement and Communication

The ESCAPE Science Analysis Platform (ESAP) team is defining and implementing a flexible science platform for the analysis of open access data available through the EOSC environment. ESCAPE Engagement & Communication (ECO) is developing and managing a programme of public engagement and education via Citizen Science mass participation experiments.

- Poster Session - Discovering data with the ESCAPE Science Analysis Platform (link) 8 November 2020 | 15:35 UTC

ESCAPE presents a suite of online data discovery tools that have been developed for the ESCAPE Science Analysis Platform (ESAP). ESCAPE ESAP is designed to be flexible and extensible with a modular structure that encapsulates its different functional components. The ESAP backend is written in Python using the Django framework and communicates with a Javascript frontend via a RESTful API. One of the core components of the ESAP is a generic interface that enables discovery of Virtual Observatory (VO) resources by querying the VO registry. Once suitable VO resources have been discovered, ESAP provides a flexible interface to select and retrieve specific subsets of data and stage them for interactive or batch data analysis. The ESAP data discovery framework also enables support for non-VO data archives with minimal developer effort. As an example, we show how citizen science classification data from the Zooniverse platform can be accessed via ESAP.

Interested on ESCAPE latest developments? Check out our news section