S2Innovation, Kraków, Poland
ESRF, Grenoble, France
MAX IV Laboratory, Lund University, Lund, Sweden
Tango Controls is successfully applied at more than 40 scientific institutions and industrial projects. These institutions do not only use the software but also actively participates to its development. The Tango Community raised several projects and activities to support collaboration as well as to make Tango Controls being easier to start with. Some of the projects are led by S2Innovation. These projects are: gathering and unifying of Tango Controls documentation, providing a device classes catalogue and preparation of a so-called TangoBox virtual machine. Status of the projects will be presented as well as their impact on the Tango Controls collaboration.
S2Innovation, Kraków, Poland
ESRF, Grenoble, France
MAX IV Laboratory, Lund University, Lund, Sweden
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
More than 40 laboratories use Tango Controls as a framework for their control systems. During its 18 years of existence, Tango Controls has evolved and matured. The latest 9.3.3 release is regarded as the most stable and feature-reach version of the framework. However, it makes use of already outdated CORBA technology which impacts all the stack, from the low-level transport protocol up to the client API and tools. The Tango Community decided to move forward and is preparing for so-called Tango Controls v10. Tango v10 is meant to be more a new implementation of the framework than a release of new features. The new implementation shall make the code easier to maintain and extend as well as remove legacy technologies. At the same time, it shall keep the Tango Controls objective philosophy and allows the new implementation to coexist with the old one at the same laboratory. The first step in the process is to provide a formal specification of current concepts and protocol. This specification will be base for the development and verification of new source code. Formal specification of Tango Controls and its purpose will be presented along with used tools and methodologies.
ESRF, Grenoble, France
ESS, Copenhagen, Denmark
CERIC-ERIC, Trieste, Italy
ILL, Grenoble, France
EuXFEL, Schenefeld, Germany
ELI-DC, Brussels, Belgium
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
ELI-ALPS, Szeged, Hungary
Photon and Neutron sources are producing more and more petabytes of scientific data each year. At the same time scientific publishing is evolving to make scientific data part of publications. The Photon and Neutron Open Science Cloud (PaNOSC*) project is a EU financed project to provide scientific data management for enabling Open Science. Data will be managed according to the FAIR principles. This means data will be curated and made available under an Open Data policy, findable, interoperable and reusable. This paper will describe how the European photon and neutron sources on the ESFRI** roadmap envision PaNOSC as part of the European Open Science Cloud***. The paper will address the issues of data policy, metadata, data curation, long term archiving and data sharing in the context of the latest developments in these areas.
*https://panosc.eu
**https://www.esfri.eu/
**https://ec.europa.eu/research/openscience/index.cfm?pg=open-science-cloud
EuXFEL, Schenefeld, Germany
BRC, Szeged, Hungary
ESRF, Grenoble, France
University of Southampton, Southampton, United Kingdom
The EGI Foundation, Amsterdam, The Netherlands
ILL, Grenoble, France
ESS, Copenhagen, Denmark
DESY, Hamburg, Germany
Jupyter notebooks are executable documents that are displayed in a web browser. The notebook elements consist of human-authored contextual elements and computer code, and computer-generated output from executing the computer code. Such outputs can include tables and plots. The notebook elements can be executed interactively, and the whole notebook can be saved, re-loaded and re-executed, or converted to read-only formats such as HTML, LaTeX and PDF. Exploiting these characteristics, Jupyter notebooks can be used to improve the effectiveness of computational and data exploration, documentation, communication, reproducibility and re-usability of scientific research results. They also serve as building blocks of remote data access and analysis as is required for facilities hosting large data sets and initiatives such as the European Open Science Cloud (EOSC). In this contribution we report from our experience of using Jupyter notebooks for data analysis at research facilities, and outline opportunities and future plans.
ESRF, Grenoble, France
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy
ALBA-CELLS Synchrotron, Cerdanyola del Vallès, Spain
PSI, Villigen PSI, Switzerland
As more and more scientific data are stored at photon sources there is a growing need to provide services to access to view, reduce and analyze the data remotely. The Calipsoplus* project, in which all photon sources in Europe are involved in, has recognized this need and created a prototype portal for Data Analysis as a Service. This paper will present the technology choices, the architecture of the blueprint, the prototype services and the objectives of the production version planned in the medium term. The paper will cover the challenges of building a portal from scratch which covers the needs of multiple sites, each with their own data catalogue, local computing infrastructure and different workflows. User authentication and management are essential to creating a useful but sustainable service.
*http://www.calipsoplus.eu/
ESRF, Grenoble, France
SOLEIL, Gif-sur-Yvette, France
SKA Organisation, Macclesfield, United Kingdom
ALBA-CELLS Synchrotron, Cerdanyola del Vallès, Spain
NEXEYA Systems, La Couronne, France
S2Innovation, Kraków, Poland
MAX IV Laboratory, Lund University, Lund, Sweden
SARAO, Cape Town, South Africa
IK, Moscow, Russia
STFC/DL, Daresbury, Warrington, Cheshire, United Kingdom
Elettra-Sincrotrone Trieste S.C.p.A., Basovizza, Italy