In order to enable an iCal export link, your account needs to have an API key created. This key enables other applications to access data from within Indico even when you are neither using nor logged into the Indico system yourself with the link provided. Once created, you can manage your key at any time by going to 'My Profile' and looking under the tab entitled 'HTTP API'. Further information about HTTP API keys can be found in the Indico documentation.
Additionally to having an API key associated with your account, exporting private event information requires the usage of a persistent signature. This enables API URLs which do not expire after a few minutes so while the setting is active, anyone in possession of the link provided can access the information. Due to this, it is extremely important that you keep these links private and for your use only. If you think someone else may have acquired access to a link using this key in the future, you must immediately create a new key pair on the 'My Profile' page under the 'HTTP API' and update the iCalendar links afterwards.
Permanent link for public information only:
Permanent link for all public and protected information:
Recent Developments & Results on Networking & Machine Learning for Science
Founded in 1984, and working in support of the LHC program since 1994, the Caltech Network Team within the Caltech LHC HEP group is a worldwide leader in scientific network development, production, and operations. The Caltech team is collaborating with university teams from Michigan, UT Arlington, Vanderbilt, Victoria in Canada, UNICAMP and the State University of Sao Paulo in Brazil, and laboratory groups engaged in network development from the DOE’s Lawrence Berkeley National Laboratory, Fermilab, and Brookhaven National Lab. The team is working with many network partners as well, including DOE’s ESnet, Internet2, CENIC, Florida Lambda Rail, MiLR and other leading US regional networks, BCNET in Canada, leading exchange points including Starlight, AmLight, NetherLight, and CERNLight, along with GEANT, SURFNet and other European research and education networks, as well as the RNP national network and the ANSP (Sao Paulo) regional network in Brazil, on novel network system development and optimization projects focused on LHC and related applications for the last 15+ years.
In the past 3 years the group is developing solutions for science challenges using Machine Learning in collaboration with FNAL, LBNL, CERN as well as NVIDIA & SuperMicro among others. We also work with Unity3D NovaVR and FNAL to create science content for VR platforms and develop powerful data visualization solutions. In the future we envision plugging an AI engine at the front end and creating a system for monitoring and interacting with multi-dimensional data in novel way. During SC16 we have a CMS.VR demo.