Heritage Science Workshop on data interoperability for Spectrometry – Online on December 14-16 2022

Heritage Science Workshop on data interoperability for Spectrometry – Online on December 14-16 2022

The Heritage Science workshop is an initiative of the DIGILAB working group of the IperionHS projectResinfra-EU-LAC and ANTECIPA as part of the SEM-EDS data interoperability pilot.

The basic concepts of Scanning Electron Microscopy (SEM) and chemical element identification using x-ray spectrometers (EDS: Energy Dispersive X-ray Spectrometer and WDS: Wavelength Dispersive X-ray Spectrometer) will be discussed, and demonstrations with practical aspects plus practical aspects of data interoperability and good practices will be addressed.

The main lecturer is Prof. Dr Nestor Zaluzec from Argonne National Laboratory, Northern Illinois University and the University of Illinois at Chicago. Dr Nicholas Ritchie from NIST will also give a talk.

The tentative program, especially the demonstration sessions, might suffer slight time shifts depending on the interest and discussions.

The official language of the workshop will be English.

The scheduled time zone is Brasilia, which is 3 hours ahead of Chicago and 4 hours behind Central Europe (Brussels, Rome, etc.)

Registration until December 13, 2022

Check the program here, but be aware that the times are for Brasilia. So 4 hours less than Central European Time (CET).


Call for Papers: 1st Sci-K International Workshop, deadline 25th January 2021

Sci-K – the 1st International Workshop on Scientific Knowledge Representation, Discovery, and Assessment in conjunction with The Web Conference (WWW) will be held in Ljubljana, Slovenia in April 19-23, 2021.

The call for papers has been published with a submission deadline of January 25, 2021.

Sci-K is calling for high-quality submissions around the three main themes of research related to scientific knowledge: representation, discoverability, and assessment. Topics of interest include, but are not limited to:

a) Representation

  • Data models for the description of scholarly data and their relationships.
  • Description and use of provenance information of scientific data.
  • Integration and interoperability models of different data sources.

b) Discoverability

  • Methods for extracting metadata, entities and relationships from scientific data.
  • Methods for the (semi-)automatic annotation and enhancement of scientific data.
  • Methods and interfaces for the exploration, retrieval, and visualisation of scholarly data.

c) Assessment

  • Novel methods, indicators, and metrics for quality and impact assessment of scientific publications, datasets, software, and other relevant entities based on scholarly data.
  • Uses of scientific knowledge graphs and citation networks for the facilitation of research assessment.
  • Studies regarding the characteristics or the evolution of scientific impact or merit.

Further information