Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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1.080 Topics available

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977 Locations available

693.932 PEOPLE
693.932 People People

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Show results for 693.932 people that are selected by your search filters.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (22/22 displayed)

  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.22.0citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.3citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.22.2citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.1citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.0citations
  • 2019ASKAP Science Data Processor software - ASKAPsoft Version 0.23.2citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.19.6citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.1citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.0citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.3citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.21.0citations
  • 2018ASKAP Science Data Processor software - ASKAPsoft Version 0.20.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.2citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.5citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.3citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.17.0citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.1citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.18.3citations
  • 2017ASKAP Science Data Processor software - ASKAPsoft Version 0.19.4citations

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Chart of shared publication
Mitchell, Daniel
22 / 24 shared
Bastholm, Eric
22 / 22 shared
Ord, Stephen
22 / 24 shared
Lenc, Emil
22 / 23 shared
Van Diepen, Ger
22 / 22 shared
Whiting, Matthew
22 / 23 shared
Khoo, Jonathan
22 / 22 shared
Collins, Daniel
22 / 22 shared
Wu, Xinyu
22 / 22 shared
Bannister, Keith
22 / 22 shared
Lahur, Paulus
22 / 22 shared
Maher, Tony
22 / 22 shared
Voronkov, Max
22 / 22 shared
Guzman, Juan
22 / 22 shared
Chart of publication period
2019
2018
2017

Co-Authors (by relevance)

  • Mitchell, Daniel
  • Bastholm, Eric
  • Ord, Stephen
  • Lenc, Emil
  • Van Diepen, Ger
  • Whiting, Matthew
  • Khoo, Jonathan
  • Collins, Daniel
  • Wu, Xinyu
  • Bannister, Keith
  • Lahur, Paulus
  • Maher, Tony
  • Voronkov, Max
  • Guzman, Juan
OrganizationsLocationPeople

document

ASKAP Science Data Processor software - ASKAPsoft Version 0.19.4

  • Mitchell, Daniel
  • Bastholm, Eric
  • Ord, Stephen
  • Lenc, Emil
  • Van Diepen, Ger
  • Whiting, Matthew
  • Khoo, Jonathan
  • Collins, Daniel
  • Wu, Xinyu
  • Marquarding, Malte
  • Bannister, Keith
  • Lahur, Paulus
  • Maher, Tony
  • Voronkov, Max
  • Guzman, Juan
Abstract

ASKAPsoft, the ASKAP Science Data Processor, provides data processing functionality, including:* Calibration * Spectral line imaging * Continuum imaging * Source detection and generation of source catalogs * Transient detectionASKAPsoft is developed as a part of the CSIRO Australian Square Kilometre Array Pathfinder (ASKAP) Science Data Processor component. ASKAPsoft is a key component in the ASKAP system. It is the primary software for storing and processing raw data, and initiating the archiving of resulting science data products into the data archive (CASDA).The processing pipelines within ASKAPsoft are largely written in C++ built on top of casacore and other third party libraries. The software is designed to be parallelised, where possible, for performance.ASKAPsoft is designed to be built and executed in a standard Unix/Linux environment and core dependencies must be fulfilled by the platform. These include, but are not limited to, a C/C++/Fortran compiler, Make, Python 2.7, Java 7 and MPI. More specific dependencies are downloaded by the ASKAPsoft build system and are installed within the ASKAPsoft development tree. Specific to the Debian platform, after a standard installation of Debian Wheezy (7.x) the following packages will need to be installed with apt-get:* g++ * gfortran * openjdk-7-jdk * python-dev * flex * bison * openmpi-bin * libopenmpi-dev * libfreetype6-dev * libpng12-devMore information regarding the building, installation and running of the software can be found in the README file in the root of the file structure that forms this collection.Source code can be accessed via the links in Related Materials section.-----A patch release covering the pipeline scripts and the processing software. The following bugs are fixed:* The pipeline configuration parameter FOOTPRINT_PA_REFERENCE willnow over-ride the value of footprint.rotation in the schedulingblock parset. Additionally, the scheduling block summary metadatafiles (created in the pipeline working directory) are now notregenerated if they already exist.* The metadata collection in the pipeline now does not fail if aFIELD in the measurement set has 'RA' in its name.* There was a memory leak in Selavy, causing an error to be thrownwhen dealing with fitted components, specifically when thenumGaussFromGuess flag was set to false and a fit failed. The codenow falls back to whatever the initial estimate for components was,even if that has fewer than the maximum number indicated bymaxNumGauss.* There was a half-pixel offset enforced in the location of thefitted Gaussian when fitting to the restoring beam whenimaging. This was resulting in a slightly incorrect restoringbeam.* If there are multiple MSs in the SB directory, one can be processedby giving MS_INPUT_SCIENCE its full path, setting the SB_SCIENCEparameter appropriately, and putting DIR_SB="".

Topics
  • impedance spectroscopy
  • mass spectrometry
  • atom probe tomography