Filter

Subjects

Content Types

Countries

AID systems

API

Data access

Database access

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 3 result(s)
HyperLeda is an information system for astronomy: It consists in a database and tools to process that data according to the user's requirements. The scientific goal which motivates the development of HyperLeda is the study of the physics and evolution of galaxies. LEDA was created more than 20 years ago, in 1983, and became HyperLeda after the merging with Hypercat in 2000
Country
EarthByte is an internationally leading eGeoscience collaboration between several Australian Universities, international centres of excellence and industry partners. One of the fundamental aims of the EarthByte Group is geodata synthesis through space and time, assimilating the wealth of disparate geological and geophysical data into a four-dimensional Earth model including tectonics, geodynamics and surface processes. The EarthByte Group is pursuing open innovation via collaborative software development, high performance and distributed computing, “big data” analysis and by making open access digital data collections available to the community.
The SuiteSparse Matrix Collection is a large and actively growing set of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.