Filter
Reset all

Subjects

Content Types

Countries

API

Data access

Data access restrictions

Database access

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 2 result(s)

SeaDataNet

Pan-European Infrastructure for ocean & marine data management

Subject(s)
Content type(s)
Country
SeaDataNet is a standardized system for managing the large and diverse data sets collected by the oceanographic fleets and the automatic observation systems. The SeaDataNet infrastructure network and enhance the currently existing infrastructures, which are the national oceanographic data centres of 35 countries, active in data collection. The networking of these professional data centres, in a unique virtual data management system provide integrated data sets of standardized quality on-line. As a research infrastructure, SeaDataNet contributes to build research excellence in Europe.

Bicocca Open Archive Research Data

BOARD

Subject(s)
Content type(s)
Country
BOARD (Bicocca Open Archive Research Data) is the institutional data repository of the University of Milano-Bicocca. BOARD is an open, free-to-use research data repository, which enables members of University of Milano-Bicocca to make their research data publicly available. By depositing their research data in BOARD researchers can: - Make their research data citable - Share their data privately or publicly - Ensure long-term storage for their data - Keep access to all versions - Link their article to their data