SwissCollNet s’engage à améliorer l'accessibilité de ses collections. Une vision commune et une stratégie à long terme favoriseront l'utilisation des collections d'histoire naturelle pour la recherche, l'enseignement et la société.

Image : OscarLoRo,

Data standards

Towards integrated global data infrastructures

Over the past ten years, several national and international programmes for the digitisation of natural history collections were initiated, most notably iDigBio (Integrated Digitized Biocollections) in the United States and DiSSCo (Distributed System of Scientific Collections) in Europe. These initiatives facilitate collaborations with and between museums to build research infrastructure for the integration of specimen data across multiple institutions as well as fostering the adoption and implementation of standards and best practices. SwissCollNet is in close contact with representatives of DiSSCo and standards and best practices are being shared.

Data standards for projects within SwissCollNet

Two main data exchange standards exist within the context of natural history collections: the Darwin Core standard (DwC), originally developed for the exchange of biodiversity data, and the Access to Biological Collection Data schema (ABCD; optionally Extended For Geosciences, ABCDEFG) for the exchange of specimen data of natural history collections. The development of both standards started around the turn of the millennium, and both have been approved by the Biodiversity Information Standards association (formerly known as the Taxonomic Databases Working Group, TDWG), in the meantime.

Projects funded by SwissCollNet must follow one of these two standards. Corresponding recommendations are published in the “Handbook on natural history collections management – A collaborative Swiss perspective” (chapter 4).

The FAIR data principles

To be of maximum benefit to research and society, data management should follow the so-called FAIR data principles which are findability, accessibility, interoperability, and reusability. The FAIR data principles are written in a very general form to allow for maximum applicability.

Projects funded by SwissCollNet must follow the FAIR data principles.

Guide collections
Image : Akademien Schweiz

Follow recommendations from the Handbook (chapter 4)!