ARACHNOLOGISCHE GESELLSCHAFT

New service of AraGes - Data Paper

The society Arachnologische Gesellschaft (AraGes) is offering a new form of publication – Data Papers, beginning with a first exemplary article/dataset published by the chair of the society Dr. Christoph Muster (Muster 2023). We offer the publication of scientific, i. e. systematically sampled data on spider assemblages (Araneae). Such a publication (data paper) includes one printed page in the journal with a DOI (Digital Object Identifier) which is also available in PDF format (Abstract document), one multipaged PDF file describing the content (Metadata document) and two data files (in csv format). All files are made available on two “landing pages” – the AraGes website and the BioOne digital library. The data will also be imported in the ARAMOB database of AraGes, eventually enriched and updated to the newest taxonomy (following the World Spider Catalog) and made available through the ARAMOB data portal. The ARAMOB database is managed by arachnologist of the SMNK under a cooperation agreement with AraGes in the database system Diversity Workbench which is regularly backed up and data are also archived by GFBio (German Federation for Biological Data). The data will thus be available also in a wider context together with comparable data. In this way several demands of the (civil) society and scientific community (represented by several scientific organisations, e.g. Deutsche Forschungsgemeinschaft, NFDI4BIODIVERSITY) on research and research data during the entire data life cycle will be met: open data, open access and data re-use (Forschungsdaten.info), fair use of data (FAIR Principles), uncovering dark data, combating the well-known scientific shortfalls which stand in the way of our knowledge about invertebrate biodiversity, ecology and their conservation and not least enabling data-driven approaches (knowledge discovery in databases).

Data files of the first Data Paper: Muster 2023 (doi: 10.30963/aramit6601)

Muster2023_obsdata

Muster2023_plotdata

 

Templates for Data Papers

Metadata

Plot data

Observation data