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Modular System for Shelves and Coasts

Viable North Sea (ViNoS) is an Agent-based Model (ABM) of the German Small-scale Fisheries. As a Social-Ecological Systems (SES) model it focusses on the adaptive behaviour of fishers facing regulatory, economic, and resource changes. Small-scale fisheries are an important part both of the cultural perception of the German North Sea coast and of its fishing industry. These fisheries are typically family-run operations that use smaller boats and traditional fishing methods to catch a variety of bottom-dwelling species, including plaice, sole, and brown shrimp.

Fishers in the North Sea face area competition with other uses of the sea---long practiced ones like shipping, gas exploration and sand extractions, and currently increasing ones like marine protection and offshore wind farming (OWF). German authorities have just released a new maritime spatial plan implementing the need for 30% of protection areas demanded by the United Nations High Seas Treaty and aiming at up to 70 GW of offshore wind power generation by 2045. Fisheries in the North Sea also have to adjust to the northward migration of their established resources following the climate heating of the water. And they have to re-evaluate their economic balance by figuring in the foreseeable rise in oil price and the need for re-investing into their aged fleet.

KPI repo for Service webODV from AWI

Starting point: Documentation and configuration of HTTPD WebDAV for operators.

Toolset to harvest (meta)data from collaborating data providers within the Helmholtz association to be included in the UnHIDE-KG. The linked data in the form of schema.org jsonld is aggregated and uplifted in data pipelines to be included into a single large knowledge graph (KG).

The source code of the HIFIS homepage. --> https://hifis.net

This repository contains the code for the front end of unHIDE, the Helmholtz Knowledge graph. This includes code how to setup a webpage for search, APIs and the backend of the User interface with SOLR and Indexer.

The project started from the work and code of https://github.com/iodepo/oih-ui and https://github.com/iodepo/oih-ui-docker. We are thankful for their work.