TEAM 8: Exposing GUF Metadata as DUV in the GeoDCAT-ap Output of GeoNetwork

TEAM LEADER: Paul van Genuchten

TEAM MEMBERS: Looking for organisations that have GUF metadata (or other User Feedback on datasets)

PROJECT IDEA: In the scope of ‘ELISE tools’ the GUF (http://www.opengeospatial.org/standards/guf) schema has recently been added to GeoNetwork (https://github.com/metadata101/guf10). GUF allows to store User Feedback linked to datasets. W3C has released a DUV schema (https://www.w3.org/TR/vocab-duv) for User Feedback that links into DCAT. Goal of this project is to develop a DUV export of GUF as part of the GeoDCAT-ap export capability of GeoNetwork. And if feasible also create a schema.org/review output as part of the schema.org/Dataset annotations in the metadata HTML visualisation.

TEAM 7: Light Weighted INSPIRE Harmonization Using Metadata in GeoNetwork

TEAM LEADER: Paul van Genuchten

TEAM MEMBERS: Antonio Cerciello, … I’m looking for organisations that have non-harmonised datasets that are eligible for INSPIRE and are willing to go through a process of harmonisation using this light weighted approach.

PROJECT IDEA: These days many data providers implement INSPIRE data harmonization at the end of the data pipeline. The harmonized data is not used by the organisation itself. This approach has a big risk. In the harmonization process data may get lost or be placed out of context. In this experiment I want to experiment with a light weight harmonization approach based on linked data principles.

The idea is to extend the iso19110 feature catalog metadata of INSPIRE source datasets with references to relevant INSPIRE ontologies (https://github.com/inspire-eu-rdf/inspire-rdf-vocabularies) in such a way that any client software would be able to take the source dataset (as-is) combined with the extended iso19110 metadata to create basic INSPIRE GML.

This work builds on this project https://github.com/geonetwork/core-geonetwork/wiki/Use-iso19110-in-GetFeatureinfo-response-visualisation

TEAM 6: Discovery and Using Copernicus Marine Environment Monitoring Service (CMEMS) in DataBio Fishing Pilot

TEAM LEADER: Dmitrij Kozuch

PROJECT IDEA: The idea is to explore which data provided by CMEMS could be of use in DataBio fishing pilot and in which way they could be used (it is important to be able to search the data by their metadata – dataset name, time extent, spatial extent etc..).

The task will logically follow the efforts, that were made during Prague hackathon in January.

TEAM 5 Open Land Use Metadata Harvesting on NextGEOSS

TEAM LEADER: Dmitrij Kozuch

PROJECT IDEA: The idea is to create metadata for the Open Land Use map for the all european municipalities (currently in the metadata catalogue: https://micka.lesprojekt.cz are only nuts regions and municipalities in Austria, Czech Republic and Flanders region of Belgium). As well as creating new metadata there will be made some refinement of the metadata based on this document, that is written by metadata experts.

As it is possible to output metadata according to GeoDCAT-AP standard (see this example) – the metadata can be used for testing in NextGeoss CKAN Data Hub by team 2.2.

TEAM 4: CKAN Extension to Integrate User Feedback with NiMMbus

TEAM LEADER:   (Viderum/NextGEOSS data hub/Berlin)

TEAM MEMBERS: Jovanka

PROJECT IDEA:  In the Pilsen hackathon a first extension for CKAN was coded to integrate the NiMMbus user feedback system of the University of Barcelona  for spatial datasets. Goal of the project is to test the maturity to make it generally available.
(Must be checked before with Jovanka after 26th of February, 2018, and UAB

TEAM 3: Traditional Metadata Standards and Community Metadata

TEAM LEADER:  (Viderum/NextGEOSS data hub/Berlin)

PROJECT IDEA: The traditional metadata standards like Dublin Core, CDAT, GeoDCAT or ISO have limited schemas which are not sufficient for communities like climate or biodiversity researchers with their Essential Climate Variables or their Essential Biodiversity Variables (EVB.

Goal of the project is a proof of concept to enrich traditional metadata standards with the CKAN “system fields” mechanism so that

  • sources get additional information for EBV metadata while harvesting
  • harvested metadata can be filtered by EV content
  • APIs like OpenSearch can provide additional search criteria from the harvested EBVs

TEAM 2: GeoDCAT in NextGEOSS CKAN Data Hub

TEAM LEADER: Wolfgang Ksoll (Viderum/NextGEOSS data hub/Berlin)

TEAM MEMBERS: Marek Splichal, Stepan Kafka, Tomas Reznik

PROJECT IDEA: Today the data hub of NextGEOSS harvests metadata from sources on a proprietary basis where connectors are programmed to harvest e.g. from different sources of the Copernicus Sentinel missions as they are provided and can be searched in the data hub with a web interface or with programmatic interface like some NextGEOSS pilot projects do.
The task of the project is to apply the GeoDCAT-CKAN-extension to a test version of the NextGEOSS data hub und to study the consequences:

  • harvesting GeoDCAT metadata
  • searching in the hub webbased
  • searching with OpenSearch interface
  • new possibilities and access points with RDF and step in the door of the semantic web world

TEAM 1: Easy-to-Use Satellite Images Discovery in a Map Viewer

TEAM LEADER: Tomáš ŘEZNÍK (Masaryk University/Lesprojekt/Wirelessinfo/HSRS)

TEAM MEMBERS: Šimon LEITGEB (Masaryk University/Lesprojekt/Wirelessinfo), Štěpán KAFKA (HSRS), Karel CHARVÁT (Plan4All/Lesprojekt/Wirelessinfo/HSRS), other participants are warmly welcomed

PROJECT IDEA: Discoverability of geospatial data and services (aka resources) has been considerably improved during the last decade as several catalogues have been developed, fulfilled with metadata and being in daily use for many users. Nevertheless, it means that a user typically works with her/his GIS system and opens a catalogue as a specialized application. Such paradigm may suit to geospatial experts.

On the contrary, a laymen expects one simple tool for maps viewing. (S)he does not like to bother with another application to discover which other geospatial resources are available for a currently zoomed area.

The aim of this team is therefore to develop an easy-to-use satellite images discovery integrated directly in a map viewer. We intentionally do not use the term ‘catalogue’ as (1) we would like to erase borders between data and metadata in our application and (2) we would like to retain catalogues in a way they are.

Relevant resources to a currently zoomed area will appear through links to satellite programmes’ APIs, such as Copernicus’ Open Access Hub. The developed application will be based on OpenLayers 4-based framework called HSLayers NG (see https://github.com/hslayers/hslayers-ng).