Dear authors, dear colleagues, 

Your are hereby invited to submit a paper to the special edition on map production and geoinformation management with the title “Modern Map Production and Geospatial Artificial Intelligence” in the International Journal of Cartography. Please take note of important dates. We have included the “production dates” as to inform you of the complete process. All submissions will be double blind reviewed to ensure the academic integrity of your submission and the journal. The best 6 to 8 articles will be selected for this special edition. We are looking forward to your contribution.

Regards,  Markus Jobst and Peter Schmitz 

Special edition editors and co-chairs of the ICA Commission on Map Production and Geoinformation Management.

Modern map production is confronted with an increasing number of data sources, a variety of use cases and continuously changing IT environments. Digitalization enables smart implementations and prepares artificial intelligence. The geospatial foundation for automatisation and artificial intelligence is a service-oriented architecture, in which no human decisions are needed for selecting the right content. Instead metadata, codelists, registries, ontologies and graphs deliver the basic building blocks to establish a network for machine learning and geospatial artificial intelligence.

Geospatial artificial intelligence (geoAI) with its principal task of data analysis and extraction, combines innovations in spatial science and artificial intelligence methods. These methods cover deep learning, data mining as well as high-performance computing to extract information from spatial big data. GeoAI researches the ability to connect large amounts of big spatial and temporal data in a variety of standardized formats.

Today the way how maps are produced and geoinformation is managed seems to change. The geospatial community, like many other IT-depending communities, face rapid technological developments, open geoinformation access and wide distribution, user participation for content creation and semantic cross-domain networks. All these aspects have relevant impact on the requirements of the system design, architecture principles, interface specification or even sustainable map-access provision and archiving perspectives. From this comprehensive point of view the paradigm of map production and geoinformation management changes.

The confrontations in modern map production lead to considerations of

handling logistical dependencies
spatial swarm intelligence and its mapping use cases 
making use of natural processing languages 
machine learning (ML) for map production 
information preparation and data wrangling 
alternative methods for embedding resilient and reliant IT infrastructures for map production 
standardization processes and implementation success 
map production algorithms 
quality management  
archiving aspects of modern map production 
map production and the success of maps 

New dates need to be confirmed

GeoAI, service-oriented architecture, logistics of distributed spatial data, spatial big data, workflows, collaborations, cloud-based services, dissemination, open data, open sources