Andrei Sima
I am a GIS specialist with great technical and management skills, continuously looking for new challenges.
With a big background in scientific research and writing I’ve managed to gather an important know-how in GIS domain. I’ve used all my knowledge from my past years, learning different GIS platforms, using many methods and workflows for map data management, spatial analysis tasks, open-data project and so on.
I’ve started to understand easily the automotive and self-driving cars phenomenon after working with different navigation devices and software platforms based on worldwide-known navigation databases and structures.
All my experience with big map data shaped my analytical and critical thinking, developing also my data quality and detail-oriented skills.
Taking part in different GIS projects and working in automotive companies helped me a lot in managing my own map data and GIS consultancy company.
Now, I’m focused on growing my programing and technical skills and teaching in parallel my colleagues all the awesome and great things I know related to GIS and automotive domain.
My GIS work related experience in years: over 15 years of GIS experience in different GIS software and databases, over 8 years of remote team managing and working experience, over 8 years of OpenStreetMap corporate editing, over 5 years of scientific and technical writing experience, over 5 years of using no-code & low-code in GIS developing, over 2 years of QA and GPS map data validation experience, over 1 year of dataset training and managing for road traffic machine learning.
Sessions
OpenStreetMap (OSM) is a widely used open-source mapping platform that supports diverse applications across sectors such as humanitarian aid, public transportation, logistics, and automotive navigation. Given its collaborative nature and global scale, maintaining high data quality is essential for ensuring reliable and accurate map usage. To address this, the OSM community has developed various tools and methodologies to detect, analyze, and resolve data quality issues.
This presentation will explore key quality assurance techniques used in the OSM ecosystem, with a focus on AtlasChecks and custom database queries. We will demonstrate how these tools help identify inconsistencies, validate data according to community editing guidelines, and support large-scale data maintenance. Additionally, we will highlight how Kaart contributes to these efforts by creating and using automated checks and tailored queries to assist communities in achieving high-quality geospatial data.
Attendees will gain practical insights into the tools and workflows that drive continuous improvement in OSM data quality and learn how they can apply similar strategies in their own mapping projects.