BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-europe-2024-academic-tra ck//speaker//LGVGFP BEGIN:VTIMEZONE TZID:EET BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1;UNTIL=20001231T220000Z TZNAME:EET TZOFFSETFROM:+0200 TZOFFSETTO:+0200 END:STANDARD BEGIN:STANDARD DTSTART:20021027T050000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:EET TZOFFSETFROM:+0300 TZOFFSETTO:+0200 END:STANDARD BEGIN:DAYLIGHT DTSTART:20020331T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:EEST TZOFFSETFROM:+0200 TZOFFSETTO:+0300 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-europe-2024-academic-track-7XTHAV@talks.staging.osgeo.or g DTSTART;TZID=EET:20240703T120500 DTEND;TZID=EET:20240703T121000 DESCRIPTION:The Open Geospatial Consortium (OGC) APIs are a new set of stan dards released in response to existing WxS standards which is considered a s a modern technology for data sharing over the internet. This study expl ores the transition from traditional geospatial service standards to moder n Open Geospatial Consortium (OGC) API standards in web applications by im plementing it in the field of urban development management. The main goal of this study is to explore the potential for enhancing web applications t hrough a comparative analysis of the integration of modern and traditional geospatial technologies based on their performance and practical implicat ions. \nThe research scope encompasses the design and development of a mod ern web application architecture\, involving database design and preparati on\, and automatic integration of data from various format\; implementatio n of geospatial services using both traditional standards and modern OGC A PI standards\, including the creation of a frontend website using Openlaye rs for the user. However\, the core focus was given on the comparative ana lysis of the traditional and modern geospatial services standards\, evalua ting data compatibility\, deployment processes\, and performance metrics w ith different levels of concurrent requests. \nThe study is structured int o two primary segments: an extensive theoretical evaluation of the standar ds\, and followed by a hands-on testing phase. involving the setup of both traditional and modern services separately while keeping the other compon ents (database and frontend) same in the architecture. In the database tie r\, PostGIS was employed\, Geoserver and Pygeoapi were used in the server section for publishing data in both traditional (WxS) and modern (OGC API) standards to the user tier. OpenLayers was used for the frontend to visua lize the data for users.\nDatabase design and preparation were accomplishe d using Geodjango and PostgreSQL\, and automatic data integration was cond ucted using Python. The ALKIS (Authoritative Real Estate Cadastre Informat ion System of Germany) includes both spatial and non-spatial information e ncoded in NAS (i.e.\, the standards-based exchange interface defined by th e Surveying Authorities of Germany) format using Extensible Markup Langu age (XML)\, served as the primary data source in this study with essential details such as street names\, house numbers\, and land parcel id. The co mparison (Geoserver and Pygeoapi) platforms considered key findings\, less ons learned\, data format compatibility\, and the evaluation of the instal lation process through literature review. Performance metrics were measur ed through hands-on testing in terms of rendering time\, overall performan ce of the website for different zoom level for different scale of vector f eatures. Testing also included different data source formats such as PostG IS\, GeoPackage (gpkg)\, and Shapefile (shp)\, with a focus on how perform ance varied with the change of the data source in the front end. Apache Jm eter and Google Chrome developer tools like network and lighthouse were us ed to get the rendering data from the front end. Usability evaluations are currently underway to gain user perspectives on aspects like data retriev al speed\, map rendering speed\, and the ease of use (e.g.\, panning\, zoo ming\, popups) in comparison to the previous system.\nIn a theoretical com parison Geoserver\, a well-established and widely adopted open-source plat form with an organized Graphical User Interface (GUI)\, boasts robust secu rity features with support for various authentication methods and precise access control. With a rich history and a large user community\, Geoserver provides extensive documentation and support resources. It supports a div erse array of data stores\, including popular databases and file-based for mats. On the other hand\, Pygeoapi\, a newer but increasingly popular proj ect\, emphasizes simplicity and ease of use. Offering modern technologies like the OpenAPI standard for a RESTful API\, Pygeoapi supports various da ta stores\, including PostgreSQL/PostGIS and Elasticsearch. Installation i s straightforward\, leveraging Python and its dependencies. While Geoserve r stands out for its comprehensive feature set\, including support for OGC standards and numerous plugins\, Pygeoapi focuses on being lightweight an d customizable according to OGC API standards.\nBased on the extensive han ds-on testing\, the analysis reveals persistent trends in rendering times across different scenarios. Pygeoapi consistently demonstrates higher rend ering times compared to both Geoserver (WFS) and Geoserver (WMS). The fluc tuation in rendering times remains relatively uniform as the zoom level in creases from 14 to 18. However\, as the number of features escalates from 4891 to 23319\, both Pygeoapi (1.55s to 7.56s) and Geoserver WFS (454ms to 2.19s) exhibit a proportional increase in rendering time. Remarkably\, Ge oserver (WMS) showcases notable stability in rendering times across variou s zoom levels and feature counts\, attributed to its tile-based approach. The observed linear correlation between feature count and rendering time s uggests a scalability factor affecting both Pygeoapi and Geoserver. Conseq uently\, users may need to consider factors beyond rendering times\, such as ease of use\, scalability\, and available features\, when making a choi ce between Pygeoapi and Geoserver for their specific spatial data needs. M oreover\, concerning different data formats\, it becomes apparent that Pos tGIS consistently outperforms SHP\, JSON\, WFS\, and GPKG in Pygeoapi. In Geoserver\, SHP and GPKG exhibit superior performance compared to other fo rmats. These findings underscore the importance of considering the nuances of data formats when optimizing the performance of spatial data services. To overcome the issue of prolonged rendering times in Pygeoapi\, especial ly when managing substantial amounts of GeoJSON data\, a viable solution l ies in incorporating vector tiles. The adoption of vector tiles led to a s ubstantial reduction in rendering times (from 5.6s to 898ms) by transmitti ng pre-styled and pre-rendered map data. This approach enhances efficiency in visualizing data on the client side\, demonstrating a significant impr ovement in performance. \nIn conclusion\, at the end this research will e ndeavour to provide actionable insights towards the effective integration of geospatial technologies\, with the goal of narrowing the divide between well-established standards and emerging APIs within the dynamic realm of web applications. DTSTAMP:20260508T232226Z LOCATION:Omicum SUMMARY:Modernizing Geospatial Services: An investigation into modern OGC API implementation and comparative analysis with traditional standards in a Web application - Sudipta Chowdhury URL:https://talks.staging.osgeo.org/foss4g-europe-2024-academic-track/talk/ 7XTHAV/ END:VEVENT END:VCALENDAR