Chaos Computer Club - archive feed

Koennen uns Werkzeuge aus dem Ethical Hacking oder Bug Bounty Hunter Bereich bei unserer taeglichen Arbeit mit Webapplikationen unterstuetzen? Koennen uns Werkzeuge aus dem Ethical Hacking oder Bug Bounty Hunter Bereich bei unserer taeglichen Arbeit mit Webapplikationen unterstuetzen? Im Umgang mit gekauften Closed Source Web Applikationen die auf Basis von WebSphere Application Server und Kubernetes laufen, geht es in vielen Support Fällen um die Reproduzierbarkeit und Javascript Analysen im Browser. Im Gegensatz zu 2010 tauchen viele Fehler nicht mehr im Serverlog auf, sondern muessen auf den Clients im Browser untersucht werden. Welche Tools verwende ich taeglich um automatisiert zu pruefen ob Updates keine Fehler verursachen (Load Testing), Browser sessions aufzuzeichnen oder zu untersuchen (Intercept Proxies), Kommandozeilentools um Browserantworten weiterzuverarbeiten (JSON). Die Automatisierung von Installationen und Updates hilft gerade bei der Reproduzierbarkeit enorm (Ansible, Terraform). Gerade bei gekauften Produkten bekommt man oft nur verzoegert Updates und muss sich um Containerupdates auch mal selbst kuemmern. Wie sieht man ohne Dockerfile welche Aenderungen in einem Container bei der Erstellung gemacht wurden? Trivy und Dive helfen beim Finden von Vulnerabilities und Dive bei der Analyse der Container. about this event: https://programm.froscon.org/2022/events/2782.html

MySQL 8.0 wird etwa alle drei Monate akualisiert. Dabei kommen immer wieder kleiner (und größere) Funktionen dazu die teils erheblich Admins das Leben vereinfachen (MySQL Dump vs. MySQL Shell Dump) In diesem Vortrag schauen wir uns die Änderungen der letzten zwei (Corona) Jahre in der Tiefe an... MySQL 8.0 wurde bereits in 2018 als finale Version zur Verfügung gestellt und geht bald ins 5te "Lebensjahr". Allerdings wurde mit praktisch jedem Update/Patch auch neue Funktionen und Erweiterungen mit ins Produkt eingebracht. In diesem Vortrag wollen wir uns die Änderungen während Corona mal etwas genauer anzuschauen: - MySQL InnoDB ReplicaSet - Binlog Compression - Consistant reads for InnoDB Cluster - MySQL Shell, Cloning, Shell Dump, Table Utils - Invisible Columns - InnoDB ClusterSets für DR Anwendungsfälle - MySQL Operator für Kubernetes - MySQL Cloud und MySQL HeatWave für real-time Analysen - Instant add/rename/drop column - uvm. about this event: https://programm.froscon.org/2022/events/2764.html

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM native images play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world. Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM native images play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world. about this event: https://programm.froscon.org/2022/events/2729.html

OpenStreetMap has many details about streets, but applications rendering or simulating lane-level detail face many challenges: determining lane properties along one street, calculating geometry of streets and junctions, handling motorway entrances, dual carriageways, dog-leg intersections, placement tags, and parallel sidewalks and cycleways. osm2streets is a new effort to produce a cleaned-up street network graph with geometry. It's a Rust library, designed to be integrated with browser apps like iD or native/Java apps like JOSM. The goal is to consolidate community efforts to solve these data transformation problems, and to produce high-detail vector maps and apps for improving lane tagging with immediate visual feedback. Start using this at https://osm2streets.org about this event: https://2022.stateofthemap.org/sessions/9NHQQM/

Der Vortrag startet mit einem Einstieg zur Rechenzentrumsautomatisierung mit Foreman und Katello. Danach wird das "Foreman SCC Manager" Plugin vorgestellt, welches die Bereitstellung von Softwarepaketen und Errata für verwaltete Systeme, auf welchen SUSE Linux Enterprise Server läuft, vereinfacht. "SCC" steht hier für SUSE Customer Center. Im Zuge unseres Open Source-Engagements wird dieses Plugin von der ATIX AG laufend gewartet und weiterentwickelt. Im Moment findet eine umfassende Umgestaltung der Produktseite statt, welche wir Ihnen vorstellen werden. = Foreman SCC Manager: Rechenzentrumsautomatisierung von SLES Der Vortrag startet mit einem Einstieg zur Rechenzentrumsautomatisierung mit Foreman und Katello. Danach wird das "Foreman SCC Manager" Plugin vorgestellt, welches die Bereitstellung von Softwarepaketen und Errata für verwaltete Systeme, auf welchen SUSE Linux Enterprise Server läuft, vereinfacht. "SCC" steht hier für SUSE Customer Center. Im Zuge unseres Open Source-Engagements wird dieses Plugin von der ATIX AG laufend gewartet und weiterentwickelt. Im Moment findet eine umfassende Umgestaltung der Produktseite statt, welche wir Ihnen vorstellen werden. Für den Vortrag benötigen Sie kein spezielles Vorwissen, von Vorteil sind aber Erfahrungen im Bereich der Systemadministration und der Automatisierung von IT-Umgebungen. Im Vortrag wird das Foreman Web UI gezeigt und wie mit Hilfe des Foreman SCC Managers SUSE Produkte anlegt werden können. == Foreman und Katello Foreman ist ein Lifecycle-Management Tool für physische und virtuelle Systeme. Sie können damit wiederkehrende Aufgaben automatisieren, Systeme ausrollen und konfigurieren, und versionierte Inhalte wie Softwarepakete und Errata auf angebundene Systeme verteilen. Katello ist als Foreman Plugin für Inhalte wie Softwarepakete, Puppet Module, oder Errata verantwortlich. Diese können manuell hochgeladen werden oder -etwas bequemer- aus online verfügbaren Quellen periodisch synchronisiert werden. == Foreman SCC Manager Die ATIX AG hat das Foreman SCC Manager Plugin entwickelt, um Foreman Instanzen mit SCC Accounts zu verbinden. Damit wird die Verwaltung von SUSE Inhalten signifikant vereinfacht. Dies ist unabkömmlich für alle, die Foreman und Katello zum Ausrollen und Verteilen von Inhalten an Systemen mit SLES nutzen. SCREENSHOT "foreman_scc_manager_list_of_suse_products_in_katello.png" Das Plugin fügt der Foreman Web UI eine neue Seite für SUSE Subskriptionen hinzu, wo ein SCC Account hinterlegt werden kann. Sie können damit SUSE Produkte auswählen und diese mit einem Mausklick nach Katello übertragen. Ohne den SCC Manager müsste jedes Produkt inklusive den Repositories einzeln und manuell in Katello angelegt werden. Stattdessen gibt es mit dem SCC Manager eine graphische Auswahl von den in Ihrem SCC Account verfügbaren Produkten. Im Anschluss können die importierten Repositories entweder -bei Bedarf- händisch oder -automatisiert- regelmäßig synchronisiert werden. == Redesign als offener Prozess Wir als ATIX AG (https://atix.de/) sind Teil der Open Source Community um Foreman. Für uns ist Open Source viel mehr als das bloße Hochladen von Code auf Github. Stattdessen treten wir in den Dialog mit der Community, mit Nutzerinnen und Nutzern, und Testenden, um das Foreman SCC Manager Plugin optimal weiterzuentwickeln. Wir stellen das Redesign des Plugins vor und zeigen Einblicke in die überarbeitete Art der Produktauswahl. Wir freuen uns auf Ihr Feedback. about this event: https://programm.froscon.org/2022/events/2771.html

In this work, we present analyses using a series of comparative data insights that help to better understand the potential and implications of integration between knowledge graphs and OSM. OpenStreetMap(OSM) is one of the richest and most diverse sources of geographic information. However, it lacks a fundamental property vital for spatio-semantic analyses: hierarchical structure and semantic linkage. OSM provides links to existing knowledge graphs (structured data that conforms to a specific ontology) e.g., via the wikidata=* tags. The usage of these link-tags is currently limited to a small percentage of both OSM and Wikidata objects. Efforts were undertaken to enhance the geographic linking, linking nearby objects of the same type and semantic linking [1-3]. On the side of the hierarchical and semantic structuring of OSM, the WorldKG knowledge graph[4] provides a semantic mapping of a large subset of OSM. While the free and open OSM tagging scheme is a fundamental part of the OSM project that enabled its success, WorldKG overcomes the inherent lack of structure this tagging scheme represents, paving the way for a knowledge-graph integration of the OSM dataset. Still, open knowledge graphs and OSM are not fully integrated. The following analyses provide a series of comparative data insights that help to better understand the potential and implications of integration between knowledge graphs and OSM. In this work, OSM is compared to Wikidata, one of the largest open knowledge graph projects from the Wikimedia Foundation that provides structured storage to other Wikimedia projects such as Wikipedia. Wikidata can, in many aspects, be compared to OSM by its community structure, its free and open nature, and simple contribution framework. In this work, the two datasets are first compared in size, data structure, and distribution. Later, we extend our analyses with a community comparison. The presented analyses also examine how two separate online communities with similar interests have evolved. Grasping the size of the two projects is a straightforward task and visible on their websites: OSM features around 1 billion elements [5], while Wikidata is much smaller with over 97 million objects, of which approximately 9 million have geographic coordinates. The topic of railway stations was chosen because these objects have a comparable definition and are well represented in both datasets with ca. 130k and 100k elements in OSM and Wikidata, respectively, indicating integration potential. In OSM, railway stations are mapped by the tags 'railway=station' or 'railway=halt'. In Wikidata, the 'instance of (P31)' property containing 'Q55488' value represents Railway Station (object type). By defining generalizable comparison indicators, the presented work provides a framework and source code (available at https://gitlab.gistools.geog.uni-heidelberg.de/giscience/ideal-vgi/osm-wikidata-comparison under the GNU Affero General Public License v3) for VGI project description, comparison, and monitoring. Similar approaches have been established for OSM contributors [6], for single OSM elements [7], and for small geographic regions [8]. For data collection in Wikidata, Wikidata API (https://www.wikidata.org/w/api.php) and Wikidata SPARQL endpoint were used. For Wikidata objects mapped with 'Railway Station', their revision history containing user information, timestamps, and a number of properties was collected. Overall contributions were collected from all users who have contributed to at least one object typed 'Railway Station'. OSM data collection was done using the ohsome API (https://ohsome.org) to extract all railway stations mapped in OSM, including their history and all edits made by the users who edited these railway stations. In addition to a general comparison between the datasets, we derived five sets for a more detailed comparison: OSM with links to Wikidata (59,441 elements), OSM without links to Wikidata (74,659), Wikidata that have links from OSM and are typed as railway stations (45,050), Wikidata without links to OSM but with geocoordinates (54,594) and Wikidata without links to OSM and without geocoordinates (6,714). Our first analysis regarding the growth rate of the two sources showed that OSM has reached a saturated state regarding the number of railway stations, where only a few stations were added since mid-2020. Wikidata, on the other hand, still experiences a stable number of new stations that are added to the project. The two datasets depict no clear temporal correlation hinting towards two independent communities, meaning that edits in OSM are not followed by edits in Wikidata and vice versa. Despite the similar size of the two datasets at a global scale, the two datasets show significant discrepancies on a country level. For example, in China, Wikidata features only 39% of the stations present in OSM while having more than double the amount of stations in

Klassische Fileserver können in vielen Fällen durch Web-gestützte Dateimanagement-Tools ergänzt oder auch gänzlich ersetzt werden. EGroupware hat einen Dateimanager integriert und bietet viele Möglichkeiten zur Dateiverwaltung inklusive Filesharing und Online Office-Integration. Dieses Vortrag greift diese einzelne Anwendung aus EGroupware heraus und zeigt die Funktionen und Einsatzmöglichkeiten im Detail. Der in EGroupware integrierte Dateimanager kann als (alleiniger) Fileserver eingesetzt werden und bietet viele Möglichkeiten zur Dateiverwaltung inklusive Filesharing und Online Office-Integration. Dieses Vortrag greift diese einzelne Anwendung aus EGroupware heraus und zeigt die Funktionen und Einsatzmöglichkeiten im Detail: * Dateiverwaltung im Dateimanager * Sharing (intern/extern) * Collabora Online-Integration * Zugriff per WebDAV * Benutzerdefinierte Felder, Berechtigungen, … * Umwandeln => PDF, jpg * Mounten von externen Verzeichnissen * Mobiler Zugriff * Automatische Ordner für EGroupware-Objekte * Was ist ein VFS? * Sicherung der Daten * Standard-“System“-Verzeichnisse * [EPL-Funktion] Versionierung, Abonnierung * [EPL-Funktion] Zusammenspiel mit Kanban * [EPL-Funktion] Anzeige Ordnernamen Vorkenntnisse sind nicht erforderlich. Hilfreich sind aber erste Kenntnisse zu EGroupware. Dazu stehen zwei **Videos von den Tux-Tagen 2020** zur Verfügung: EGroupware (User-Sicht) und EGroupware extended (Admin-Sicht) https://help.egroupware.org/t/de-tux-tage-2020-vortrage-zu-egroupware-videos-und-vortragsfolien-verfugbar/75555 Weitere Videos/Folien zu EGroupware und drum herum: https://help.egroupware.org/t/de-ubersicht-vortrage/76255 about this event: https://programm.froscon.org/2022/events/2789.html

The United Nations Global Service Center (UNGSC) is developing Virtual Reality applications utilizing OpenStreetMap data. Through a Virtual Reality (VR) pilot project, UNGSC aims to provide UN peacekeepers on the field with 3D digital replicas of the cities in which they are operating, building a sandbox that enhances operational planning with simulations. In order to develop such applications, OpenStreetMap buildings are collaboratively edited, validated and ingested. Field mapping and street-level imagery are also extremely important to add details to the rendered buildings. There could be the possibility to organise a live demo through VR headset. The United Nations Global Service Center (UNGSC) is developing Virtual Reality (VR) applications utilizing OpenStreetMap data. Through the Virtual Operation Center (VOC) pilot project, UNGSC aims to provide UN peacekeepers on the field with 3D digital replicas of the cities in which they are operating, building a sandbox that enhances operational planning with simulations. Under the umbrella of the UN Mappers community, the areas of interest get mapped by means of Tasking Manager projects. Differently from other building mapping campaigns, those are different, as higher quality of the footprints is needed, as well as better placement at the ground floor level and understanding of tall buildings. Furthermore mapping can be complemented with field mapping with street-level imagery as well as smartphone applications, in order to add details on the buildings characteristics as height, levels, roof shape, color and material. After validation of all the edited data, the buildings are ingested into Virtual Reality software development tools as ArcGIS CityEngine and Unity to develop the sandbox application accessible through VR headset. Buildings get eventually rendered utilizing OSM tags which define the 3D model of each object. The activity has been already tested and developed in Mogadishu, Somalia, and Tripoli, Libya, where the mapping took place engaging with the local communities (OSM Somalia and OSM Libya). At the end of the talk, there could be the possibility to organise a live demo through VR headset. about this event: https://2022.stateofthemap.org/sessions/GNG37Y/

Sidewalks are a relevant part of the living space in urban environments, but there are still few mapped sidewalks. In recent years, the mapping of sidewalks has grown in importance among the OSM and academic communities. To cover up this gap, we propose a Github-hosted, fully open-source QGIS Plugin entitled "OSM SidewalKreator" to automatically draw for OSM the geometries of sidewalks crossings and kerb crossing interfaces. Furthermore, the tool gives the user the capacity to control the process. Then, deepen, improve, and increase the amount of sidewalk mapping in OpenStreetMap to improve accessibility and mobility worldwide. Sidewalks are a relevant part of the living space in urban environments. The existence of sidewalks and their condition is fundamental to locomotion in general and is critically important in mobility groups such as cyclists, wheelchair users, blind people, the elderly, and children. Also, the displacement along sidewalks can ensure safety from traffic, contributing to the well-being of citizens [1]. There is still an open debate about the best way to represent sidewalks in the OpenStreetMap community. Some users claim that they should be represented only as tags of the streets, using compound tags such as "sidewalk:left/right:surface=*", arguing that over-representation can pollute the map and create unnecessary complexity [2]. Biagi [3] and many OSM users nowadays [4] have been showing the representation of sidewalks as separated geometries as allegedly their best representation in OSM. There are many listed advantages [4]: crossings may be represented as lines, with the kerb interfaces as points (8 in a regular 4-way intersection); the actual traversing length will be represented (as it will include block corners and crossings); independence from the digitizing direction, as "left" and "right" may swap if someone inverts the way direction; ease of representation for pedestrian islands. Moreover, some cases cannot be represented correctly using the tag scheme or will need some cumbersome solutions, as it shall represent the portion of the sidewalk that is orthogonally projected from the street. Therefore, if a property is different on both sides, one may need to split the highway into four segments to represent it correctly. There are also other issues, e.g. geometric properties such as the distance from the sidewalk to the street will stay unclear. Regardless of the form chosen for representation, there are still few mapped sidewalks. For example, according to Taginfo [5], as of April of 2022, there are approximately 201 million ways with the "highway" key, but only 16.8 million (7.61%) are tagged as "highway=footway", considering the key "footway", there are only 4.8 million (2.45% of 201 million) ways tagged as such (58% sidewalk, 41% crossing), considering the tag "sidewalk=*", there are only 2.6 million (1.3% of 201 million) ways tagged. So, considering that most features are located in urban environments [6;7], where the major part of streets may have a sidewalk, the sidewalks are underrepresented in both schemes. Historically, it has been an issue, as[8] showed that in Berlin, only 5.6% of the Highways have a "sidewalk" tag, growing to only 8.2% in 2017 [9]. Recently, the mapping of sidewalks has grown in importance among the OSM and academic [10;11;12;13] communities. For example, the Open Sidewalks Initiative [14]. They are both a community and a project, providing dedicated mapping with an elaborate scheme on how to map in a pedestrian-centered way, but only manually. Drawing sidewalks and crossings is time-consuming and can be error-prone. This effort can be inferred by examining the OpenSidewalk's own Tasking Manager [15], where in the most near-completion project [16], each task has taken 9.4 minutes to be mapped, but 22.7 minutes be validated. Thus, considering just crossing mapping, for the 1046 existing tasks, it will take approximately 163.9 hours of mapping and 395.7 hours of validation. This total encompasses an area of just approx. 6.17 km2, only 0.65% of the urban area of the city of Sao Paulo, for example. To cover up this gap, we propose a Github-hosted, fully open-source QGIS Plugin entitled "OSM SidewalKreator" [17], which aims to automatically draw for OSM the geometries of sidewalks, crossings and kerb crossing interfaces, along with the basic descriptive tags. This tool gives the user the capacity to control and supervise the entire process. It contains a user-friendly GUI (Guided User Interface) that enables and disables the buttons according to the step in the process. The plugin methodology, encompassing the steps that the plugin runs through are basically: 1) Fetch Interest OSM data (highways and optionally buildings and addresses, when available) from a bounding polygon given by the user; 2) Generate a table for standard widths for the values for t

A recent release of new scientific datasets generated from OpenStreetMap exemplifies the need for analysis-ready repositories of OSM data that require minimal pre-processing. We created the Analysis-Ready Daylight OpenStreetMap Distribution to provide researchers with the opportunity for simple cloud-based SQL queries of nearly 1B OSM features. We demonstrate the capabilities with intrinsic and extrinsic data coverage assessments of OSM buildings globally. Despite being one of the most open and freely available spatial datasets, OpenStreetMap (OSM) data accessibility remains a challenge. Data accessibility measures how easily end-users can access and use a given dataset for their needs [1]. Because OSM data is intended to be rendered as a map or ingested into routing engines, it is often not easily consumable by data analysts. Pre-analysis workflows require OSM data to be downloaded, parsed, and converted into more common formats, which means that novice end-users of OSM may lack the experience to readily access and use OSM data in decision-making. Incorporating communities into spatial decision-making processes, such as mapping, is important because a). community members are experts on their communities and b). have a larger stake in final solutions which directly impacts their lived-experiences[2]. OSM empowers a variety of communities, including local governments[3], digital humanitarian groups[4], and even student groups [5], to help navigate and understand places of respective importance. Research by Nirandjan et al. recently lowered barriers to using OSM data as a reference dataset of critical infrastructure [6]. After categorizing and quantifying particular types of OSM features, the authors released the data in formats more common in geospatial analysis, such as GeoTiffs [6]. This article’s popularity (ranked 90th percentile on the publisher’s website) demonstrates the importance of making OSM data—and datasets derived from OSM—more accessible by means of familiar data structures compatible with common tools. If OSM data were more accessible for analysis, could we see it used in more geospatial research and innovation at large [7]? While many community-maintained tools exist to convert, extract, and download OSM data, each requires domain knowledge of the unique OSM data structure (nodes, ways, and relations). Furthermore, working at the country or planet-scale requires extensive computational resources. To further lower the barriers to entry for OSM data analysis and extraction, we created the Analysis-Ready Daylight OpenStreetMap Distribution (ARD-OSM). ARD-OSM is published on the registry of open data (RODA) on Amazon Web Services (AWS), where it is freely available to anyone [8]. This dataset containing 1B OSM features is optimized for use with Amazon Athena, a serverless interactive query engine on AWS. Additionally, ARD-OSM has resolved the OSM data format into common geometries such as points, lines, and polygons. Data also includes pre-computed valuable attributes such as length, surface area, quadkeys, and geographic bounding boxes which are stored as additional metadata. To demonstrate the analytical capabilities of this dataset, next, we will perform a global OSM building density assessment. Building density is a common metric in OSM quality research, often used to assess map coverage and completeness, such as studied by Yeboah et al. [9]. Measuring building density requires counting all of the buildings within a defined unit of spatial analysis. We use zoom-level 11 map tiles to create an analysis grid that encompasses the global built environment in fewer than 1M tiles. Then, we divide the building count by the area of each map tile to obtain the number of buildings mapped per square kilometer. Since every feature in ARD-OSM includes the zoom-level 15 quadkey of the map tile in which it exists, we can use a SQL GROUP BY expression instead of a geospatial operator for aggregation. Here is the short query used to count the number of buildings in each zoom-level 11 map tile: ```sql SELECT substr(quadkey, 1, 11) as z11_tile, count(id) as number_of_buildings FROM analysis_ready_daylight WHERE tags[‘building’] IS NOT NULL AND release = ‘v1.12’ GROUP BY substr(quadkey, 1, 11) ``` In May 2022, running in AWS region us-east-1, this query took 15 seconds and cost just USD $0.10. The results of this query show the density of mapped buildings in OSM to be highest in Europe with additional areas of high density where Humanitarian mapping campaigns have been active such as Nepal, South Eastern Asia, and isolated parts of Africa. This is consistent with the findings of Herfort et al. [10]. How should these densities be interpreted? Do denser regions have higher levels of building completeness in which most or all buildings are mapped? Building density is an intrinsic data quality measure, to further contextualize these findings, we need to perform an extrinsic assessment by comparing our results again

The opening session of the Academic Track at the State of the Map 2022 conference. about this event: https://2022.stateofthemap.org/sessions/RBZHX7/

Tui Widgets ist eine von Grund auf neu entwickelte c++ Library. Sie stellt flexibel anpassbare Elemente zur Entwicklung von Terminal User Interfaces bereit. Dabei legen wir Wert auf eine Benutzerinteraktion, die sich analog zu Desktop Anwendungen verhält. Dieser Vortrag gibt eine Übersicht über das Framework und demonstriert anhand einer Beispielanwendung, wie das Framework verwendet wird. Auf der vergangenen FrOSCon hat Martin breites termpaint vorgestellt. Darauf aufbauend zeigen wir euch dieses Jahr Tui Widgets. Es kombiniert klassisches Look and Feel in der Tradition von Turbo Vision mit QtCore als Basis für Widgets und Event-Loop. Dabei werden die Widgets über Layout-Manager angeordnet, die auf Veränderungen der zur Verfügung stehenden Fläche reagieren können. Es stehen Elemente für Texteingabe, Radio- und Checkboxen, Buttons, Listen und Menüs genauso wie Fenster zur Verfügung. about this event: https://programm.froscon.org/2022/events/2743.html

In den letzten Jahren wurde die openSUSE-Infrastruktur deutlich verbessert. Aber ist sie jetzt perfekt? Natürlich nicht - sonst hätten die Heroes (= openSUSE Admin-Team) Langeweile, und ich könnte diesen Vortrag nicht halten. Wo Leute arbeiten, passieren natürlich auch lustige[tm] Dinge. Bringt bitte Euer eigenes Popcorn mit ;-) about this event: https://programm.froscon.org/2022/events/2780.html

Auch in diesem Jahr sammeln Oliver und Michael die Themen, Kuriositäten und Aufreger des vergangenen Open Source-Jahres auf und diskutieren gemeinsam mit dem Publikum auf der Open Source Couch. Auch in diesem Jahr sammeln Oliver und Michael die Themen, Kuriositäten und Aufreger des vergangenen Open Source-Jahres auf und diskutieren gemeinsam mit dem Publikum auf der Open Source Couch. about this event: https://programm.froscon.org/2022/events/2761.html

The Small Device C Compiler (SDCC) is a free compiler targeting various 8-bit systems, including common microcontroller (µC) architectures. The SDCC-STD-UX project funded by the Bundesministerium für Bildung und Forschung aims to improve standard compliance in SDCC, in particular support for current and future C standards. SDCC targets common 8-bit µC architectures, such as the MCS-51, STM8, S08, Rabbit and Padauk, as well as some architectures now mostly relevant to retrocomputing or -gaming, such as Z80 and SM83. As a C compiler, SDCC aims to support current and future C standards, but is not up to the level of GCC or clang. For debug information, there is some basic support for ELF/DWARF. This summer, the Bundesministerium für Bildung und Forschung via the Prototypefund funds the SDCC-STD-UX effort to improve standards compliance and usability in SDCC. This ngoing effort has already resulted in substantial improvements in support for C standards that will be in the future SDCC 4.3.0 release. about this event: https://programm.froscon.org/2022/events/2819.html

Albert Einstein's quote "If you want to know the future, look at the past." couldn't be more accurate today. Many young software engineers and graduates today were born in the early 2000s and only know the struggles of early software engineering from their older colleagues, the vintage computing community or abandoned books. Further, many developers from the early 90s are retiring now and there is a danger of losing important knowledge. In my presentation we will travel back 30 years and look at how software was built from 1990 to 2020. Not in theory, but with practical examples including screenshots and actual production code from the era. [1991] "Apps" ;) for Windows 3.11 with Visual Basic 2.0 [1996] The first baby steps in "Web development" [1997] "Mobile Apps" with C++ and PalmOS [1999] Writing code for the last MacOS (Version 9) [2000] Arrival of the HTML coder ;) Web development goes mainstream [2002] C# for Windows & Windows Mobile "App development" [2003] C++ on Linux: building everything imaginable [2005] Apache, PHP, MySQL becomes mainstream [2008] Birth of "The Cloud": Developing with Google App Engine [2010] "Mobile Apps" for everyone! Building on iOS, Android & Blackberry [2012] The great merge conflict: Git sends SVN, CVS & HG to the history books [2015] Cloud & Software-as-a-Service: Goodbye InstallShield Wizard [2018] Serverless & Infrastructure-as-Code: Goodbye operating system [2020] JavaScript! How did you even survive 25 years? Sit back, relax and enjoy the ride while we fire up the flux capacitor to look at 30 years of software development and archeologically explore software history. I have experienced much of the software development history myself or through my father who built software from the 80s to the 90s. Given the time, the presentation will not go into every detail but give a glimpse and an immersion into the yesteryear of software development. It is supposed to be an insight into people interested in software development and history as well as those who might be interested to discover more about vintage computing, especially programming. While vintage computing is becoming more and more popular, vintage programming is still in it's infancy. about this event: https://programm.froscon.org/2022/events/2730.html

It’s easy to see how OpenStreetMap could be leveraged to improve the completeness and freshness of government geospatial datasets. So why aren’t all governments using OpenStreetMap? In the US, the ODbL license has prevented government agencies from using the data. Public Domain Map aims to resolve this (and other challenges) by providing a workflow that allows contributions to be used in both OpenStreetMap and public domain US Government databases. We will share the journey of Public Domain Map, and importantly, how the project is bringing together US federal agencies and open source contributors to meet this goal. about this event: https://2022.stateofthemap.org/sessions/CFVMU7/

Language barrier and the default to English puts non-English speakers at a systemic disadvantage throughout open mapping communities and humanitarian open mapping activities resulting in significant missed participation and impact. We held experimentation on language translations of key resources identified by collaborators coming from local OSM communities and we hope to share the findings in this talk. We believe that language localization will enable inclusion and participation of underrepresented groups in mapping, dialogues and other humanitarian open mapping activities. We ran small experiments with local contributors to test how localisation of resources could work in the main languages of 3 priority countries (Vietnam, Madagascar, Mozambique) and we hoped its insights would inform a self-sustainable Localization Strategy for these communities and beyond. However, the documented findings are not sufficient due to challenges encountered (including communication and technical barriers, difficulty with monitoring and evaluation, among others) during the course of the research. Hence, opportunities and recommendations will be presented for future work to explore this theme. OSM Diary post on the launch: https://www.openstreetmap.org/user/arnalielsewhere/diary/397844 about this event: https://2022.stateofthemap.org/sessions/3MMV93/

During the 2019-2020 pilot supported by Microsoft, 18 million building footprints were automatically extracted from satellite imagery for all of Tanzania and Uganda. HOT found that on average, mappers working without AI assistance could map between 1000-1500 buildings per working day. For areas with high-quality AI output, providing mappers with AI-generated building footprint suggestions increased this rate to up to 2500-3000 buildings per day approximately doubling the rate at which building data could be added to OpenStreetMap, which is the crucial link for making it available to the humanitarian information management community. While doubling mapping efficiencies (100% efficiency gain) are promising, one of the greatest challenges is making sure data is converted from AI/ML to OpenStreetMap in a rapid yet responsible community-centric way (respecting existing data contributions already in OpenStreetMap). This project enabled us to take the ‘next step’ after receiving the building predictions from Microsoft by building better tools for data conflation. This is expected to dramatically reduce manual intervention. By doing this, human mappers can focus their time and skills on value-added activities: ground-truthing and validating predictions and adding local knowledge to the map not visible from satellite imagery (such as place names, location of key lifeline infrastructure, etc. We’ll describe our mapping workflow and progress updates for Kenya and Nigeria, and the specific challenges met with this dataset extracted through machine learning will be explained. Considering the growing availability of such AI-related datasets, we’ll review common errors and how we adapted to them and to other issues such as imagery offsets, heterogeneity of existing data and other context specific challenges. Eventually we’ll propose recommendations regarding this type of editing and aspects to consider before starting such imports and how to get the community involved. about this event: https://2022.stateofthemap.org/sessions/GNEJ9G/

This session will provide an introduction to the OpenStreetMap operations team, what OpenStreetMap.org services we are responsible for building and maintaining. Grant recently became the OpenStreetMap Foundation's first full-time employee. Grant will present how he is helping improve reliability and security of the project's technology and infrastructure. Grant will detail how the Operations team are modernising the project's infrastructure by reducing complexity, paying-down [technical debt](https://en.wikipedia.org/wiki/Technical_debt), while reducing the need to maintain [undifferentiated heavy lifting](https://www.factoftheday1.com/p/december-23-undifferentiated-heavy). If you’re interested in what powers OpenStreetMap and make it tick, come to this session. about this event: https://2022.stateofthemap.org/sessions/D8XYDN/

Verschiedene Aktive aus Projekten rund um Freie Software und Digitale Souveränität berichten aus der praktischen Arbeit und von Themenkonferenzen, was sich in Schulen und an anderen Lernorten so tut, welche Entwicklungen und Herausforderungen es gibt und wo Hilfe benötigt wird. In den Schulen wird der Grundstein für (Digital)kompetenzen gelegt – was insbesondere Konzerne dazu bewegt, ihre proprietären Systeme zur frühren Kundengewinnung und -bindung zu positionieren. Ein bisschen wie David gegen Goliath wollen verschiedene Software- und Gesellschafts-Projekte auch Freie Software und damit Digitale Souveränität in einer für politische Entscheidungsträger*innen, Schulträger und Schulleitungen greifbaren Form positionieren. Für die Bildung sind die Freiheiten, die Freie Software bietet, ein klarer Vorteil: Neben wirtschaftlichen Vorteilen durch geringere Lizenzkosten und der ohne geplante Obsoleszenz größeren Nachhaltigkeit erlauben offener Code und Lizenzen vor allem auch eine Verwendung als Unterrichtsobjekt selber. So können Lerngruppen anhand der Software, die sie in ihrer realen Lebensumwelt nutzen, informatische Konzepte erlernen und sogar selber zu ihrer realen Lebensumwelt im Digitalen beitragen. In "State of the Edu" erzählen Aktive aus verschiedenen Projekten, welche Entwicklungen es bei ihren Lösungen gibt, was sie in der praktischen Arbeit im schulischen und außerschulischen Bildungsumfeld erlebt und gelernt haben und wohin die Entwicklungen gehen. Dieses Mal gehören hierzu: <ul> <li>AlekSIS®, das Freie Schul-Informations-System – Neues Release Entwicklungvon Schul-Informations-Apps mit Schüler*innen und wie die Integration mit offenen und proprietären Systemen läuft</li> <li>Debian Edu NG? – Wie sich ein zentrales Schul-Server-System im Umfeld von dezentralem, asynchronem Lernen, Tablet-Klassen und BYOD-Konzepten schlagen muss</li> <li>Bildungsmesse didacta – Vom Austausch mit Lehrkräften, Schulträgern und kommerziellen Mitbewerbern</li> </ul> Neben Berichten erzählen wir auch, wo aktive Mithilfe benötigt wird und wo man sich, technisch und nicht-technisch, einbringen kann. Denn nur gemeinsam und mit gebündelten Kräften können wir uns erfolgreich "auf dem Markt behaupten"! about this event: https://programm.froscon.org/2022/events/2790.html

Ein Anwendungsbeispiel für massive Parallelisierung mit CUDA für die semantische Suche in Multimediadatenbanken. Die schnelle Suche nach dem ähnlichen Bild - Große Multimediabibliotheken entstehen durch allgegenwärtige Smartphones aber auch in den Bereichen von Medien und Medizin. Sie Suche von ähnlichen Inhalten (Multimedia Information Retrieval) kann durch Semantische Graphen/Knowledge Graphen erfolgen. Graph Datenbanken sind dort jedoch langsamer als einem lieb ist. Mit dem vorgestellten Verfahren können Suchergebnisse durch massive Parallelisierung sehr schnell Ergebnisse liefern. Eine kleine Einführung in die Entwicklung für Parallelisierung Ein Beispiel für die Parallelisierung mit GPUs. about this event: https://programm.froscon.org/2022/events/2806.html

QGIS is one of the most used Opensource GIS software with some native functionalities to work with OSM data. Either with raster layer as a basemap, or with vector, QGIS can deal with OSM data. Depending on the amount of data to work with, the need to "refresh" the data (from the main OSM database), the extent of the coverage, different plugins or technologies are possible. This presentation will try to give an overview how it's possible to use OpenStreetMap data according to different situations (Geocoding, TMS/WMS, OverpassAPI, PostgreSQL…). The presentation will show how you can contribute to QuickOSM to add some default « mappreset » to QuickOSM on GitHub. about this event: https://2022.stateofthemap.org/sessions/AKYJPG/

Lighting talks registered during the State of the Map conference. ## OSM Teams: History & Updates _by Lane Goodman_ ## Bike Data Project _by Ben Abelshausen_ ## 360° imagery everywhere _by Joost Schouppe_ ## Worldwide Administrative Boundaries Dataset Project _by Albert Bautista_ about this event: https://2022.stateofthemap.org/sessions/FGDY3F/