Posts

  • KDE Itinerary @ Paris Open Transport Meetup

    I have been invited by Kisio Digital to present the work we have been doing around KDE Itinerary at the Paris Open Transport Meetup next week. The meetup is near Gare de Lyon and starts on Thursday at 19:00. Feel free to come by, I’m looking forward to discuss ideas on how to move KDE Itinerary forward.

  • Automatic C++ comparison operators

    C++ comparison operators are usually fairly straightforward to implement. Writing them by hand can however be quite error prone if there are many member variables to consider. Missing a single one of them will still compile and mostly work fine, apart from some hard to debug corner cases, such as misbehaving or crashing algorithms and containers, or data loss. Can we do better?

  • KDE Frameworks 5 for Yocto

    At the KDE booth at Embedded Linux Conference Europe in Edinburgh the other week you might have seen the Plasma Mobile shell running on a Raspberry Pi 3, similar to what I presented at Akademy in Vienna. Besides showing the flexibility of Plasma and how nicely the Plasma Mobile shell works on touch screens, this was originally built as a demonstration of the KDE Frameworks 5 Yocto recipes.

  • KF5 Static Builds

    Static linking has long gone out of fashion, at least on the average Linux desktop distribution. There are however good reasons to still (or again) support this for our frameworks. One is the rise of application bundles (Flatpak, Android APK, AppImage, etc).

  • August/September in KDE Itinerary

    Since KDE Itinerary was first presented to a wider audience at Akademy 2018 a lot has happened. Here are the most important changes from the past two month, in KDE Itinerary and the underlying frameworks.

  • KDE Itinerary - Static Knowledge

    In the previous post on writing custom data extractors for the KItinerary framework, I mentioned we are augmenting extracted data with knowledge from Wikidata. This post will cover this aspect in more detail.

  • KDE Itinerary - Writing Custom Extractors

    Following the look at how KDE Itinerary does data extraction, this post will cover custom data extractors in a bit more detail. Custom extractors are needed where we are unable to obtain the information we are interested in from structured annotations, or add information to incomplete structured data (such as boarding pass barcodes).

  • KDE Itinerary - Data Extraction

    After the overview of KDE’s travel assistant components we are going to look at one part in particular here, the booking data extraction. The convenience and usefulness of the overall system depends on being fed with accurate and complete data of when and where you are going to travel, ideally fully automatically.

  • KDE Itinerary - Overview

    As introduced in the previous post there has been some work going on to explore a privacy-by-design alternative to digital travel assitant services like provided by Google or TripIt.

  • KDE Itinerary - How did we get here?

    At Akademy I’ve presented the current state of KDE Itinerary. Due to popular demand and since 25 minutes aren’t a whole lot of time I’ll try to write a few posts on this subject here too, beginning with how this all started.