Every Tool and Project I learned about, at #mozfest
I spent the weekend at a conference in London called #mozfest, which was run by Mozilla and featured people talking about open source code, journalism, art, science, community, and community learning. Saw lots of great products/ideas, which are summarized below. I’m highlighting things that I would need dev help on, but that we could make (if you’re interested in a side project.) Tomorrow, I’ll report on key takeaways.
1. HearUsHere uses GPS coordinates to place sounds at specific locations. This allows users to compose audio experiences as they travel throughout a space. (For example, recording sounds as a walking tour around a city.) Imagine what we could do with this for news or our programming.
2. Wit.ai is natural language for the Internet of Things.
3. Free web app to take the pain out of transcribing interviews.
4. I worked on a team to think about how we could recreate the tape recorder to make a better experience for reporters out in the field. Want to work on this? Let me know.
2. The BBC News Lab team is working on several projects of note.
COMMA creates metadata from large collections of audio files. It produces crude transcripts using speech recognition, automated tags and speaker segmentation. (from Letter from America Rediscovered.)
Letter from America categorized by theme
To do this, they used WikipediaMiner, which is a toolkit built for tapping into the rich semantics encoded within Wikipedia.
2a. Related: Local Angle developed by researchers at the Knight Lab, finds locally revenant stories in national news. They do this by using Wikipedia’s API and an API that finds keywords in stories. Imagine how we could apply this to audio, particularly if we can pluck out keywords.
Structured Wikipedia Data Resources: How Wikipedia structures data and how you can use it to do cool stuff
- How the New York Times, the New York Public Library and ProPublica are crowdsourcing data — and relying on their audience to provide layers of metadata that could be useful for future projects
- Sarah Marshall, an editor at the WSJ, runs a very helpful blog with her thoughts about journalism tools and strategy.
- I ran a session on how to think about your audience while designing new tools.
- What if articles modified themselves based on an individual reader’s needs? What if, rather than building news applications and interactive graphics that rely on user input, the content was automatically restructured or personalized based on where or what a reader was doing?
- How the Trib used a lot of data to describe neighborhood boundaries in Chicago
- Penguin is experimenting with letting readers remix a Stephen Fry novel Think about this in terms of what we could do with our stories.
- PenFlip is like Github, but for collaborating on writing articles. I really like this.
- There was a session on what designers and UX folks could learn from how video game folks design successful tutorials in their games. Key takeaways: less text, don’t give people too much info upfront, add rewards, reinforce good behavior, listen to users. (This is also applicable when thinking about news and stories.)
- NPR’s Analytics Dashboard (with pictures)
- PopcornMaker is a way to remix web video, audio, and images into mashups that can be embedded onto other websites.
- Notes about VOX, New Yorker and Pitchfork’s internal CMSes from Sarah Marshall. (More notes on this.)
- A group of us came up with several bot ideas that would be useful for a newsroom (Help me make these.)
1. Could a bot provide reporters with predictions about board appointments, political appointments or hiring decisions based on aberrant behaviors on Twitter? In other words, if everyone from NPR starts following X, then it’s pretty likely X is about to be hired by NPR — even if that information isn’t publicly announced yet. This could help business reporters, political reporters and entertainment reporters. (Here’s how Buzzfeed predicted Ezra Klein was going to VOX using humans to determine this.)
2. Could a bot suggest questions for reporters to ask about a particular topic, based on questions that have been posted to Ask Metafilter, Reddit’s Explain it Like I’m 5, Quora, and the Stack Exchange network? i.e. How can we filter the best questions posted on these networks and give them to reporters so they know what the audience is curious about?
3. Could you have a bot that would monitor the ethics of other bots?
- Here’s a bot WNYC made that automatically tweets about upcoming hurricanes.
- Hack the New Org: Creates a new organization with a unique approach, audience, and topic.
- Cool notecards to use when plotting awesome projects
See something cool? Let us know! The archives for this listserv live here: socialmediadesk.tumblr.com