Something that I began doing more often is converting videos of developing embryos or marine invertebrates to animated GIFs. But how to do this conversion without affecting the quality of the video?
Some time ago I found this guide to convert videos to high-quality animated GIFs using the tool FFmpeg. The trick is to generate a color palette based on the original video to improve the color quality of the GIF. Based on this guide I created a small bash script to make my life easier and perhaps yours too 😉
Last year I decided to experiment with DuckDuckHack, the developer plataform for the search engine DuckDuckGo. The idea was to use the instant answers to find scientific articles as a quick Google Scholar shortcut.
It’s feasible, in principle, but I decided to try something simpler. A plugin that uses the PLOS API to search their articles and display in the instant answer box.
To use it you just need to add the word “plos” + keywords (example above). The result is a list of titles and dates of the five most-relevant articles with direct links. Hovering the mouse over a link will show the authors and which PLOS journal. This final format was simplified after the initial pull request and polished up in the second.
Since DuckDuckGo is less used than Google I guess the number of users might be low. Maybe I’m the only one… It would be amazing if it could query the whole scientific literature! But well, I like this little hack. I guess it’s the excitement of connecting services using APIs.
On a Saturday morning a few weeks ago I bumped into the Hack4Knowledge, a meeting to build apps, tools and remixes with existing databases to innovate and enrich the creation and dissemination of knowledge.
I was already playing with Mendeley API and took the opportunity to put an idea into practice: aggregate bibliographic references related to a taxon. It is not a particularly new idea, and it also does not differ much from searching a taxon name on google or scopus, but since Mendeley database is based on its users’ collections, it is possible to extract some interesting information. For example, find out which articles are more popular ou create trending topics with popular taxa based on the number of readers and related publications.
Regardless of the source, article data also allows to extract useful information such as the most active authors on a certain taxon, network of collaborators, annual variation in the number of related articles, popular research topics for each group, etc. Integrating the data and using visualization tools it would be possible to “see” holes in the knowledge or follow the history of one’s research.
Imagine if every article was freely available with contained information (metadata) about the studied organisms with taxonomic classification, occurrence data, collection sites, dna sequences, citations with semantic markup, research topics, hypotheses to test, methods, raw data, etc. Anyone would be able to have a summary of the current knowledge about an organism. Specially interesting to set research quidelines and avoid spending money with the same mistakes; optimization of science. And do not forget about the possibility to attach observations, annotations, discussions, unsolved questions, and other collaborative activities.
Well, after creating a prototype of the idea, I have just pust the basic functions of the aggregator to work. Nothing I wrote above is included, just a search interface where you can use a scientific or common name and a page for each taxon with a list of related references and some sorting options. If a taxon is not in the database, it searches in realtimes, therefore, it is necessary to wait a little and reload the page (at least until I automate this).
If you are interested you can test the Living Bibliography at livingbib.organelas.com. Just remember it is completely experimental, I do not garantee that your favorite articles will appear or that the information will be accurate (there are many duplicated articles, wrong author names, badly formatted titles, swapped journal names, and so on at Mendeley). I don’t know how much I’ll be able to work on it, but the source code is open and I would love to hear ideas and suggestions 🙂