In July and August I attended the Open Knowledge Festival and Wikimania. At both events I had many interesting discussions around open source tools for open access scholarly publishing, and I was part of a panel on that topic at Wikimania last Sunday.

One topic I will cover this Sunday in a presentation on Open Scholarship Tools at Wikimania 2014 together with Ian Mulvany is visualization. Data visualization is all about telling stories with data, something that is of course not only important for scholarly content, but for example increasingly common in journalism. This is a big and complex topic, but I hope the following will get you started.

This Sunday Ian Mulvany and I will do a presentation on Open Scholarship Tools at Wikimania 2014 in London. From the abstract: This presentation will give a broad overview of tools and standards that are helping with Open Scholarship today.

Before all our content turned digital, we already used page numbers to describe a specific section of a book or longer document, with older manuscripts using the folio before that. Page numbers have transitioned to electronic books with readers such as the Kindle supporting them eventually. For content on the web we can use the # fragment identifier, e.g.

Yesterday 60 years ago the first volume of the Lord of the Rings trilogy by J.R.R. Tolkien was published. The quote above obviously doesn’t quiet apply to scholarly publishing, but one recurring theme that I have often heard in the last few years is that of a need for a canonical digital document format for scholarly content that rules all other formats.

In a post last week I talked about roads and stagecoaches, and how work on scholarly infrastructure can often be more important than building customer-facing apps. One important aspect of that infrastructure work is to not duplicate efforts. A good example is information (or metadata) about scholarly publications. I am the technical lead for the open source article-level metrics (ALM) software.

I attended the Open Knowledge Festival this week and I had a blast. For three days (I also attended the fringe event csv,conf on Tuesday) I listed to wonderful presentations and was involved in great discussions - both within sessions, but more importantly all the informal discussions between and after sessions.

Literate Programming by Donald Knuth (1983) is a seminal book that introduces the concept of literate programming. Using technology available in 2014 we can make a small but important change to the last sentence: This blog post is an example for such a document.

Earlier this week Björn Brembs wrote in a blog post (What Is The Difference Between Text, Data And Code?): To sum it up: our intellectual output today manifests itself in code, data and text. The post is about the importance of publication of data and software where currently the rewards are stacked disproportionately in favor of text publications.

Last week I had a little discussion on Twitter about a great blog post by Zach Holman: Only 90s Web Developers Remember This. The post is not only fun to read, but also reminded me that it is now almost 20 years (1995) that I built my first website - of course using some of the techniques (the one pixel gif!, the   tag!) described in the post.

In this post I want to talk about some of the misunderstandings I frequently encounter when discussing markdown as a format for authoring scholarly documents. Scholars will always use Microsoft Word Microsoft Word is of course what almost all authors use in the life sciences and many other disciplines. One big reason for this is the file formats accepted my manuscript submission systems.