One of the important outcomes of the Markdown for Science workshop that took place in June 2013 was a decision on a name - Scholarly Markdown - and a brief definition:Markdown that supports the requirements of scientific textsMarkdown as format that glues open scientific text resources togetherA reference implementation with documentation and testsA community In my eyes this is still a great definition.

One of the major challenges of writing a journal article is to keep track of versions - both the different versions you create as the document progresses, and to merge in the changes made by your collaborators. For most academics Microsoft Word is the default writing tool, and it is both very good and very bad in this.

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 Sunday Ian Mulvany and I will do a presentation on Open Scholarship Tools at Wikimania 2014 in London. From the abstract: One of the four broad topics we have picked are digital object identifiers (DOI)s . We want to introduce them to people new to them, and we want to show some tricks and cool things to people who already now them.

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.

One Ring to rule them all, One Ring to find them, One Ring to bring them all and in the darkness bind them. Yesterday 60 years ago the first volume of the Lord of the Rings trilogy by J.R.R. Tolkien was published.

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 is a methodology that combines a programming language with a documentation language, thereby making programs more robust, more portable, more easily maintained, and arguably more fun to write than programs that are written only in a high-level language. The main idea is to treat a program as a piece of literature, addressed to human beings rather than to a computer.

Earlier this week Björn Brembs wrote in a blog post (What Is The Difference Between Text, Data And Code?): The post is about the importance of publication of data and software where currently the rewards are stacked disproportionately in favor of text publications . The intended audience is probably mainly other scientists (Björn is a neurobiologist) who are reluctant to publish data and/or code, but there is another interesting aspect