October 23, 2017

Open Access Week 2017!

Welcome to Open Access Week 2017! Synthetic Daisies participated in Open Access Week 2016 with two instructional posts on Altmetrics and Secondary Datasets.  On Twitter, several hashtags (#oaweek#OpenAccess#OpenScience, and #OpenData) will be full of related content over the next few days. And we will have longer posts on Tuesday and Thursday on the topics of Open Project Management and Version-Controlled Papers that will be worth reading.

Over the last year, the OpenWorm Foundation and Orthogonal Laboratory made a commitment to open access instruction in a series of microcredentials (digital badges). The OpenWorm badge system offers a series of badges on Literature Mining specifically and Open Science more generally. The Orthogonal Lab badge system offers a series of badges on Peer Review. Have a productive week!

October 2, 2017

Pseudo-Heliocentric Readership Information in Gravitationally Bound Form

Or, how to get 300,000 reads by being persistent [1] and getting results in unexpected places. Let's review our milestones in three cartoons.

The made-up planetary orbits featured here [2] may violate the physics of actual solar system orbits, at least as simulated by Super Planet Crash [3].

[1] Candy, A. (2011). The 8 Habits of Highly Effective Bloggers. Copyblogger, October 25.

[2] Previous readership milestones, in order of distance from central star: 20000, 50000, 100000 (first image), 120000, 150000 (second image), 200000, 250000 (third image).

[3] Featured in the Scientific Bytes and Pieces, August 2015 post.

September 21, 2017

An Infographical Survey of the Bitcoin Landscape

Josh Wardini sent me information on a new Bitcoin infographic that serves as a survey of events over the last 10 years in the world of Bitcoin development and legal regulation. Many interesting factoids in this graphic, some of which were unbeknownst to me. In the next few paragraphs, I will discuss my impressions that are brought to bear by each subset of factoids.

The relationship between blockchain and mining is an interesting one, and underscores the power of blockchain as both a data structure and a secure transaction system. Bitcoin is also its own economic system, complete with social interactions. In particular, the competitive and cooperative aspects of cryptocurrency can serve as a model for understanding the social structure of markets.

This is another interesting feature of bitcoin: the network has computational power to both unlock the value of existing blockchain as well as to create new currency. Bitcoin mining has always been a bit of a black box to me [1], but it seems as though it has potentially two roles in the bitcoin economy. In a Synthetic Daisies post from 2014, I mentioned that the supply of bitcoin is fixed (in the manner of a precious metals supply), but it turns out that it is not that simple. Of course, since then blockchain technology has become the latest hot emerging technology in a number of areas unrelated to Bitcoin and even the digital economy [2].

It turns out the computational systems (unlike people) is not all that hard to understand. However, digital currency, which is based on human systems, is much harder to understand (or at least fully appreciate). In 2013, I did a brief Synthetic Daisies mention of a flash crash on one of the main Bitcoin exchanges. There is a lot of opportunity to use blockchain and even perhaps cryptocurrency in the world of research. If ways are found to make these technologies more easily scalable, then they might be applied to many research problems involving human social systems [3].

[1] So I sought out a few introductory materials on Bitcoin mining to clarify what I did not know: 

a) startbitcoin (2016). Beginner's Guide to Mining Bitcoins. 99 Bitcoins blog, July 1.

* mining consists of discovery blocks in the blockchain data structure, the discovery of which is rewarded through a "bounty" of x bitcoins. From there, inequality emerges (or not).

b) Mining page. Bitcoin Wiki.

* the total number of blocks is agreed to by the community, as is the total amount of computational power of the network. This makes the monetary supply nominally fixed, but is not required by the technology.

c) Hashcash Algorithm page. Bitcoin Wiki.

Despite the clear metaphoric overtones, Bitcoin mining is essentially like breaking encryption in that it requires a massive amount of computing power thrown at a computationally hard problem, but is also has elements of an artificial life model (e.g. competition for blockchain elements).

Water-cooled rigs probably maximize your investment margin....

[2] Of course, there has been innovation in the use of blockchain for Bitcoin and more general cryptocurrency transactions. For more, please see:

Portegys, T.E. (2017). Coinspermia: a cryptocurrency unchained. Working Paper, ResearchGate, doi:10.13140/RG.2.2.33317.91360.

Brock, A. (2016). Beyond Blockchain: simple scalable cryptocurrencies. Metacurrency project blog, March 31.

[3] A few potential examples:

a) Data Management. 1  2

September 11, 2017

This Concludes This Version of Google Summer of Code

I am happy to announce that the DevoWorm group's first Google Summer of Code student has successfully completed his project! Congrats to Siddharth Yadav from IIT-New Delhi, who completed his project "Image Processing with ImageJ (segmentation of high-resolution images)".

Our intrepid student intern

His project completion video is located on the DevoWorm YouTube channel. This serves as a counterpart to his "Hello World" video at the beginning of the project. The official project repo is located here. Not only did Siddharth contribute to the data science efforts of DevoWorm but also contributed to the OpenWorm Foundation's public relations committee.

Screenshot from project completion video

As you will see from the video, a successful project proceeds by organizing work around a timeline, and then modifying that timeline as roeadblocks and practical considerations are taken into account. This approach resulted in a tool that can be used by a diverse research community immediately for data extraction, or build upon in the form of future projects. 

In terms of general advice for future students, communicate potential problems early and often. If you get hung up on a problem, put it aside for awhile and work on another part of the project. As a mentor, I encourage students to follow up on methods and areas of research that is most successful in their hands [1]. In this way, students can find and build upon their strengths, while also achieving some level of immediate success. 

[1] This seems like a good place to plug the Orthogonal Research Lab's Open Career Development project. In particular, check out our laboratory contribution philosophy.

August 25, 2017

Live streaming of Orthogonal Lab content

Research live-streaming: an experiment in content [1].

The Orthogonal Research Laboratory, in conjunction with the OpenWorm Foundation, is starting to experiment with live video content. We are using YouTube Live, and live streams (composed in Xsplit Broadcaster) will be archived on the Orthogonal Lab YouTube channel. The intial forays into content will focus on research advances and collaborative meetings, but ideas for content are welcome. 


[1] obscure reference of the post: a shot of Felix the Cat, whose likeness was used to calibrate early experimental television broadcasts.