SUBSCRIBE
About this site
- "Freelancing science" is a blog about biology in silico, data visualization and open science. Written by Paweł Szczęsny.
- Contact: pawel at FreelancingScience dot com
-
Original content of this site is licensed under a Creative Commons Attribution 3.0 Unported License, unless stated otherwise.
Other sites and projects
- New home site - Circle of complexity
- Tracking 2.0 meme across disciplines - All 2.0
- Sistema Commons - textbook for music instructors
-
Most popular posts
- Freelancing science - today and tomorrow
- Biology Image Library - scientific stock photography?
- Images of molecules
- PhD thesis in LaTeX
- Blender in visualization of molecules
- Publication quality pictures of biomolecules
- Open projects
- Many Eyes and literature summary
- Bioinformatics is a visual analytics (sometimes)
- Complex systems and biology - introduction
Twitter Updates
- @researchremix DM me your address and the size of the t-shirt (with the units). Hopefully you'll get it before Christmas. 2 months ago
- @Kubke Wasn't that TOPAZ platform? http://t.co/lt5jUguB 3 months ago
- @researchremix I know Kamil (creator of the remix) - I will ask him if there's a chance you can get one :) 3 months ago
- @researchremix @RepoRat Yup, beer-maker or brewer. It's a very noble surname here :) cc@jpiwowar 3 months ago
- @researchremix @RepoRat BTW Heather, do you know what it means in Polish? 3 months ago
Category Cloud
bioblogs bioinformatics Biological engineering Career Clipped Comments Community Data mining Dump-all Education Fun Imaginary nanodevice Money open-science Papers Proteins PubMed Research Research skills Science and Art Secretion system Services Software Structural biology Structure prediction Synthetic biology Visualization
Shared items- Quantification of mRNA and protein and integration with protein turnover in a bacterium
- 07/20/11 PHD comic: 'Intellectual Freedom'
- [News & Analysis] Psychology: Searching for the Google Effect on People's Memory
- Epigenome-wide association studies for common human diseases
- How to waste public money in one easy step…
- Genome sequence and analysis of the tuber crop potato
- Differential Producibility Analysis (DPA) of Transcriptomic Data with Metabolic Networks: Deconstructing the Metabolic Response of M. tuberculosis.
- Learning: Not Just the Facts, Ma'am, but the Counterfactuals as Well.
- The neural basis of following advice.
- How stands the Tree of Life a century and a half after The Origin?
GR starred items (not necessarily scientific)- A Polycomb-based switch underlying quantitative epigenetic memory
- Structural basis for alginate secretion across the bacterial outer membrane.
- A Model of Proto-Anti-Codon RNA Enzymes Requiring L: -Amino Acid Homochirality.
- How accurate is the new Ion Torrent genome, really?
- Day Old News is Fresh Enough
- Bridging the Resolution Gap in Structural Modeling of 3D Genome Organization.
- Does the potential for chaos constrain the embryonic cell-cycle oscillator?
- Sequence, structure, and network evolution of protein phosphorylation.
- Microbial Virulence as an Emergent Property: Consequences and Opportunities
- Discovering Novel Subsystems Using Comparative Genomics
-
My science-related images





More Photos Archives
Timestamped FriendFeed activity – really public “profile”
Accidentaly, I have found a simple way for obtaining a time stamp for each entry and comment any person with publicly available lifestream makes on FriendFeed (except “Likes”, which do not seem to be timestamped at all). Activity of semi-randomly choosen person during the day (summarized over couple of weeks (!)) is shown below:
FriendFeed usage during 24 hours, summarized over couple of days.
While relation between AM and PM periods is correct, time-zone is manually shifted, so it’s more difficult to guess who’s this activity is (but it’s not Robert Scoble if you want to ask). What does it tell? Basically, this person does not close FriendFeed window for the most of the day. Additionally, there’s a period of the day in which “catching-up” has place. Nothing interesting so far? Original data has much more details. It is possible for example to collect information when during the day particular person usually watches videos on YouTube. Guess – is that during working hours?
Ability to get that data for couple of weeks back without any trouble (I didn’t need to track this person’s activity for such period) was kind of disturbing. I knew it’s very simple to start tracking my habits, but I wasn’t aware of the fact that it’s also easy to see what I was doing over the last three weeks. Do you think it makes a difference?
Share this:
Like this:
Posted by Pawel Szczesny on January 29, 2009 in Comments, Visualization
Tags: activity tracking, Blog, FriendFeed, RSS