Data as an art material
Presenting data without the need for graphicacy
Usinging biomimetic psychology (not just physical and systems designs) https://www.google.co.uk/search?q=psychological+biomimeticry&ie=utf-8&oe=utf-8&gws_rd=cr&ei=Z6exV9exC8X3aP2ohMAG
https://www.movebank.org/
Movebank is a free, online database of animal tracking data hosted by the Max Planck Institute for Ornithology. We help animal tracking researchers to manage, share, protect, analyze, and archive their data. Movebank is an international project with over 11,000 users, including people from research and conservation groups around the world.
Stamen – process exposition on mapping emotion to data vis https://hi.stamen.com/embracing-the-abstract-in-visualized-data-47044cee8bd3#.onscse3a4
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SET `fieldname` = replace(`fieldname`, ‘UNWANTED-TEXT’, ‘WANTED-TEXT’)
http://www.r-bloggers.com/simple-pattern-detection-in-numerical-data/
http://www.skillsyouneed.com/num/statistics-identifying-patterns.html
https://www.oreilly.com/ideas/using-design-patterns-to-find-greater-meaning-in-your-data/
I’ve been considering what additional data will be needed for the animation/objects. I think some of the basic stuff can be calculated and stored in MySQL, things like:
All these data points can be used as parameters in the animation.
How can we see communal activity, such as nearest neighbours? We need to divide the nest into 6 zones, and note which zone each animal is in at any one time. The zones might be a better way of visualising the animals rather than the sensor points, as we can have them animating to simple rules within that zone area. Sketch: https://www.flickr.com/gp/141167866@N06/7q8812
From the zones we can see which animals are sharing a zone, and which animals are neighbours (in a touching zone). We can also calculate length of time in a zone which when summed will give us a break down of activity across the nest.
i.e. a day in the life of animal 16 =
zone A 20%
zone B 5%
zone C 40%
zone D 15%
zone E 12%
zone F 8%
We can then see if we can match the pattern of one animal to another based on which zone they are in and when.
nmr_data = this is the main data, currently not live, but a lot of archive in there to play with
nmr_index = look-up table for ID to tag matching
nmr_readers = list of the reader serial numbers
nmr_records = stores date logged changes in mass, rank, genitalia and teats of each animal (many NULL)
nmr_ethogram = describes the codes used in the manual observation table
nmr_manual_obs = contains a set of behaviours for each animal in the colony (currently 11 are temporary placeholders that have the repeated oos code)
nmr_nest_distances = distances in mm from one sensor to another for the mapping animation
nmr_sensors = will store light and sound fluctuations
nmr_env = environment data, temperature (per change of 2 degrees or more) and humidity (once per hour)
The latest schema is here: https://github.com/misslake/rat.systems/blob/master/sql/nmr%20schema.sql
Today the iMac was deployed to track colony Omega (20 NMRs) using 7 sensors. The data is being stored on a local MySQL db.
deployed code on github (misslake)
estimated data logging (as determined with lights on):
24 rows of non-blank data per 30 seconds
scales up to around 70,000 per day if NMR movement frequency maintains this pace
files size: MySQL dump of 41,000 rows = 1.6MB. scales up to around 40MB per million rows
14.28 days per 40MB/million rows
System left on, with display sleep (NOT system sleep).
Our leaders are applying the methods of agribusiness cattle-raising to us: ear-tag, barcode, number, sort, record. And cull, of course.
Source: Margaret Atwood: we are double-plus unfree | Books | The Guardian
Research data:
https://www.epsrc.ac.uk/about/standards/researchdata/
“The expectations arise from seven core principles which align with the core RCUK principles on data sharing. Two of the principles are of particular importance: firstly, that publicly funded research data should generally be made as widely and freely available as possible in a timely and responsible manner; and, secondly, that the research process should not be damaged by the inappropriate release of such data.”
Research data principles: https://www.epsrc.ac.uk/about/standards/researchdata/principles/ (accessed 18th May 2015
EPSRC’s Charter is to support high-quality basic, strategic and applied research and related post-graduate training in engineering and the physical sciences, and to communicate and disseminate the resulting outcomes and knowledge. As such, EPSRC believes that the following guiding principles, which are aligned with the agreed RCUK principles on sharing of research data, should inform all decisions relating to the management of all research data that has arisen as a result of EPSRC funding:
EPSRC-funded research data is a public good produced in the public interest and should be made freely and openly available with as few restrictions as possible in a timely and responsible manner.
EPSRC recognises that there are legal, ethical and commercial constraints on release of research data. To ensure that the research process (including the collaborative research process) is not damaged by inappropriate release of data, research organisation policies and practices should ensure that these constraints are considered at all stages in the research process.
Sharing research data is an important contributor to the impact of publicly funded research. To recognise the intellectual contributions of researchers who generate, preserve and share key research datasets, all users of research data should acknowledge the sources of their data and abide by the terms and conditions under which they are accessed.
EPSRC-funded researchers should be entitled to a limited period of privileged access to the data they collect to allow them to work on and publish their results. The length of this period will depend on the scientific discipline and the nature of the research.
Institutional and project specific data management policies and plans should be in accordance with relevant standards and community best practice and should exist for all data. Data with acknowledged long term value should be preserved and remain accessible and useable for future research.
Sufficient metadata should be recorded and made openly available to enable other researchers to understand the potential for further research and re-use of the data. Published results should always include information on how to access the supporting data.
It is appropriate to use public funds to support the preservation and management of publicly-funded research data. To maximise the scientific benefit which can be gained from limited budgets, the mechanisms for managing and providing access to research data should be both efficient and cost-effective in the use of such funds.
Great idea from Max Ogden about a way to enhance the move to open data. Dat will encourage users of open data to share the scrubbed, formatted, transformed, or sync’d data back to a repository so that others can use the data without going through the same process.
What is dat?
dat is a new initiative that seeks to increase the traction of the open data movement by providing better tools for collaboration.
To illustrate the goals of dat consider the GitHub project, which is a great model of this idea working in a different space. GitHub is built on top of an open source tool called git and provides a user-friendly web application that lets software developers find code written by others, use it in their own programs and improve upon it. In a similar fashion dat will be developed as a set of tools to store, synchronize, manipulate and collaborate in a decentralized fashion on sets of data, hopefully enabling platforms analogous to GitHub to be built on top of it.
The initial prototype of dat will be developed thanks to support from the Knight Foundation as a collection of open source projects in Summer and Fall 2013 by Max Ogden and other open source contributors.
Why do dat?
Open data is a relatively new concept that is being actively supported by both United States President Barack Obama and Internet creator Tim Berners-Lee. The goal is to get those who possess data that could be useful to others to make that data publicly available. The way this is done today by making data available as read-only: you can download bulk copies of data or query a REST API but there is no standard way to share any changes you make to the data. dat seeks to take this idea further and enable a decentralized workflow where anyone can track the changes they make to data after they consume it.
A Life in AdWords, Algorithms & Data Exhaust. An interview with Erica Scourti. | http://www.furtherfield.org.
Slides from Subtlety and Softness in Data-driven Art presented 2nd October 2012 at the O’Reilly Strata Conference: Making Data Work
The slides contain data definitions and a data analysis framework developed during a research fellowship co-hosted by Seed Media Group, NY and Queen Mary University of London, summer 2012.
Links, papers, notes, inspirations from Summer 2012 in NY whilst at Seed Media.