data – Translating Data

Data for Life – notes

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 medialabkatowice eu en projects data driven city

Data-Driven Methods for City Research and Exploration

Movebank – animal track data hosting

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…

Stamen – process exposition on mapping emotion to data vis https://hi.stamen.com/embracing-the-abstract-in-visualized-data-47044cee8bd3#.onscse3a4

find and replace SQL

UPDATE `tablename` SET `fieldname` = replace(`fieldname`, ‘UNWANTED-TEXT’, ‘WANTED-TEXT’)

http www r bloggers com simple pattern detection…

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/

NMR 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: distance travelled (per day, stored per nmr; cumulative since beginning of data) speed (average per day; current – based on last x mins) days alive (current –… Continue reading NMR data

Updated schema for RAT.systems

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… Continue reading Updated schema for RAT.systems

NMR tracking – Omega

started: 2015-11-20 11:18:00.854 data dump: 2015-11-23 10:49:05.320 44015 rows

1st test – NMR tracking in lab (local version)

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… Continue reading 1st test – NMR tracking in lab (local version)

Margaret Atwood: we are double-plus unfree

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

The Live Wire by Natalie Jeremijenko

Source: tech90s: Natalie Jeremijenko

EPSRC research data principles

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… Continue reading EPSRC research data principles

dat: A Collaborative Data repo

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… Continue reading dat: A Collaborative Data repo

A Life in AdWords, Algorithms & Data Exhaust. Interview with Erica Scourti.

A Life in AdWords, Algorithms & Data Exhaust. An interview with Erica Scourti. | www.furtherfield.org.

Subtlety & Softness in Kinetic Data-driven Art @ Strata Conference

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. Download PDF

Research Archive (Summer 2012)

Links, papers, notes, inspirations from Summer 2012 in NY whilst at Seed Media. translatingdata.wordpress.com

Definitions

Of Living: Biological
Data whose origin is directly linked to something that is alive. Data that occurs without conscious origin (i.e. not from a human typing). Often from sensors. Examples: a) species migration reported by a sensor; b) quantified self data such as output from a heart-rate monitor; c) a bird-call.

Of Living: Environmental
Data whose origin is directly linked to the natural world. Often from sensors. Examples: a) ocean temperature, b) solar storm activity, c) seed bank information.

Of Non-Living: Object
Data whose origin is a physical object or device. Object data is often generated for machine to machine communication, however, the Internet of Things will see a greater machine to (human) consumer communication. Examples: a) a fridge’s energy use; b) a CCTV camera; c) a smart watch.

Of Social Context: Commercial
Data produced by or about a corporate entity. Examples: a) 10 years of financial information about a company; b) the expiry date on a chocolate bar.

Of Social Context: Personal
Data produced by or about an individual. Certain types will have restricted access, and some legal and technical protections. Other will be accessible by some, if not all, of the general public. Examples: a) Google’s search analysis profile of a non-anonymised individual’s interests; b) International travel logs held at border controls; c) a recording of a private telephone conversation; d) family photos publicly tagged on Flickr; e) your social network feed.

Of Social Context: Social
Data produced by or about a social group or society. Examples; a) global number of births each day; b) voting preference in a London borough; c) immigration figures.

Of Social Context: State
Data produced by or about a government or ruling authority. Examples: a) the economy of the eurozone; b) legislation documents.

Of Licence: Closed
Closed data is generally only accessible to people within an organisation or to certain individuals. Examples: a) company personnel files; b) national security documents.

Of Licence: Open
Open data can be accessed, used, and shared by anyone. Examples: a) state-owned weather records, b) earthquake monitoring data.

Of Licence: Shared
Shared data is data available to a specific group of people for a specific purpose. Examples: a) the electoral register; b) anonymized supermarket shopping patterns.

Of Time/Space: Geospatial
Data describing, is relevant to, or is derived from a space or geographic area. Examples: a) GPS coordinates from a cross-country walk; b) the number of people visiting the Tate Modern art gallery; c) the area of a baseball pitch; d) longitude and latitude.

Of Time/Space: Live
Data which is, or was, captured in real-time. The recording does not necessarily get played-back at the same rate, or in the same moment. Examples: a) a football match on TV; b) animal tracking data.

Of Time/Space: Real-time
Data that is created, captured and disseminated in an immediate (ish) time-frame relative to the context of its use; it changes over time. Examples: a) smart-meter reporting electricity usage every 30 seconds (real-time data acquisition with a relevant-time display); b) feeds from sensors such as a webcam on a birds nest, a GPS location of a mobile phone, or a humidity reading in an gallery space.

Of Time/Space: Static
Data in which the items do not change once created, but the dataset can grow over time. Includes historical datasets and archive indexes. Examples: a) historical global population size; b) a recording in the sound archive at the British Library.

Of Time/Space: Temporal
Data which is time-based in its nature, relevant to a specific time or which may only exist for a short time period (transient). Examples: a) the value of a kilogram of rice over time; b) your date of birth; c) the radio signals received from an exploding star.

Of Type: Anecdata
Anecdotal information gathered and then presented as evidence. Anecdata is often not precisely measurable, has no reliable provenance, is hard to compare, and /or cannot be unproven by the scientific method. Examples: a) a collection of comments on a product website; b) proverbs such as ”Never look a gift horse in the mouth”.

Of Type: Causal
Data in which it is (or is made) obvious to the observer what its origin is. Example: a vocal recording.

Of Type: Generated
Data created by a software program. Examples: a) algorithmic music; b) cellular automaton; c) a model of a galaxy exploding.

Of Type: Metadata
Data about data. Data which describes information about other data. Examples: a) the number of rows in a database; b) the time and date a phone call was made.

Of Type: Processed
Data which has been calculated, altered or processed in some way. Examples: a) a sonification of stock market figures; b) aggregated statistics; c) a colourful digital photograph reduced to black and white.

Of Type: Retrieved
Data made available on request by machine or user. Examples: a) compilation of weather data from the past 24 hours as a single CSV file; b) availability status of a library book.

Of Type: Streamed
The technical means of delivering real-time data as a contiguous stream. The primary use-cases are where there is no requirement for data storage, or that the data-sets involved are too large to be manipulated in any other manner (the entire Twitter back catalogue). Examples: a) real-time audio and video from a carnival procession; b) on-demand replay of a film from 1960; c) music playing from a digital radio.

Of Disclosure: Anonymised
Data that has had any identifiable in- formation about a person, animal, or thing removed. Examples: a) CCTV camera footage containing people which have been blurred or obfuscated; b) all bicycle hire users across a city with user IDs and names removed.

Disclosure: Identifiable
Data in which the direct source within it (person, animal, or thing) can be identified. Examples: a) a Facebook data export including friend names; b) a set of mobile phone numbers with owner address details.

Of Disclosure: Unknown
Data which contains information about a person, animal, or thing but in which it is not clear if it is adequately anonymised. Examples: a) a live Twitter feed containing some geolocated photos of people and animals; b) a sound recording from a public space that includes ambient conversation.