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'The future of podcasting is adaptive, open and data ethical' aimed to provide an insight into what podcasting may look like in the near-future, using Object-Based Media. As it turns out, this future is exciting, and may be closer than it seems!

Cathy Loughran coverage of BBC Data day

"Timeline Storyteller is an expressive browser-based visual storytelling environment for presenting timelines. You can use Timeline Storyteller to present different aspects of your data using a palette of timeline representations, scales, and layouts, as well as controls for filtering, highlighting, and annotation. You can export images of a timeline or assemble and record a story about your data and present it within the application. "

"TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well."

Apply Magic Sauce is a non-profit academic research project coordinated by the University of Cambridge Psychometrics Centre. The demos and platforms available here are a modest attempt to reverse the trend in Big Data and empower citizens to not only retain control of their data but also derive meaningful insight from it.

The Watson Personality Insights service uses linguistic analytics to extract a spectrum of cognitive and social characteristics from the text data that a person generates through blogs, tweets, forum posts, and more. "

"I gave them an insight into my personality. They gave me a menu to match my tastes."

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

@interchangeling: Remember when Intel turned your life into a museum exhibition using Facebook data? You will, with #PerceptiveMedia http://t.co/6EoOcBCy http://twitter.com/interchangeling/status/167428765067116544

Apple is seeking a patent on something it calls "Inferring user mood based on user and group characteristic data" that its application says would figure out how you are feeling and "... then deliver content that is selected, at least in part, based on the inferred mood."

"A bus stop poster which evolved over time depending on how people responded to it has recently been tested in London. It is part of a wider area of research into how our emotional responses and biometric data could teach advertisers how to target people according to their mood."

"Big data opens up a hyper-personalised marketing opportunity - but creative treads a thin line between relevance and invasiveness"

Technology for real-time sharing of 2D/3D data

"The move towards end-to-end IP between media producers and audiences will make new broadcasting systems vastly more agnostic to data formats and to diverse sets of consumption and production devices. In this world, object-based media becomes increasingly important; delivering efficiencies in the production chain, enabling the creation of new experiences that will continue to engage the audience and giving us the ability to adapt our media to new platforms, services and devices."

Channel 4 is bolstering its video on demand advertising package with a new ad format that can directly address viewers by their name. Accessing registration data, the company can directly address viewers with an audio personalised digital ad campaign.

Future Macs may adjust their audio depending on where you're sitting or standing - and based on how many folks are in a room. Apple has filed for a patent (number 20170249122) for "devices with enhanced audio." The patent involves a system for enhancing audio including a Mac and an output device. The Mac includes a sensor configured to determine a user location relative to the computer. The sensor is also configured to gather environment data corresponding to an environment of the computer.