Here's an inspiring and insightful article by Sally Whiting on ContentsMagazine analyzing the role of the archivist and the traits and responsibilities that make his work so valuable to content producers.
She writes: “Applying archival principles to content strategy makes for solid content—I can demonstrate this, and I exercise it in my work.”
As content curators will increasingly need to learn more about archiving, organizing and preserving what they curate, this article provides an inspiring set of considerations about the key value of context and provenance.
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In addition she poses some important questions about what could actually be done by better curating our own content archives:
“Archives are accustomed to a passive role, asking reflectively what their patrons want to find.
As they work to help researchers tell their stories, it’s easy for archives to forget to keep shaping their own.”
Local communities in Uganda send UNICEF some 10,000 text messages (SMS) every week. These messages reflect the voices of Ugandan youths who use UNICEF’s U-report SMS platform to share their views on a range of social issues. Some messages are responses to polls created by UNICEF while others are unsolicited reports of problems that youths witness in their communities. About 40% of text messages received by UNICEF require an SMS reply providing advice or an answer to a question while 7% of messages require immediate action. Over 220,000 young people in Uganda have enrolled in U-report, with 200 to 1,000 new users joining on daily basis. UNICEF doesn’t have months or the staff to manually analyze this high volume and velocity of incoming text messages. This is where advanced computing comes in.
There are over half-a-billion Twitter users, with an average of 135,000 new users signing up on a daily basis (1). Can emergency management and disaster response organizations win over some Twitter users by convincing them to use their apps in addition to Twitter? For example, will FEMA’s smartphone app gain as much “market share”? The app’s new crowdsourcing feature, “Disaster Reporter,” allows users to submit geo-tagged disaster-related images, which are then added to a public crisis map. So the question is, will more images be captured via FEMA’s app or from Twitter users posting Instagram pictures?
This question is perhaps poorly stated. While FEMA may not get millions of users to share disaster-related pictures via their app, it is absolutely critical for disaster response organizations to explicitly solicit crisis information from the crowd. See my blog post “Social Media for Emergency Management: Question of Supply and Demand” for more information on the importance demand-driven crowdsourcing. The advantage of soliciting crisis information from a smartphone app is that the sourced information is structured and thus easily machine readable. For example, the pictures taken with FEMA’s app are automatically geo-tagged, which means they can be automatically mapped if need be.
While many, many more picture may be posted on Twitter, these may be more difficult to map. The vast majority of tweets are not geo-tagged, which means more sophisticated computational solutions are necessary. Instagram pictures are geo-tagged, but this information is not publicly available. So smartphone apps are a good way to overcome these challenges. But we shouldn’t overlook the value of pictures shared on Twitter. Many can be geo-tagged, as demonstrated by the Digital Humanitarian Network’s efforts in response to Typhoon Pablo. More-over, about 40% of pictures shared on Twitter in the immediate aftermath of the Oklahoma Tornado had geographic data. In other words, while the FEMA app may have 10,000 users who submit a picture during a disaster, Twitter may have 100,000 users posting pictures. And while only 40% of the latter pictures may be geo-tagged, this would still mean 40,000 pictures compared to FEMA’s 10,000. Recall that over half-a-million Instagram pictures were posted during Hurricane Sandy alone.
Social media networks are evolving a new nervous system for our planet. These real-time networks provide immediate feedback loops when media-rich societies experience a shock. My colleague Todd Mostak recently shared the tweet map below with me which depicts tweets referring to “marathon” (in red) shortly after the bombs went off during Boston’s marathon. The green dots represent all the other tweets posted at the time. Click on the map to enlarge. (It is always difficult to write about data visualizations of violent events because they don’t capture the human suffering, thus seemingly minimizing the tragic events).
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Visualizing a social system at this scale gives a sense that we’re looking at a living, breathing organism, one that has just been wounded. This impression is even more stark in the dynamic visualization captured in the video below.
What this post is about: Society’s collective intelligence needs to be able to see clearly what’s going on and take action about it. Both NSA surveillance and corporate suppression of activism interfere with that vital dynamic. This post clarifies what’s going on in these dynamics and suggests strategies to counter them and increase society’s collective intelligence.
Any healthy living system will try to weed out challenges that threaten its functioning. That’s what immune systems do: they preserve business-as-usual in a body.
But this natural maintenance activity of a system can be counterproductive:
(a) when changing circumstances demand adaptive responses, when the system NEEDS to change its business-as-usual – and
(b) when the system has been parasitized by something that is using it for the parasite’s own purposes at the larger system’s expense.
This data visualization (click to enlarge) displays more than 23,500 photos taken in Brooklyn and posted to Instagram during Hurricane Sandy. A picture’s distance from the center (radius) corresponds to its mean hue while a picture’s position along the perimeter (angle) corresponds to the time that picture was taken. ”Note the demarcation line that reveals the moment of a power outage in the area and indicates the intensity of the shared experience (dramatic decrease in the number of photos, and their darker colors to the right of the line)” (1).
Phi Beta Iota: Each dot is an actual photograph with time and space tag. It is the first step toward streaming video from aggregated individual hand-held camera shots.
From accommodation to cars, the internet is turning us from consumers into providers and challenging established business models. We talk to Martin Varsavsky, founder of Fon – the largest Wi-Fi company in the world – and profile two more pioneers, from TaskRabbit.com and BlaBlaCar.com
In 2006, serial entrepreneur and investor Martín Varsavsky – inspired by a conviction that he could cloak the world in free Wi-Fi by encouraging people to share their home connections – founded Fon in Madrid. The company is now the largest Wi-Fi network in the world, with almost 12m hot spots in more than 100 countries.
“My general thinking at the time was that we live in a world in which benefits are only accrued through economic growth and the endless consumption of resources, and that there have to be other ways that are of more benefit to people,” he says. “Why should everyone have their own car when most of the time they are not using them? Think of a marina full of boats. How frequently do those boats go out?”
Today, it has been argued that the sharing economy – which is perhaps best defined as a way of sweating underutilised assets, by building communities around them and turning consumers into providers – has the potential to reboot businesses across most economic categories. Indeed, Forbes magazine recently estimated that total revenues for the sector could top $3.5bn this year, with growth exceeding 25%. However, when setting up Fon, Varsavsky became convinced that people needed a nudge or financial incentive before they'd happily share their assets.
