Strengthening Local Capacity for Data-Driven Decisionmaking

Curated on Posted on by Stefaan Verhulst

A report by the National Neighborhood Indicators Partnership (NNIP): “A large share of public decisions that shape the fundamental character of American life are made at the local level; for example, decisions about controlling crime, maintaining housing quality, targeting social services, revitalizing low-income neighborhoods, allocating health care, and deploying early childhood programs. Enormous benefits would be gained if a much larger share of these decisions were based on sound data and analysis.
In the mid-1990s, a movement began to address the need for data for local decisionmaking.Civic leaders in several cities funded local groups to start assembling neighborhood and address-level data from multiple local agencies. For the first time, it became possible to track changing neighborhood conditions, using a variety of indicators, year by year between censuses. These new data intermediaries pledged to use their data in practical ways to support policymaking and community building and give priority to the interests of distressed neighborhoods. Their theme was “democratizing data,” which in practice meant making the data accessible to residents and community groups (Sawicki and Craig 1996).

The initial groups that took on this work formed the National Neighborhood Indicators Partnership (NNIP) to further develop these capacities and spread them to other cities. By 2012, NNIP partners were established in 37 cities, and similar capacities were in development in a number of others. The Urban Institute (UI) serves as the secretariat for the network. This report documents a strategic planning process undertaken by NNIP in 2012 and early 2013. The network’s leadership and funders re-examined the NNIP model in the context of 15 years of local partner experiences and the dramatic changes in technology and policy approaches that have occurred over that period. The first three sections explain NNIP functions and institutional structures and examine the potential role for NNIP in advancing the community information field in today’s environment.”

Collaboration In Biology's Century

Curated on Posted on by Stefaan Verhulst

Todd Sherer, Chief Executive Officer of The Michael J. Fox Foundation for Parkinson’s Research, in Forbes: “he problem is, we all still work in a system that feeds on secrecy and competition. It’s hard enough work just to dream up win/win collaborative structures; getting them off the ground can feel like pushing a boulder up a hill. Yet there is no doubt that the realities of today’s research environment — everything from the accumulation of big data to the ever-shrinking availability of funds — demand new models for collaboration. Call it “collaboration 2.0.”…I share a few recent examples in the hope of increasing the reach of these initiatives, inspiring others like them, and encouraging frank commentary on how they’re working.
Open-Access Data
The successes of collaborations in the traditional sense, coupled with advanced techniques such as genomic sequencing, have yielded masses of data. Consortia of clinical sites around the world are working together to collect and characterize data and biospecimens through standardized methods, leading to ever-larger pools — more like Great Lakes — of data. Study investigators draw their own conclusions, but there is so much more to discover than any individual lab has the bandwidth for….
Crowdsourcing
A great way to grow engagement with resources you’re willing to share? Ask for it. Collaboration 2.0 casts a wide net. We dipped our toe in the crowdsourcing waters earlier this year with our Parkinson’s Data Challenge, which asked anyone interested to download a set of data that had been collected from PD patients and controls using smart phones. …
Cross-Disciplinary Collaboration 2.0
The more we uncover about the interconnectedness and complexity of the human system, the more proof we are gathering that findings and treatments for one disease may provide invaluable insights for others. We’ve seen some really intriguing crosstalk between the Parkinson’s and Alzheimer’s disease research communities recently…
The results should be: More ideas. More discovery. Better health.”
 
 
 

How citizens in Tanzania and DRC are getting better health care and education through open budgets

Curated on Posted on by Stefaan Verhulst

at ONE: “Earlier this year we asked what you thought were the continent’s most important development priorities, as part of our You Choose campaign.  Health care was very near the top of the list, so now we’re on the case.
We know that better health care will save lives. Preventable and treatable diseases such as AIDS, TB, and malaria continue to kill more than 2 million people in Africa every year.
Open Budgets Save Lives aims to do two things:

  • Encourage African leaders to prioritise health care spending
  • Open up national budgets so that African citizens can see where the money is going

Transparency in government spending is an incredible tool for all of us – allowing citizens and local NGOs to hold governments accountable for spending that lines up with citizens’ priorities.
Giving citizens current, accurate and understandable budget information increases the likelihood that resources will be managed well, and used efficiently. Countries with open budgets are also more likely to line up spending with stated priorities, and ensure policy commitments are funded. Open budgets also help reduce corruption, by making it easier to draw a line between what is supposed to be spent and the results that are achieved.”

Why the world’s governments are interested in creating hubs for open data

Curated on Posted on by Stefaan Verhulst

in Gigaom: “Amid the tech giants and eager startups that have camped out in East London’s trendy Shoreditch neighborhood, the Open Data Institute is the rare nonprofit on the block that talks about feel-good sorts of things like “triple-bottom line” and “social and environmental value.” …Governments everywhere are embracing the idea that open data is the right way to manage services for citizens. The U.K. has been a leader on this — just check out the simplicity of gov.uk — which is one of the reasons why ODI is U.K. born….“Open data” is open access to the data that has exploded on the scene in recent years, some of it due to the rise of our connected, digital lifestyles from the internet, sensors, GPS, and cell phones, just to name a few resources. But ODI is particularly interested in working with data sets that can have big global and societal impacts, like health, financial, environmental and government data. For example, in conjunction with startup OpenCorporates, ODI recently helped launch a data visualization about Goldman Sachs’s insanely complex corporate structure.”

A Videogame That Recruits Players to Map the Brain

Curated on Posted on by Stefaan Verhulst

Wired: “I’m no neuroscientist, and yet, here I am at my computer attempting to reconstruct a neural circuit of a mouse’s retina. It’s not quite as difficult and definitely not as boring as it sounds. In fact, it’s actually pretty fun, which is a good thing considering I’m playing a videogame.
Called EyeWire, the browser-based game asks players to map the connections between retinal neurons by coloring in 3-D slices of the brain. Much like any other game out there, being good at EyeWire earns you points, but the difference is that the data you produce during gameplay doesn’t just get you on a leader board—it’s actually used by scientists to build a better picture of the human brain.
Created by neuroscientist Sebastian Seung’s lab at MIT, EyeWire basically gamifies the professional research Seung and his collaborators do on a daily basis. Seung is studying the connectome, the hyper-complex tangle of connections among neurons in the brain.”

The Shame Game: U.S. Department of Labor Smartphone App Will Allow Public to Effortlessly Scrutinize Business Employment Practices

Curated on Posted on by Stefaan Verhulst

Charles B. Palmer in National Law Review: “The United States Department of Labor (DOL) recently launched a contest to find a new smartphone app that will allow the general public to effortlessly search for and scrutinize businesses and employers that have faced DOL citations. Dubbed the DOL Fair Labor Data Challenge, the contest seeks app entries that integrate information from consumer ratings websites, location tracking services, DOL Wage & Hour Division (WHD) citation data, and Occupational Safety & Health Administration (OSHA) citation data, into one software platform. In addition, the contest also encourages app developers to include other features in their respective app entries, such as information from state health boards and various licensing agencies.
The DOL Fair Labor Data Challenge is part of the DOL’s plan to amplify its enforcement efforts through increased public awareness and ease of access to citation data. Consumers and job applicants will soon be able to search for and publicly shame employers that hold one or more citations in the DOL database, all by just using their smartphones.”

Can We Build A Kickstarter For Cancer?

Curated on Posted on by Stefaan Verhulst

Paul Howard in Forbes: “tarting you own band, writing your first novel, or re-publishing your favorite ‘80s tabletop RPG are all cool goals. You can do them all on Kickstarter. What would be cooler?
How about funding a virtual biotech company with one goal: Saving or extending the life of a cancer patient who doesn’t respond to “standard of care” treatments….
The Cancer Commons approach – a distributed framework for empowering patients and learning from every patient/treatment combination – breaks down traditional distinctions between clinical trials and patient treatment in the “real world.” Instead of developing treatments in a lab and then testing them on randomized patients in clinical trials (designed to benefit future patients), researchers would apply the latest scientific knowledge and tools to help each patient achieve the best possible outcome today based on what we know – or think we can predict – about a molecular subtype of cancer….
We’ll need more than money to power a Kickstarter-for-cancer movement. We’ll need to encourage companies – from Big Pharma to “small” biotechs – to participate in distributed, Bayesian trials where new biomarkers or combinations of biomarkers are tested in patients with particular molecular profiles. And the FDA is going to have to be convinced that the system is going to generate high quality data that benefits patients, not sell them snake-oil cures.
In return for companies making their compound libraries and experimental drugs available for the “virtual biotechs” launched by cancer patients and their families, there should be a regulatory path established to take the most promising drugs and drug combinations to market.”

The Internet generation will learn to let go

Curated on Posted on by Stefaan Verhulst

Julian B. Gewirtz and Adam B. Kern in The Washington Post: “Ours is the first generation to have grown up with the Internet. The first generation that got suspended from school because of a photo of underage drinking posted online. The first generation that could talk in chat rooms to anyone, anywhere, without our parents knowing. The first generation that has been “tracked” and “followed” and “shared” since childhood.
All this data will remain available forever — both to the big players (tech companies, governments) and to our friends, our sort-of friends and the rest of civil society. This fact is not really new, but our generation will confront the latter on a scale beyond that experienced by previous generations…
Certainly there will be many uses for information, such as health data, that will wind up governed by law. But so many other uses cannot be predicted or legislated, and laws themselves have to be informed by values. It is therefore critical that people establish, with their actions and expectations, cultural norms that prevent their digital selves from imprisoning their real selves.
We see three possible paths: One, people become increasingly restrained about what they share and do online. Two, people become increasingly restrained about what they do, period. Three, we learn to care less about what people did when they were younger, less mature or otherwise different.
The first outcome seems unproductive. There is no longer much of an Internet without sharing, and one of the great benefits of the Internet has been its ability to nurture relationships and connections that previously had been impossible. Withdrawal is unacceptable. Fear of the digital future should not drive us apart.
The second option seems more deeply unsettling. Childhood, adolescence, college — the whole process of growing up — is, as thinkers from John Locke to Dr. Spock have written, a necessarily experimental time. Everyone makes at least one mistake, and we’d like to think that process continues into adulthood. Creativity should not be overwhelmed by the fear of what people might one day find unpalatable.
This leaves the third outcome: the idea that we must learn to care less about what people did when they were younger or otherwise different. In an area where regulations, privacy policies and treaties may take decades to catch up to reality, our generation needs to take the lead in negotiating a “cultural treaty” endorsing a new value, related to privacy, that secures our ability to have a past captured in data that is not held to be the last word but seen in light of our having grown up in a way that no one ever has before.
Growing up, that is, on the record.”

Big data  + politics = open data: The case of health care data in England

Curated on Posted on by Stefaan Verhulst

New Paper in Policy & Internet: “There is a great deal of enthusiasm about the prospects for Big Data held in health care systems around the world. Health care appears to offer the ideal combination of circumstances for its exploitation, with a need to improve productivity on the one hand and the availability of data that can be used to identify opportunities for improvement on the other. The enthusiasm rests on two assumptions. First, that the data sets held by hospitals and other organizations, and the technological infrastructure needed for their acquisition, storage, and manipulation, are up to the task. Second, that organizations outside health care systems will be able to access detailed datasets. We argue that both assumptions can be challenged. The article uses the example of the National Health Service in England to identify data, technology, and information governance challenges. The public acceptability of third party access to detailed health care datasets is, at best, unclear.”

Data Science for Social Good

Curated on Posted on by Stefaan Verhulst

Data Science for Social Good: “By analyzing data from police reports to website clicks to sensor signals, governments are starting to spot problems in real-time and design programs to maximize impact. More nonprofits are measuring whether or not they’re helping people, and experimenting to find interventions that work.
None of this is inevitable, however.
We’re just realizing the potential of using data for social impact and face several hurdles to it’s widespread adoption:

  • Most governments and nonprofits simply don’t know what’s possible yet. They have data – but often not enough and maybe not the right kind.
  • There are too few data scientists out there – and too many spending their days optimizing ads instead of bettering lives.

To make an impact, we need to show social good organizations the power of data and analytics. We need to work on analytics projects that have high social impact. And we need to expose data scientists to the problems that really matter.

The fellowship

That’s exactly why we’re doing the Eric and Wendy Schmidt Data Science for Social Good summer fellowship at the University of Chicago.
We want to bring three dozen aspiring data scientists to Chicago, and have them work on data science projects with social impact.
Working closely with governments and nonprofits, fellows will take on real-world problems in education, health, energy, transportation, and more.
Over the next three months, they’ll apply their coding, machine learning, and quantitative skills, collaborate in a fast-paced atmosphere, and learn from mentors in industry, academia, and the Obama campaign.
The program is led by a strong interdisciplinary team from the Computation institute and the Harris School of Public Policy at the University of Chicago.”