In a new post at TechPresident, Jeffrey Warren of Public Lab makes a full-throated argument for the need to look at the current data revolution in a new way. I encourage you to read his piece in full, but here is (as far as I see it) the gist.

Warren posits that “big data”, the concept of mining vast quantities of data to reveal underlying patterns and the hot new trend in research, business, and everywhere else, is fundamentally flawed. He argues that the more we accept big data, the more we are ceding the advantage of that data to large organizations with the infrastructure and expertise necessary to analyze it. To Warren, big data is “premised on an asymmetric — purely upward — flow of data towards a central authority whom we must trust to make decisions on our behalf.” In other words, big data risks making the powerful only more powerful.

Instead, Warren puts forward an alternative called Small Data: a “bottom-up, voluntary, shared model of data aggregation whose participants are not mere data points,” and where platforms are “built on the open exchange of data, by and for the public, towards civic ends.” It is similar to a previous argument made by Rufus Pollock of the Open Knowledge Foundation, also under the label of “small data.” To Warren, small data is not just crowdsourcing, but instead is about going a step farther, with the “public having a say in how that pooled data is used, and what questions it answers.” Warren likens it to the PC, which was the revolutionary counter to the idea that only the biggest and most powerful organizations would have access to computers. In his mind, data should go the same way.

There is much to unpack in Warren’s post, so I will refrain from tackling it all, but his argument did made me think more about two notions around data that I have not been able to get out of my head for months.

Years ago, Larry Diamond coined a term that defined a new field of research and practice. Called “Liberation Technology,” the disciple looked at how new technologies (Ushahidi, for example) are being used to advance social good, whether remote-sensors for human rights or social media for peacebuilding. Reading Warren’s post, I could not help but think that where we have failed so far is advancing a related concept: “liberation data,” the active use of data to create positive social change. The data is here to stay (and more is on the way), we need to step up and start looking at how it can, can’t, should, shouldn’t, will, and won’t be used to create a better world. Very recently there have been some steps in the right direction, for example the Data Science for Social Good summer fellowship we are participating in. But, my own (ongoing) literature review on the use of data for social good has found the topic largely devoid of activity. It is, as far as I can tell, an unexplored frontier.

In a new post at TechPresident, Jeffrey Warren of Public Lab makes a full-throated argument for the need to look at the current data revolution in a new way. I encourage you to read his piece in full, but here is (as far as I see it) the gist.

Warren posits that “big data”, the concept of mining vast quantities of data to reveal underlying patterns and the hot new trend in research, business, and everywhere else, is fundamentally flawed. He argues that the more we accept big data, the more we are ceding the advantage of that data to large organizations with the infrastructure and expertise necessary to analyze it. To Warren, big data is “premised on an asymmetric — purely upward — flow of data towards a central authority whom we must trust to make decisions on our behalf.” In other words, big data risks making the powerful only more powerful.

Instead, Warren puts forward an alternative called Small Data: a “bottom-up, voluntary, shared model of data aggregation whose participants are not mere data points,” and where platforms are “built on the open exchange of data, by and for the public, towards civic ends.” It is similar to a previous argument made by Rufus Pollock of the Open Knowledge Foundation, also under the label of “small data.” To Warren, small data is not just crowdsourcing, but instead is about going a step farther, with the “public having a say in how that pooled data is used, and what questions it answers.” Warren likens it to the PC, which was the revolutionary counter to the idea that only the biggest and most powerful organizations would have access to computers. In his mind, data should go the same way.

There is much to unpack in Warren’s post, so I will refrain from tackling it all, but his argument did made me think more about two notions around data that I have not been able to get out of my head for months.

Years ago, Larry Diamond coined a term that defined a new field of research and practice. Called “Liberation Technology,” the disciple looked at how new technologies (Ushahidi, for example) are being used to advance social good, whether remote-sensors for human rights or social media for peacebuilding. Reading Warren’s post, I could not help but think that where we have failed so far is advancing a related concept: “liberation data,” the active use of data to create positive social change. The data is here to stay (and more is on the way), we need to step up and start looking at how it can, can’t, should, shouldn’t, will, and won’t be used to create a better world. Very recently there have been some steps in the right direction, for example the Data Science for Social Good summer fellowship we are participating in. But, my own (ongoing) literature review on the use of data for social good has found the topic largely devoid of activity. It is, as far as I can tell, an unexplored frontier.

In a new post at TechPresident, Jeffrey Warren of Public Lab makes a full-throated argument for the need to look at the current data revolution in a new way. I encourage you to read his piece in full, but here is (as far as I see it) the gist.

Warren posits that “big data”, the concept of mining vast quantities of data to reveal underlying patterns and the hot new trend in research, business, and everywhere else, is fundamentally flawed. He argues that the more we accept big data, the more we are ceding the advantage of that data to large organizations with the infrastructure and expertise necessary to analyze it. To Warren, big data is “premised on an asymmetric — purely upward — flow of data towards a central authority whom we must trust to make decisions on our behalf.” In other words, big data risks making the powerful only more powerful.

Instead, Warren puts forward an alternative called Small Data: a “bottom-up, voluntary, shared model of data aggregation whose participants are not mere data points,” and where platforms are “built on the open exchange of data, by and for the public, towards civic ends.” It is similar to a previous argument made by Rufus Pollock of the Open Knowledge Foundation, also under the label of “small data.” To Warren, small data is not just crowdsourcing, but instead is about going a step farther, with the “public having a say in how that pooled data is used, and what questions it answers.” Warren likens it to the PC, which was the revolutionary counter to the idea that only the biggest and most powerful organizations would have access to computers. In his mind, data should go the same way.

There is much to unpack in Warren’s post, so I will refrain from tackling it all, but his argument did made me think more about two notions around data that I have not been able to get out of my head for months.

Years ago, Larry Diamond coined a term that defined a new field of research and practice. Called “Liberation Technology,” the disciple looked at how new technologies (Ushahidi, for example) are being used to advance social good, whether remote-sensors for human rights or social media for peacebuilding. Reading Warren’s post, I could not help but think that where we have failed so far is advancing a related concept: “liberation data,” the active use of data to create positive social change. The data is here to stay (and more is on the way), we need to step up and start looking at how it can, can’t, should, shouldn’t, will, and won’t be used to create a better world. Very recently there have been some steps in the right direction, for example the Data Science for Social Good summer fellowship we are participating in. But, my own (ongoing) literature review on the use of data for social good has found the topic largely devoid of activity. It is, as far as I can tell, an unexplored frontier.