The data divide between the "haves" and the "have nots" - Are First Nations ready?
The opportunity for Owning, Controlling, Accessing and Possessing (ie. the principles of OCAP) the data / information about each First Nation is an important challenge that the community leaders and administration is presently facing. What information will be shared and who will take care of the First Nation information about the people, the lands and the resources are questions that are being asked. Often it is the Canadian government who is releasing information to the media that provides their view of the information about First Nations that is written about and presented to the public.
Why Open Data Alone Is Not Enough
By Jesse Lichtenstein - June 28, 2011
If you care about transparency, these are interesting times. WikiLeaks may have faded from the headlines, but growing numbers of people accept the notion that information collected by and about the government should be online, searchable, and mashable.
At least 16 nations have major open data initiatives; in many more, pressure is building for them to follow suit. The US has posted nearly 400,000 data sets at Data.gov, and organizations like the Sunlight Foundation and MAPlight.org are finding compelling ways to use public data—like linking political contributions to political actions. It’s the kind of thing that seems to prove Louis Brandeis’ famous comment: “Sunlight is said to be the best of disinfectants.” But transparency alone is not a panacea, and it may even have a few nasty side effects. Take the case of the Bhoomi Project, an ambitious effort by the southern Indian state of Karnataka to digitize some 20 million land titles, making them more accessible. It was supposed to be a shining example of e-governance: open data that would benefit everyone and bring new efficiencies to the world’s largest democracy. Instead, the portal proved a boon to corporations and the wealthy, who hired lawyers and predatory land agents to challenge titles, hunt for errors in documentation, exploit gaps in records, identify targets for bribery, and snap up property. An initiative that was intended to level the playing field for small landholders ended up penalizing them; bribery costs and processing time actually increased.
A level playing field doesn’t mean much if you don’t know the rules or have the right sporting equipment. Uploading a million documents to the Internet doesn’t help people who don’t know how to sift through them. Michael Gurstein, a community informatics expert in Vancouver, British Columbia, has dubbed this problem the data divide. Indeed, a recent study on the use of open government data in Great Britain points out that most of the people using the information are already data sophisticates. The less sophisticated often don’t even know it’s there.
Data divides have consequences. Consider the recent adventures in the financial markets: The quants on Wall Street applied their savvy to manipulate theoretically open data for personal gain. Or look at the catastrophic effects of bundling unacceptable real estate risk into something that, to the less data-savvy, appeared to be financially sound mutual funds. The reality of these data divides is that information is anything but transparent to the majority of people—even if it’s technically available.
India also passed a Right to Information Act in 2005, requiring governments and agencies to digitize many records and respond quickly to any citizen’s request for information. It has the potential to shine light on pervasive inefficiencies and rampant corruption. But so far it’s helped only the middle class, not the massive underclass, which remains at risk of intimidation and violence. (Far from being encouraged to use open data, many have been murdered for doing so. The Guardian calls people silenced in this manner “Right to Information martyrs.”)
The concern that open data may simply empower the empowered is not an argument against open data; it’s an argument against looking at open data as an end in itself. Massive data dumps and even friendly online government portals are insufficient. Ordinary people need to know what information is available, and they need the training to be conversant in it. And if people are to have anything more than theoretical access to the information, it needs to be easy and cheap to use. That means investing in the kinds of organizations doing outreach, advocacy, and education in the communities least familiar with the benefits of data transparency. If we want truly open government, we still have to do the hard work of addressing basic and stubborn inequalities. However freely it flows, the data alone isn’t enough.
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A Data Divide? Data “Haves” and “Have Nots” and Open (Government) Data
Posted on July 11, 2011 by Michael Gurstein
The notion and substance of a “Digital Divide” has been very extensively discussed and researched. The definition, at its most basic, is that the “Digital Divide” is the “divide” between those who have access to Information and Communications Technologies (ICTs) and particularly the Internet and those who don’t have such access.
(I’ve covered a lot of this below in earlier blog posts and elsewhere but my intention in presenting this here in this form at this time is to raise and focus the discussion of a “Data Divide”particularly for Open Government Data now, when things are still somewhat in flux, and there is the real possibility of those most directly involved–data designers and government folks–paying some attention and intervening in a positive way.)
Researchers have extensively explored the range of social, economic, geographical and other barriers which underlie and to a considerable degree “explain” (cause) the Digital Divide. My own contribution has been to argue that “access is not enough”, it is whether opportunities and pre-conditions are in place for the “effective use” of the technology particularly for those at the grassroots.
The idea of a possible parallel “Data Divide” between those who have access and the opportunity to make effective use of data and particularly “open data” and those who do not, began to occur to me. I was attending several planning/recruitment events for the Open Data “movement” here in Vancouver and the socio-demographics and some of the underlying political assumptions seemed to be somewhat at odds with the expressed advocacy position of “data for all”.
Thus the “open data” which was being argued for would not likely be accessible and usable to the groups and individuals with which Community Informatics has largely been concerned – the grassroots, the poor and marginalized, indigenous people, rural people and slum dwellers in Less Developed countries. It was/is hard to see, given the explanations, provided to date how these folks could use this data in any effective way to help them in responding to the opportunities for advance and social betterment which open data advocates have been indicating as the outcome of their efforts.
As I presented this uneasiness in public fora and through my blog it became additionally clear that many involved in “open data” saw their interests and activities being confined to making data ‘legally” and “technically” accessible — what happened to it after that was somebody else’s responsibility. And with this I partially agree. Ensuring the broadest opportunity for the use of (for example) Open (Government) Data (OGD) is a broad public responsibility which of course, is shared between public authorities and technical developers; with however, the technical developers having the responsibility (IMHO) to ensure that from their – technical – side no barriers are introduced (and technical barriers are removed) to allowing for the broadest possible public use of the data where they are undertaking their activities.
As I thought more actively on these issues I realized that while there were striking parallels between the Digital Divide and what I was rapidly coming to see as an associated “Data Divide” there were also very substantial and significant differences –notably while the Digital Divide deals with, for the most part “infrastructure” issues, the Data Divide is concerned with “content” issues.
As well, where a Digital Divide might exist for example, as a result of geographical or policy considerations and thus have uniform effects on all those on the wrong side of the “divide” whatever their socio-demographic situation; a Data Divide and particularly one of the most significant current components of the Open Data movement i.e. OGD, would have particularly damaging negative effects and result in particularly significant lost opportunities for the most vulnerable groups and individuals in society and globally. (I’ve discussed some examples here at length in a previous blogpost.)
The Data Divide thus would be the gap between those who have access to and are able to use Open (Government) Data and those who are not so enabled.
I have suggested elsewhere that there are seven layers/components through which a “Data Divide” (building on my similar analysis of the Digital Divide”) might be understood:
1. infrastructure—being on the wrong side of the “Digital Divide” and thus not having access to the basic infrastructure supporting the availability of OGD.
2. devices—OGD that is not universally accessible and device independent (that only runs on I-Phones for example)
3. software—“accessible” OGD that requires specialized technical software/training to become “usable”
4. content—OGD not designed for use by those with handicaps, non-English speakers, those with low levels of functional literacy for example
5. interpretation/sense-making—OGD that is only accessible for use through a technical intermediary and/or is useful only if “interpreted” by a professional intermediary
6. advocacy—whether the OGD is in a form and context that is supportive for use in advocacy (or other purposes) on behalf of marginalized and other groups and individuals
7. governance—whether the OGD process includes representation from the broad public in its overall policy development and governance (not just lawyers, techies and public servants).
Intervening at this relatively early stage – whether by Open Data designers or through government (or other) policy and programmes (or most desirably both) –can help to avoid a Data Divide and preclude many of the negative effects (and relatively costly make up efforts) and lost opportunities associated with the Digital Divide.
My strong suggestion/hope would be that a minimum of 10% of expenditures on OGD would go to ensuring that structures of “data haves” and “data have nots’ was not being created as an outcome of OGD projects. Contributions to training for data use, for digital literacy, for disability oriented user interface design, to support advocacy based on OGD, for ensuring that OGD is not device dependent, to assist in participation in OGD governance and others would go some way in ensuring this outcome.