Jason Hare's Data Management Blog

By Dennis D. McDonald, Ph.D. dmcdonald@balefireglobal.com Introduction How important are costs when you are planning an open data program? Are they, as suggested by Rebecca Merrett in Addressing cost and privacy issues with open data in government , the "… elephant in the room," especially when data anonymization costs are being considered? Or are such costs just a normal consideration when planning any project where quantities of different types of data have to be manipulated and delivered? It's difficult to make a generalization about this. Open data program costs can fall along at least three general dimensions: 1. Controlled versus uncontrolled 2. Known versus unknown 3. Startup versus ongoing 1. Controlled versus uncontrolled Why worry about what you can’t control? The answer is because they can impact your program whether you control them or not. Examples of uncontrolled costs might be: Taxes, licensing, insurance, and registration fees. Staff salaries that can'

By Dennis D. McDonald, Ph.D., Balefire Global, dmcdonald@balefireglobal.com During the brainstorming session at the inaugural meeting of the Open Data Enthusiasts meet up last week in Washington DC, attendee David Luria commented that we need to do a better job of understanding, defining, and communicating the objectives of open data programs if we want them to be successful. I couldn't agree more. Program objectives need to be clearly defined and shared with stakeholders and program participants so that everyone is marching in the same direction. If we don't understand and agree on our objectives how can we establish requirements and metrics to measure what we're trying to accomplish? Admittedly the above principle is straight out of Project Management 101 and describes the initial steps you need to take in planning and documenting any project, not just those involving open data. Still, what I have noticed after involvement with many data related projects is that there a

In May of this year, Asian and European countries met for the regional Open Government Partnership summits to once again discuss transparency and open government. In light of the session tracks that were presented I am evaluating some of the technologies of the past and how there has been a welcome and fundamental shift from Open Government and Open Data being ambiguously linked toward the separation of the two in more current thinking and in technology approaches. Most notably, the deprecation of Microsoft's Open Government Data Initiative platform is a positive sign of the times that the government community is becoming aware of the danger of open government and open data linking. Harlan Yu and David G. Robinson discussed the OGP in "The New Ambiguity of Open Government" (Princeton CITP/Yale ISP Working Paper).   "The Open Government Declaration is broad approach toward 'openness,' as signatories commit to 'seeking

By Dennis D. McDonald, Ph.D., Balefire Global, dmcdonald@balefireglobal.com Introduction In Management Needs Data Literacy to Run Open Data Programs I addressed the question of how much “data literacy” open data program managers need. I outlined a series of topics corresponding to different parts of the data management lifecycle the program managers need to be familiar with. While certainly I don't believe it is necessary for all program managers to be “data scientists” to manage open data programs effectively, I do think that there are certain data related skills that managers do need. One of the most important is the ability to think about data both from analytical as well as structural perspectives. The analytical perspective Analytically, managers need to understand that useful data are not just random collections of numbers but represent patterns and trends that can be used to tell stories about the objects or events with which the numbers are associated. The range of tools

In response to "The Potential of Open Data" published by Deirdre Lee, at the Insight Centre for Data Analytics, NUI Galway (www.insight-centre.org), I offer my opinion on the health of the government's open data efforts to date. Ireland needs to take a page from Sir Francis Maude and not the US. The US open data initiative is an embarrassment. Embrace "Data is the 21st century’s new raw material." The Beginning of Open Data in Ireland To be fair, Ireland is just beginning the road to open data after an internal struggle stretching back five years. The Irish Minister of Reform, Brendan Howlin, has also wisely eliminated FOI fees for information requests. This FOI issue has long been a point of political divisiveness in Ireland. Indeed at the Open Government Partnership Summit in Dublin this past year, I witnessed street demonstrations against FOI. Government creates an Open Data Initiative In late January, a tender was issued by the CIO of Ireland, William

  In the Beginning In response to " The Potential of Open Data " published by Deirdre Lee, at the Insight Centre for Data Analytics, NUI Galway ( www.insight-centre.org ), I offer my opinion on the health of the government's open data efforts to date. Ireland needs to take a page from Sir Francis Maude and not the US. The US open data initiative is an embarrassment. Embrace "Data is the 21st century’s new raw material." The Beginning of Open Data in Ireland To be fair, Ireland is just beginning the road to open data after an internal struggle stretching back five years. The Irish Minister of Reform, Brendan Howlin, has also wisely eliminated FOI fees for information requests. This FOI issue has long been a point of political divisiveness in Ireland. Indeed at the Open Government Partnership Summit in Dublin this past year I witnessed street demonstrations against FOI. Government creates an Open Data Initiative In late January, a tender was issued by the CIO of I

By Dennis D. McDonald, Ph.D., Balefire Global, dmcdonald@balefireglobal.com It makes sense that, if you devote time and energy to designing, ramping up, and managing an open data program, you're doing so for a reason. In What does the term “program alignment” mean when applied to open data programs? I made the assumption that you will want to align your open data program with the sponsoring organization’s goals and objectives and then measure the open data program’s performance by whether or not these goals and objectives are supported. I did mention a caveat: you can't always predict how the data provided through your open data program are used, what all the uses of your data and up being, who the users are, and what the benefits of these uses might be, given your lack of control over how your data might be re-used and re-shared. If this is so, how concerned should you be about the secondary and tertiary uses made of your program’s open data? Perhaps the data you’re distribu