Wednesday, November 23, 2011

My Google Scholar Citations page

I just took advantage of the opening-up of Google Scholar Citations and got my own page up. It is pretty cool to see your citations, etc. all pulled together.

Sunday, March 27, 2011

Canada not involved in Aid transparency

  1. The Aid Revolution begins with XML / The Aid Revolution Begins Here
  2. Publish What You Fund: The Global Campaign for Aid Transparency
  3. International Aid Transparency Initiative (IATI)

Very oddly, Canada (correction: Canadian government: see below) is NOT involved in this initiative, but the following countries and organizations are:
  •    World Bank
  •    Asian Development Bank
  •    The European Commission (EC)
  •    United Nations Development Programme (UNDP)
  •    Global Alliance for Vaccines and Immunisation (GAVI)
  •    Hewlett Foundation
  •    Australia - AusAID
  •    Denmark - Ministry of Foreign Affairs
  •    Finland - Ministry for Foreign Affairs
  •    Germany - Federal Ministry for Economic Cooperation and Development (BMZ)
  •   Ireland - Irish Aid
  •   Netherlands – Dutch Ministry of Foreign Affairs – Development Cooperation
  •   New Zealand – NZAID
  •   Norway - Norad
  •   Spain – Spain Ministry of Foreign Affairs and Cooperation
  •   Sweden - SIDA
  •   Switzerland - Swiss Agency for Development and Cooperation (SDC)
  •   UK - DFID
There is also no Canadian government involvement on the IATI steering committee.

    Someone should pass this on to the CBC, pointing out Canada's non-participation.
    Someone should ask all the parties in the Canadian election what their policy on this is.

    Correction: 2011.03.27 11:54:  As suggested by letters to donors ("IATI steering committee members commend donors for agreement of Standard") there is some Canadian, non-government, involvement of

    Friday, January 21, 2011

    Visualizing the relationship between different classes of digital and physical resources in a Science-policy-based Department

    Some of my work includes consulting with the Canadian Forestry Service (CFS) at Natural Resources Canada (NRCan) in the area of scientific data management, digital repositories / archiving and project management.

    Some of the work revolves around the interpretation and application of various records keeping and archival policies, such as those from Treasury Board Secretariate's Directive on Record Keeping and Library and Archives Canada. Some of these policies are difficult to interpret or are still in flux, and I have had some difficulties in interpreting the terms, definitions, etc. of these policies.

    I find that visualizing things (or the act of creating a visualization) can often help in understanding. So I've put together the following Venn diagrams to help (me mostly). I've tried to generalize to any Science-base-policy department in the government of Canada.

    Caveat: This is my own view of what I have seen and interpreted, and may be incorrect. It is not derived from any private or proprietary information. It is also very possible that this does not correspond to how NRCan, CFS, LAC and TBS view these things. I am not a government employee and this is my own view.




    Figure 1

    • There are physical and digital information resources
    • There are resources of 'business value'; some are digital, some are physical
    • Science resources are all of business value; some are digital, some are physical
    • Some resources of business value will be archived by LAC; Some science resources will be archived by LAC
    • Some (most going forward) science resources and resources of business value will be born digital


    Figure 2: Figure 1 may be a little too abstract to some, so I have a couple of exemplary and special case information resource media types to help show where these fit in to this framework.
    • Artifacts, samples, & specimens are physical resources, some of which will be sent to LAC
    • Some artifacts, samples, & specimens are science resources, some of which will be sent to LAC
    • Documents, still & moving images are both physical and digital
    • Some documents, still & moving images will be born digital
    • Some documents, still & moving images are of business value, some of which will be sent to LAC
    • Some documents, still & moving images are of science resources, some of which will be sent to LAC
    • Huge data is extremely large volume data, that is of business value
    • Huge data is mostly science resources value
    • Huge data will never be sent to LAC value




    Figure 3: Information resources not sent to LAC that are active and to be used / store over the long term need to be managed by the owning organization. This management can include institutional repositories and data centres (IRDC), along with a certain amount of process.
    • IRDC include many resources of business value
    • IRDC include most science resources
    • IRDC does not include all huge data
    • IRDC include both digital and physical resources, some documents, still & moving images and some artifacts, samples, & specimens.
    I am the most unsure of the the huge data resource. I don't have any huge data being created that is not of business value. I _think_ this is right, but there may be some use cases of which I am not aware.
    The IRDC do not include all resources of business value. Here I am thinking that the ephemeral business value resources will not make it into the IRDC. Again, I think this is correct.

    I'd appreciate any feedback on this visualization; whether it makes sense and if it is fairly successful at representing the main classes of information resources at play in science-policy-based departments.

    You can find a PDF of these diagrams on slideshare.

      Tuesday, January 11, 2011

      "We Need a Research Data Census" - Francine Berman

      Francine Berman's call for a research data census in the U.S. recognizes the reality that the valuable research assets produced by public (and private) research funding is uncounted, mostly unmanaged, and destined to be, or in the process of being, degraded, damaged and lost. Lost to future research, re-use, re-purposing.

      While a census is useful when your knowledge about a topic is effectively zero, as in this case, I don't think that it is a good ongoing solution to this particular problem. Distributed and open research data repositories, open standards like OAI-PMH, rich metadata (and the tools to create/manage them) and the will of funding agencies and research organizations can all come together to make a real-time census possible.

      But an initial census is clearly needed, in order properly discover the complete nature of the research data problem, in order to plan the processes, infrastructure and organizations to properly deal it.

      • Berman, F. 2010. We Need a Research Data Census - The increasing volume of research data highlights the need for reliable, cost-effective data storage and preservation at the national scale.Communications of the ACM 53:12:39-41 10.1145/1859204.1859220