All in Open Data
On Managing Health Data Programs: Some Thoughts After the Health Datapalooza Conference
As an extension of my own research and consulting on big data project planning and management, I wanted to improve my understanding of how data governance and program management practices impact how medical and health data are used.
What Kind of Management Structure Is Needed to Govern a Data Analytics Program?
I’m fairly “old-school” when it comes to planning and building information systems. That is, first you decide what your requirements are and what services you need to provide, then you decide which technologies you need to adapt, develop, or purchase to help you meet those requirements.
Do Health Data and Metadata Ownership Licenses Help or Hurt Innovation?
We see how the current web of licensing agreements is hobbling cable TV operators as they find themselves having to compete more and more with web based streaming services. Isn’t it also possible that similar restrictions regarding health data and metadata might provide similar challenges to creating new and beneficial products and services from shared data?
Should Clinical Trial Data Sharing Be a Precondition for Refereed Journal Article Acceptance?
To appreciate some of the implications of the recent proposal by the International Committee of Medical Journal Editors (ICMJE) to make consideration of journal article acceptance contingent upon the author’s agreement to share de-identified clinical trial data with other researchers, as reported by NPR, some context is appropriate.
Needed: Better Integration of Project Management and Data Management
These days, still, when you read about big data or if you attend conferences or webinars you’re much more likely to read about products and tools. You don’t hear as much about “back room” management issues you need to address to make sure all the members of the project team are sharing information and marching in the same direction.
Is Loss of Government Economic Survey Data Inevitable?
While it may be inevitable that all government data collection efforts have to tighten their belts, hopefully the process of making tough prioritization decisions will be done in light of rational factors such as the value of the data to users, the cost of collecting it, the availability of alternatives, and the manner in which data management processes are governed.
The Commerce Data Advisory Council's 2nd Meeting: Storytelling, Staff Recruiting, and Complex Processes
There’s an understanding represented by this group that the data resources being stewarded by Commerce programs both reflect and are critical inputs to U.S. technical and industrial competitiveness. Hopefully this group will be able to facilitate an exchange of useful “lessons learned” and resources across the varied Commerce programs.
Ten Questions for People Who Manage Large Data Intensive Projects
I’ve been researching how to manage projects where the goal is to make large amounts of data open, accessible, and useful.
10 Basic Suggestions for Planning and Managing Data Intensive Projects
It is also impossible for the project manager to ignore how data management and data governance are handled in the organization as a whole.
Problems and Opportunities with Big Data: a Project Management Perspective
Being able to make wise investments in “big data” capabilities may require more collaborative approaches to project management and decisionmaking than are currently being practiced.
Managing Data-Intensive Programs and Projects: Selected Articles
I’ve created this special compendium of posts that are relevant to planning and managing data related programs and projects. There are four groups:
I heard David Lebryk of the U.S. Department of Treasury speak on Data Act implementation this morning at the Johns Hopkins/REI Systems Government Analytics Breakfast Forum in Washington DC.
Data Program Governance and the Success of Shared Digital Services
If the tip of the data management “spear” is analyzing data in new and interesting ways to help solve important problems, someone still has to manufacture the spear, carry it, and train throwers to hit the target.
Who Gets Credit for Open Data?
The lack of easily accessible source and context information might eventually become a problem. Public programs ultimately have to depend on public funding. If the public doesn’t know the data they rely on are coming from public sources – which they pay for with their taxes — how can they be expected to make intelligent decisions about which programs to fund?
Managing Open Transportation Data at the U.S. Department of Transportation
Such challenges are not unique to the Federal Government. All large organizations desiring to take a more strategic position in how data — the lifeblood of organization processes — are managed and released will have to address such governance issues.
Dashboarding Open Data Program Governance
A key feature of the Project Open Data effort being managed by OMB and OSTP is that so much of it is being conducted in the open using accessible resources such as shared documentation, a defined metadata schema, and use of GitHub for capturing comments and issues. Agencies that want to involve private sector vendors in their open date efforts should consider the use and management of such tools as a required part of program governance and oversight (as long as sufficient staff and resources are provided to manage such efforts, of course).
Pushing for standardization of such regulatory information will greatly enhance public access and transparency — as long as effective governance and sufficient resources are made available to support the process and the systems that provide public access.
Interim Report on the Generalizability of the NOAA Big Data Project’s Management Model
It’s good to see the Federal government and private sector working together to create value from data that might not be realized were its use restricted only to specifically funded and legislated programs.
Moving to the Cloud: Business as Usual or Opportunity for Change?
Sometimes it makes sense to consider open data programs and cloud infrastructure transformation at the same time.