Genealogy & Data Management
Some of you may be aware that my ‘day’ job involves benchmarking organizations against various process and business improvement models (see: PEP) . If you are reading this note on ManyRoads, you most certainly are aware that I have a passion for genealogy (as my daughter might say: “No Duh.”).
What I am curious about is… do you feel, like I do, that the genealogy industry (e.g., Ancestry.com, familysearch.org, etc.) would benefit from having more reliable, accurate, and predictable data management practices? If this thought piques your interest, please read on.
Data Management Maturity Model
The Carnegie Mellon Software Engineering Institute (SEI) and the Enterprise Data Management Council (EDM Council) have formed a strategic partnership to create a new Data Management Maturity (DMM) Model for the information technology and financial industries. The new model will define the components of data management at the specific business-process level so that organizations can assess themselves against documented best practices and upgrade their management of essential data resources.
The overall goal of this new collaboration is to help the information technology and financial industries become more proficient in their management of critical data and to provide a consistent and comparable benchmark for regulatory authorities in their efforts to control operational risk. The DMM will be constructed based on the foundational process areas found in Capability Maturity Model Integration (CMMI) developed by SEI and funded by the Department of Defense and in the CERT Resiliency Management Model (RMM) developed in collaboration with the Financial Services Technology Consortium. It will result in a framework and accompanying assessment methodology for evaluating the efficiency of data management practices, measuring the maturity of operational integration, and establishing standard best practices that can be adopted by information organizations worldwide.
The goal of managing data as a corporate asset where precision, consistency, comparability and standardized meaning are assured is just now emerging as a business priority among organizations. And while the objectives of data management are conceptually understood, the practice of data management is difficult to implement because of the difficulties in unraveling and reconnecting systems, processes and operational environments that are required to gain control over data as it proliferates throughout large organizations.
At the core of the challenge is the lack of practical expertise and fact that there is no proven operational route map to guide organizations in their goal of enterprise-wide data management. The Data Management Maturity Model objective has been crafted in conjunction with information technology and financial industries practitioners to help respond to the twin forces of need and complexity that characterize the data management challenge. The objective of the DMM is to help organizations turn the ‘art and practice’ into the ‘science and discipline’ of data management.
Any thoughts, comments, questions you might have are most welcome. As this effort gets underway, what would you like to see brought to bear in this realm? If you have ideas, concerns, or would like to participate in any way, please either leave a comment here or contact me directly from our Contact page.
In the end, we will all benefit from improving the reliability of our information sources, databases, and systems.
Nov 06, 2011 @ 18:21:32
In an ideal world this would be wonderful. In a real world this would be devestating to the genealogical community.
I have spent 24 years in the “information technology” (IT) world. The pursuit of “best practice” has driven the business world for many years: best practice results in efficiency, etc. which results in less cost resulting in more profit. Then governments got involved in setting standards and raising issues of reporting for the financial industry; because of dire need and because a multi-billion dollar industry was expected to afford it.
No other industry is subject to this primarily because of prohibitive costs. Even though Ancestry.com and their competitors make millions in revenue, I would hazard a guess that those efforts are balanced by the efforts of FamilySearch.org (funded by the Church of Jesus CHrist of Latter Day Saints) and the myriad of volunteer driven organizations. How would you expect low-income and no-income providers to comply with little or no compliance budget? They wouldn’t and the genealogical society would suffer the consequence.
Even if you could impose standards on for-profit ventures only, how would you enforce standards? Ancestry.com includes the 1871 Census of Canada Index created by the Ontario Genealogical Society (OGS): Ancestry.com profits (through subscriptions) but would pass compliance responsibility to OGS because they created the data. In this case study the profiteers keep the money and the volunteer-driven creator gets swamped in the regulatory quagmire.
What about the Canada GenWeb or USGenWeb Project(s); solely volunteer driven organizations whose aim is to provide free genealogy data. Would you have them tell every amateur transcript submitter when/where/why/how they will provide the data they do? Many “chapters” rely on free web hosting and otherwise have no financial benefits: others that due solicit funds to cover costs will lose everything to meet compliance. I would expect these projects to fold in less than a week.
What I see as a result is Ancestry.com and maybe one or two competitors remaining, with enough loopholes to avoid compliance while every genealogist is held hostage to pay whatever fees these companies demand.
Nov 06, 2011 @ 21:20:52
I guess I respectfully disagree. Firstly there is no standard implied by the DMM effort; this model is an effort by the Information Industry in promoting self-regulation, heightened professionalism and shared learning.
As always with SEI models, the industries themselves choose how or when these models are to be applied. Certainly there is no body within the genealogy industry today that will force any genealogy firm to do anything with the data and learnings that the DMM or any other SEI model(s) might provide.
As for the loopholes you mention, I no of no loophole larger than that presented by an industry where there exist few if any standards for professionalism, integrity, standards of performance or data security. As for your point about costs, like all quality and business models the DMM could be misapplied and misused but without a genealogical standards enforcement body to mandate a standards approach or application of this or any other model, that risk seems minuscule. Besides which the cost problem exists in all the examples you highlighted above, today, so I doubt that anything we would learn from participating in DMM development would make our current circumstances any worse than they are right now.
As the genealogy industry struggles to grow and present a more professional image, participation in efforts like the DMM provide a unique opportunity to contribute, learn and grow. I believe we need to continue to preserve the integrity of the genealogy hobby while encouraging professionalism from those who provide services, information, data, and tools to those who want to use them. In any event, anything we would do should support our needs and aspirations either as individuals or as a collective.
Nothing is being mandated of us.