[OpenGLAM] Effective records mgmt as a foundation of trusted open data / big data
jhagmann at gmail.com
Fri Feb 13 09:16:22 UTC 2015
pls refer to this article from the Records mgmt Journal (2014):
, Valerie Léveillé
(2014) "Whither the retention schedule in the era of big data and open
data?", Records Management Journal, Vol. 24 Iss: 2, pp.99 - 121
- The argument is made that the business processes supporting open data and
big data initiatives could serve as the basis for developing enhanced
standards and procedures that are relevant to the characteristics of these
two kinds of initiatives. The point is also made, however, that addressing
the retention and disposition issues requires knowledge and leadership,
both of which are in short supply in many organizations. The
characteristics, the issues and the approaches will be tested through case
studies and consultations with those involved with managing and
administering big data and open data initiatives.
- There is very little, if any, current literature that addresses the
impact of big data and open data on the development and application of
retention schedules. The outcome of the research will benefit those who are
seeking to establish processes leading to formally approved retention and
disposition specifications, as well as an instrument - the approved
retention and disposal schedule - designed to ensure the ongoing integrity
of the records and data associated with big data and open data initiatives.
Open data and trust/integrity
The reliability, accuracy and trustworthiness of the datasets used in
support of open
data initiatives depend on the ability to trace them back to the original
sources from which they have derived. The ability to demonstrate the
the original record sources - that is, being able to show that the record
complete, authentic and managed within a secure and controlled environment
- in turn
helps promote confidence that the data sets generated from these sources
can be trusted.
Conversely, the absence of controls that would otherwise support and ensure
trustworthiness of the original source records will erode trust in the
derived data sets
and, as a consequence, undermine the quality and effectiveness of the
initiatives that are
using the datasets.
Open data initiatives support business processes. They
may begin with the steps involved in deciding which sets of data should be
available and how they should be packaged for dissemination and access.
steps focus on:
* the packaging process itself and the steps involved in developing search
* formatting the data;
* configuring it for dissemination via a web-based portal and the internet
* migrating it to the portal;
* ensuring the integrity of the data throughout the process and at the
final stage of
* monitoring user access and feedback thereafter.
If the statistics are to be mashed-up with other statistics or other forms
of data, then a
similar series of systematic production steps will be followed. Closely
related to these
processes and steps are those associated with the creation and collection
of the statistics
in the first place; public opinion surveys, surveys undertaken to support
policy development and other similar forms of data collection activities
that are selected
to support open data initiatives each proceed through a systematic workflow
comprises a business process.
As will be explained later in the paper, analysis of the business processes
big data and open data initiatives should form the basis for addressing the
retention and disposition.
RIM Consulting <http://homepage.bluewin.ch/cyberhagi/5001.html> / KRM
Baden - Switzerland
President ARMA Swiss Chapter
*Der neue Leitfaden Information Governance ist ab sofort vorbestellbar
Governance Leitfaden 2015 / Subskription
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