In late 2013, I became the director of a new group in IST called Enterprise Architecture (EA). I have written previous blog posts about Enterprise Architecture (the practice), but the EA Group does more than just Enterprise Architecture. One of our other key responsibilities is Information Management.
The University has a Statement on Information Management available on the Secretariat & Office of the General Counsel’s website. While this statement is from 2009 and up for review by the Administrative Information Governance Committee (AIGC), any discussion about Information Management at Waterloo should start with this document.
Quoting the current statement:
Information is a vital asset, both in terms of supporting academic excellence and the efficient management of services and resources. It plays a key part in governance, administration, service planning and delivery, and performance management. Effective management of information:
- increases transparency and accountability while protecting the privacy of individuals
- facilitates informed decision making
- enhances the efficiency of program and service delivery; and
- minimizes risk to the university by protecting its information assets and ensuring compliance with appropriate legislation, regulations, and standards.
It is therefore of paramount importance to ensure that information is efficiently managed, and that appropriate policies, procedures, and accountabilities, provide a robust framework for information management.
As University employees, we uphold the Principles and Practices of this statement by taking an active role in ensuring that we "manage information well, use it effectively, share it appropriately, and safeguard it carefully, in accordance with the university’s information-related policies and procedures."
What does this framework actually look like?
Combining the disciplines of “Enterprise Architecture” and “Enterprise Information Management,” I want to provide a summary of the specific models and frameworks we are working with to understand what “Information Management” entails.
Models and frameworks
The DIKW (Data, Information, Knowledge, Wisdom) Hierarchy / Pyramid Model1
This model has been represented in a variety of ways, but for my practical purposes I define the segments as follows:
Data – Facts without context.
- Information – Data “in formation”, data in context.
- Knowledge – Information in context. The ability to answer questions based on information; to know how something happens.
- Wisdom – Being able to act (based on knowledge) to amplify positive/dampen negative outcomes.
To understand the difference between each level, consider the following example:
- Data - 24
- Information - Temperature in office: 24°C
- Knowledge - The air conditioner should prevent the temperature from rising over 21°C
- Wisdom - The air conditioner requires maintenance
Despite the terminology used on campus, we rarely encounter ‘data’ in our day-to-day lives at the University. We instead work with a various pieces of ‘information’ in two forms generally named data and content:
- Structured information (data) - Information in the form of key-value groupings, usually stored in spreadsheets or databases. As soon as the label "Name" is connected to the data “Colin” you have information, not data.
- Unstructured information (content) - Information such as free-form text or images that are contained in documents. This blog post is an example of content.
DAMA-DMBOK: DAMA International Data Management Body of Knowledge2
The DAMA-DMBOK outlines 10 Data Management Functions3:
- Data Governance – planning, supervision and control over data management and use
- Data Architecture Management – connection of data to the larger Enterprise Architecture strategy
- Data Development – analysis, design, building, testing, deployment and maintenance
- Database Operations Management – support for structured physical data assets
- Data Security Management – ensuring privacy, confidentiality and appropriate access
- Reference & Master Data Management – managing golden versions and replicas
- Data Warehousing & Business Intelligence Management – enabling access to decision support data for reporting and analysis
- Document & Content Management – storing, protecting, indexing and enabling access to data found in unstructured sources (electronic files and physical records)
- Meta Data Management – integrating, controlling and delivering meta data
- Data Quality Management – defining, monitoring and improving data quality
We have begun work with groups across campus to tackle each of these functions, and will be expanding our efforts in the coming months through the implementation of Special Interest Groups (SIGs) discussed further below.
Electronic Discovery Reference Model / Information Governance Reference Model (EDRM IGRM)4
The IGRM is a high-level model that captures the Information Management concerns of a number of key stakeholders in a single diagram:
- Business - how can the information be used to improve services?
- Privacy & Security - how can the information be protected against unauthorized access?
- IT - how can the information be stored and retrieved so that duplication of work and technology is minimized?
- Records & Information Management (RIM) - what should the schedules for information retention be?
- Legal - are we following all laws and regulations around information collection and use?
These models are a few of the tools the Enterprise Architecture Group (EAG) intends to use to understand the current Enterprise Information Management (EIM) capability on campus. By looking at projects, processes, services, and systems through the lens of these models, we hope to help our clients understand their Information and how they can get value from it.
Today we work at an operational level — project-by-project, service-by-service. As we publish our vision and roadmap over the summer and into the fall, the EAG will begin seeking input from interested parties. Look for the EA Special Interest Groups (SIGs) where we hope to discuss EA topics like this or contact email@example.com to be notified when they are up and running.
- Ackoff, R. L., "From Data to Wisdom", Journal of Applied Systems Analysis, Volume 16, 1989 p 3-9.