Information Audit and XInformatics course summary Peter Fox

Information Audit and XInformatics course summary Peter Fox Xinformatics Week 10, April 10, 2011 1

Contents • Information audit • Summary of this course • What you needed to learn/ objectives 2

Businessdictionary. com • Analysis and evaluation of a firm's information system (whether manual or computerized) to detect and rectify blockages, duplication, and leakage of information. • The objectives of this audit are to improve accuracy, relevance, security, and timeliness of the recorded information. 3

What is an information audit? • An information audit is a process that effectively determines the current information environment within an organization by identifying and mapping: – What information is currently available? – Where the information lives? – How the information is (or is not) delivered or accessed? – How the information is maintained, revised or deleted? 4

Results/ format (e. g. ) • The results of an information audit are twofold: there is a detailed report which includes: – What information do staff acquire? Where from? At what cost? How is it used? – What information do staff create? What happens to it? Where does it go? – What information is stored and why? What purpose will it serve? – What information is passed on or delivered? To whom? For what purpose? In what form? 5

Results/ format (e. g. ) – Is there a gap, or a match, between that which is available and that which is needed? – What are the skills and responsibilities of the people who carry out these tasks? – What equipment and tools do they have available (hardware, software, filing cabinets, web sites, etc)? – Are there any control documents, such as policy statements, guidelines, service level agreements, procedures, manuals? – Is any of the information (produced, acquired, processed, re-delivered, or stored) superfluous to needs? – Are any of the information-handling activities nonproductive? 6

Results/ format (e. g. ) • There is also a detailed flow chart: – A visual map that show the areas, processes, functions and activities through which information passes, clarifying gaps or fault-lines that need to be plugged or bottlenecks and overflows that need to be unblocked • Sound familiar? 7

How to use? • An information audit can be used as a baseline for making major improvements to the business process of an organization. • It is extremely helpful in the identifying, buying, and implementation of enterprise systems, such as finance systems, portfolio management systems, document management systems, learning and knowledge management systems, etc. 8

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The key is: • As the volume, complexity and heterogeneity increases… – Suddenly information looks more like a continuum – All known methods, algorithms do not scale (except for very simple operations) – And because it is information, humans are part of the loop • Thus - understand apply theoretical foundations • All to date are developed in an analog world, not a digital one!! 10

Abduction • method of logical inference (Peirce) • prior to induction and deduction i. e. "hunch” • starts with a set of (seemingly unrelated) facts + intuition (some connection) and brought together – via abductive reasoning • abduction is the process of inference that produces a hypothesis as its end result 11

A Use Case • … is a collection of possible sequences of interactions between the information system under discussion/ design and its actors, relating to a particular goal • … consists of a prose description of an information system's behavior when interacting with the actors • … is a technique for capturing functional requirements of an information system • … captures non-functional requirements

Ultimately: Wetware • ‘Before you make the software interoperable, you need to make the people interoperable’: Ian Jackson, 13

E. g. Table of Contents • • • • • • ==Plain Language Description== ===Short Definition=== ===Purpose=== ===Describe a scenario of expected use=== ===Definition of Success=== ==Formal Use Case Description== === Use Case Identification=== ===Revision Information=== ===Definition=== ===Successful Outcomes=== ===Failure Outcomes=== ==General Diagrams== ===Schematic of Use case=== ==Use Case Elaboration== ===Actors=== ====Primary Actors====Other Actors==== ===Preconditions=== ===Postconditions=== ===Normal Flow (Process Model)=== ===Alternative Flows=== • • • • • • • ===Special Functional Requirements=== ===Extension Points=== ==Diagrams== ===Use Case Diagram=== ===State Diagram=== ===Activity Diagram=== ===Other Diagrams=== ==Non-Functional Requirements== ===Performance=== ===Reliability=== ===Scalability=== ===Usability=== ===Security=== ===Other Non-functional Requirements=== ==Selected Technology== ===Overall Technical Approach=== ===Architecture=== ===Technology A=== ====Description====Benefits====Limitations==== ===Technology B=== ====Description====Benefits====Limitations==== ==References== Developed for NASA TIWG

Information theory • Semiotics - study of sign processes or signification and communication, signs and symbols, into three branches: – Syntax: Relation of signs to each other in formal structures – Semantics: Relation between signs and the things to which they refer - meaning – Pragmatics: Relation of signs to their impacts on those who use them 15

THE PHYSICS OF INFORMATION © 2005 Ev. REsearch LTD Ev. REsearch©

Physics of information = uncertainty/ integrity • Information of a random variable is defined as the Sum of p x log p, where p=probability. It represents the uncertainty of the variable • Mutual information of two variables = how much information one variable contains about the other – i. e. the decrease of the uncertainty of one variable by knowing the other • In probabilistic terms, the entropy decreases by conditioning on the distribution 17

Noise • Uncertainty, especially any that is introduced is a source of noise, or more accurately – bias in the use or interpretation of the information – is context and structure dependent – Noise/ bias contamination is rampant in information systems • Quality assessment, control and verification is less developed for information sources 18

Mode of noise introduction From Shannon and Weaver (1949) Msg? Information Source Signal? Web Content, Structure Recvd? Msg? Web browser? Noise source HTML page, user 19

Intersecting disciplines: Library Science Organizes. Cataloging and classification Preservation ‘maintaining or restoring access to artifacts’ Cognitive Science mental representation, the nature of expertise, and intuition Social Science Collaborati on Cultural norms Rewards 20

Presentation • Separation of content from presentation!! • The theory here is empirical or semi-empirical • Is developed based on an understanding of minimizing information uncertainty beginning with content, context and structural considerations and cognitive and social factors to reduce uncertainty • Physiology for humans, color, … 21

Organization • Organizations - producers v/s consumers • Organization of information presentation, e. g. layout on a web page • Yes - content, context and structure • How to organize – What have you seen? – Needed? – Not had resolved? 22

Mental Representation • Thinking = representational structures + procedures that operate on those structures • Did you make progress? • Methodological consequence: what have you learned about the study how we think about information systems? 23

Behind this: Information Models • Conceptual models, domain models, explore domain concepts • High-level conceptual models are created as part of initial requirements envisioning efforts - to explore the high-level static business or science or medicine structures and concepts. • Conceptual models are created as the precursor to logical models or as alternatives to them • MUST be followed by logical and physical models 24

(Information) Architectures • Definition: – “is the art of expressing a model or concept of information used in activities that require explicit details of complex systems” (wikipedia) – “… as in the creating of systemic, structural, and orderly principles to make something work - the thoughtful making of either artifact, or idea, or policy that informs because it is clear. ” Wuman 25

Architectures • Building on content, context, and structure, think of information architectures as “in front of the interface” and “behind the interface” • What’s the proportion – is it just like an iceberg? I. e. the majority of information architecture work is out of sight, "below the water. ” 26

Reference architectures • “provides a proven template solution for an architecture for a particular domain. It also provides a common vocabulary with which to discuss implementations, often with the aim to stress commonality. • A reference architecture often consists of a list of functions and some indication of their interfaces (or APIs) and interactions with each other and with functions located outside of the scope of the reference architecture. ” (wikipedia) • Have you seen a reference architecture? 27

Design? • “In the context of information systems design, information architecture refers to the analysis and design of the data stored by information systems, concentrating on entities, their attributes, and their interrelationships. • It refers to the modeling of data for an individual database and to the corporate data models an enterprise uses to coordinate the definition of data in several distinct databases. 28

Design theory • Elements – Form – Value – Texture – Lines – Shapes – Direction – Size – Color • Relation to signs and relations between them 29

Principles of design • • Balance Gradation Repetition Contrast Harmony Dominance Unity 30

Broad life-cycle elements • Acquisition: Process of recording or generating a concrete artefact from the concept (the act of transduction) • Curation: The activity of managing the use of data from its point of creation to ensure it is available for discovery and re-use in the future • Preservation: Process of retaining usability of data in some source form for intended and unintended use • Stewardship: Process of maintaining integrity across acquisition, curation and preservation 31

Acquisition • What do you know about the developer of the means of acquisition – Documents -not be easy to find/ read/ understand – Remember bias!!! • Have a checklist (the Management list) and review it often 32

Curation • • • From Producers to Consumers! Organization and presentation! Documentation! Provenance! So sorry for all the !!!!!!!! • Technology-neutrality? • Add metainformation 33

Preservation • Archiving is but one component • Intent is that ‘you can open it any time in the future’ and that ‘it will be there’ • Steps not be conventionally thought of • Think far into the future …. history gives some guide to future considerations 34

Information Management • • • Creation of logical collections Physical handling Interoperability support Security support Ownership Metadata collection, management and access. Persistence Knowledge and information discovery Dissemination and publication 35

Information Workflow • Series of tasks performed to produce a final outcome • Information workflow = “analysis pipeline” – Automate tedious jobs that users traditionally performed by hand for each dataset – Process large volumes of data/ information faster than one could do by hand 36

Information integration • Involves: combining information residing in different sources and providing users with a unified view of them • Recall the domain examples: – Geo? – Medical/ health? – Others? 37

Discovery? • Discussion – What is the reality? – Information architecture considerations? – Facilitation of Xinformatics? 38

Visualization? • Reducing the amount of data, quantization – Patterns – Features – Events – Trends – Irregularities – Exit points for analysis • Also presentation of data • Cognitive science and the mental representation 39

Factors that count! • Quality – Is in the eyes of the beholder – why this is so important? • Uncertainty – has aspects of accuracy (how the real world situation is assessed, it also includes bias) and precision (down to how many digits) • Bias – Systematic error resulting in the distortion of measurement data caused by prejudice or faulty measurement technique – A vested interest, or strongly held paradigm or condition that may skew the results of sampling, measuring, or reporting the findings of a quality assessment: • Psychological: for example, when data providers audit their own data, they usually have a bias to overstate its quality. • Sampling: Sampling procedures that result in a sample that is not truly representative of the population sampled. (Larry English) 40

In one slide? • Use case – you have to know the goal (+more) • Conceptual and logical models -> information models • Understand information flows and uncertainties (sign systems), the life cycle and manage them • Apply information, library, cognitive, social science, and design elements to developing a design of an architecture • Think the design through (e. g. get closer to the physical model (workflow? )) and assess the presentation, organization, content, context, structure, syntax, semantic and pragmatics 41

What would your slide include? 42

Objectives • To instruct future information architects how to sustainably generate information models, designs and architectures • To instruct future technologists how to understand support essential data and information needs of a wide variety of producers and consumers • For both to know tools, and requirements to properly handle data and information • Will learn and be evaluated on the underpinnings of informatics, including theoretical methods, technologies and best practices. 43

Learning Objectives • Through class lectures, practical sessions, written and oral presentation assignments and projects, students should: – Understand develop skill in Development and Management of multi-skilled teams in the application of Informatics – Understand know how to develop Conceptual and Information Models and Explain them to nonexperts – Knowledge and application of Informatics Standards 44 – Skill in Informatics Tool Use and Evaluation

Discussion • All of the material? 45

Reading for this week • http: //en. wikipedia. org/wiki/Information_audit • http: //www. librijournal. org/pdf/2003 -1 pp 2338. pdf 46

What is next • April 17 – No class GM week • April 24 – guest lectures, 9 am: astro-, 10 am: geo-, 11 am: chem • May 1 – final project presentations (BE ON TIME, i. e. 5 -10 mins BEFORE 9 AM) • And, be prepared to be asked (and answer) questions 47