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Presentation on theme: "IM: Making the UK Smarter PROFESSOR TOM JACKSON DIRECTOR OF THE CENTRE FOR INFORMATION MANAGEMENT."— Presentation transcript:


2 Overview Growth of information and the digital age challenge The creation of CIM and why the end of the Library? Creating the IM workforce

3 Growth of Information and Challenges ahead

4 Speed of Change ~2012

5 43 Years Old

6 Speed of Change – late 2013

7 Speed of Change – July 2014

8 Social Media Command Centre

9 The Information Footprint

10 Rapid Change - Digital Footprint 20/11/2014 – IDC - What does your digital footprint look like? Examples, web, email, Facebook, surveillance cameras, twitter, on- line banking, digital photographs, etc. 1918’s paper footprint – max of 2mb a year and now the digital one….

11 The Complex Digital Age? Complexities of managing ‘soft’ and ‘hard’ data, information and knowledge Employee Knowledge Unstructured data Internet – finding the information Processes and Systems

12 How many bytes of information does my brain hold? Tricky trying to put a value on it! What would you guess?

13 Based on number of junctions between neurons Brain contains 100 billion neurons Each has ~ 20,000 shared synaptic junctions Assumption each holds equivalent of a binary ‘bit’ Storage capacity between 100 and 1000 terabytes How many Bytes of Information does my Brain hold?

14 Your brain is the size of forest! 1 TB = 50,000 trees made into paper and printed So our brains are the equivalent of 50,000,000 trees! 400 Billion trees in the Amazon Rain Forest (1 b = thousand million)

15 Information Landscape The employee Explicit Knowledge Public Information InternetIntranet Own and Company Records Folder Hierarchies Group File storesTacit KnowledgeColleaguesYou needThat need you...between 100 and 1000 terabytes per employee Internet 500bn gigabytes 54TB of unstructured data Systems and Processes

16 The Complex Digital Age? Barrier Overcome: Data storage capacity Challenges: Providing meaning to terse seemingly unconnected data Realising the value of the data and information Structuring systems and processes Visualising and manipulating data and information streams Intelligent systems

17 Creation of CIM – why the end of the Library?

18 From Information Science to the CIM What is Information Science? What do we do? Do students know what information science is? Do students know what information management is? What should the brand be? How do we market IM?


20 The CIM Team Expertise located within School of Business and Economics Expertise located across campus The CIM Vision – Transforming the Digital World by conducting research that matters. - Evidence the significance and value of information - Challenge thinking and practice around information management - Improve performance through analysis, interpretation and judgement of information - Research areas: Organisation, People, and System

21 Mapping the Mood of the Nation – EMOTIVE Extracting the Meaning Of Terse Information in a Geo-Visualisation of Emotion Analyses tweets and categorises them into cross cultural emotions Best f-measure for fine-grained emotions in the world Used to monitor and potentially change real-time events through intervention Ann O’Brien, Martin Sykora, Tom Jackson

22 MAIPLE - Managing Access to the Internet in Public Libraries Two-year project funded by the AHRC To identify and quantify measures being taken in public libraries to regulate and manage access to the Internet Not all wifi access is filtered Over-blocking of content is the most frequent cause of complaint with regard to filters (88.5%) Digital divide – some important information is being blocked (e.g. sexual health information) Louise Cooke, Claire Creaser, Adrienne Muir, Rachel Spacey

23 Email Knowledge Extraction Discover who knows what Cut time searching Reduce duplication of information Identify potential training needs by analysing gaps in knowledge profiles Profile employees to help with recruitment when staff leave Provides social network analysis Who are the key information brokers Potential a reward scheme for sharing knowledge

24 Sus-IT – New Dynamics of Ageing Sus-IT - to promote autonomy and independence Substantial research over many years 10 million people in the UK over 65 years old 10.5 million over 65 in 2030 19 million by 2050. Finding – changing technology will cause long term issues with people over 65 Leela Damodaran, Wendy Olphert

25 Systems Thinking – PEArL The PEArL Framework (Participants; Engagement; Authority; relationships; Learning) Example use: Supported implementation of new Automotive Functional Safety Standard ISO 26262 Dr Champion invited onto Steering Group overseeing Systems Engineering processes Applied to support Key Workers and Residents in Homeless Shelters; the British Association of Chemical Specialists; Belron ( Autoglass) to assist with a new European wide integration initiative. Donna Champion

26 Police Mobile Data Terminals Mobile technology devices could save the average police force £800,000 a year. Full set-up costs are just £440,000 Leicestershire Constabulary now has 730 police officers and 293 sergeants using the MDTs A 15.2 per cent increase in officer visibility; reduced vehicle mileage and service costs and an increase of 600 per cent in agreed appointments The time it takes to make a crime report available to another officer has reduced from three days to just 11 minutes Louise Cooke, Rachael Lindsay, Tom Jackson

27 Benefits Realisation Management Key Idea: Benefits are primarily derived from doing things differently [organisational change], and IT is simply the enabler of new ways of working. Benefits should be actively reviewed and realised throughout the working life of a new technology, not just at the point of implementation. Prof Doherty and Dr Coombs are actively investigating a variety of tools and approaches to help organisations leverage real value from their IT investments, in a variety of business contexts. ‘Benefits realisation – it’s a journey, not a destination’

28 Embedded Intelligence Increasing sources of data - insurance premiums - recalling faulty cars - determining emotional state of driver whilst driving? - imagine personalised advertising boards – driven by emotion

29 So how do we Market ourselves? Semantic web based on library science Taxonomy and Ontologies Broad range of skills not just IM Data Analytics Information Management Records Management Knowledge Management - Employee Knowledge – 100 to 1000 terabytes (1920’s) We are managing the ‘Information Age’!

30 Creating the IM Workforce

31 Skillset Managing and enabling data, information and knowledge quality (consistent format, avoiding errors, setting up systems to enable good data input and automated checking; information quality: relevance, authority, scope etc.; ‘good’ knowledge: who’s voice); Managing and enabling the organisation of data e.g. databanks such as with census data, client records etc.; information e.g. through metadata such as taxonomies and ontologies and knowledge e.g. mapping knowledge in an organisation; Mark Hepworth

32 Skillset Managing and enabling effective storage of data, information and knowledge through various technologies e.g. databases, information e.g. libraries, electronic information systems and apprenticeship, audio diaries etc.. Managing and enabling access to data, information and knowledge and the issues surrounding sharing and security; enabling exploitation of data (data mining, ‘big data’ analytics), information and knowledge extraction via information retrieval and processing algorithms and interaction, dashboards, visualisation, representation and the facilitation of informed decision making. Mark Hepworth

33 University Courses Loughborough University have changed the BSc and MSc The content is there Improved presentation and selling of the programmes Strong global Chartered Institute required Must be focused on the Information Age Even stronger as an alliance CI needs strong presence in organisations Failure to change Global need will see new global institutes to take the challenge forward

34 Summary Urgently rebranding required Let’s take control of the domain Lead the way Example – iSchools in academia Without a strong unified institute Ownership of our domain will be conquered by others Leading to a weaker dispersed domain and presence


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