Information Publication for Systems Engineers (making engineering outputs more accessible) Follow the presentation on your own screen by visiting: extuitive.co.uk/ip This will allow you to follow links and participate in interactive polls Setting the scene What are we not talking about? Giving presentations The fine details of the ‘academic’ publication process How to do techincal writing Being an artist Data analysis So what are we talking about?

10:00 — 10:25 Scene setting and general concepts 10:25 — 10:40 Data/Information management 10:40 — 10:45 Mini-exercise 10:45 — 11:05 Document presentation 11:05 — 11:10 Break 11:10 — 11:25 Exercise 11:25 — 12:00 Graphic presentation 12:00 — 13:00 Lunch 13:00 — 13:20 Group exercise 13:20 — 13:40 Publication 13:40 — 14:00 Advanced techniques Why do we care… …as engineers? …as Systems Engineers? Pedantry, or professionalism? Who am I? Dr John Welford MEng PhD CEng IET MINCOSE WSP New Zealand, Technical Principal Systems Engineer

(Not a data visualisation expert or a typographer) Who are you? Name Job/role Interest/experience in the area General concepts Data and information The DIKW model:

Wisdom Assimilated knowledge, application of knowledge Understanding and application

Knowledge Third-party comprehension Information publication

Information Statistics, tables, interpretations, graphs Data analysis Data Machine code, binary, ASCII, spreadsheets, equations Think about your audience What do they already know? What will be familiar to them? What do they need to know? What is the inferential distance between them and you? What special needs might they have? Presentation of abstraction As engineers we are oen working with an abstraction of the real system. When we publish information we are always presenting an abstraction of the real system.

It seems that perfection is attained not when there is nothing more to add, but when there is nothing more to remove.

— Antoine de Saint Exupéry

It is therefore up to us to choose what to emphasize, for example… (credit xkcd.com) Separating content from presentation Familiar to web-authors: HTML = content (+ structure), CSS = presentation. In DIKW terms: information = content (+ structure), publication = presentation. Ideally — first develop the content, then later develop the presentation. Practically — development is oen in parallel; however, content should always be prioritised. Some tools provide a clear separation between content and presentation, others are more WYSIWYG. In either case, it pays to at least conceptually make the separation. Dangers of conflating content with presentation 1. Distraction from the process of working with information 2. Reduced portability and compactness 3. Lack of proper information structure

(This presentation content is written in Markdown, the formatting is in CSS) Additional considerations

Be conscious & intentional Every aspect of presentation represents a decision. Every decision should be justifiable. Be consistent The same decision should have the same outcome each time it’s made. There should be uniformity in the resulting publication. Beauty vs. practicality Ideally both! But (for engineering): practicality >> beauty. Science, art, opinion Be aware that most advice on the topic of information publication falls into one of three categories (including this tutorial): 1. Science (researched and peer-reviewed) 2. Art (general expert concensus) 3. Opinion (my own) References References cited or linked throughout, but top reference texts are: The Elements of Typographic Style — Robert Bringhurst Visualization Analysis & Design — Tamara Munzer Show Me the Numbers: Designing Tables and Graphs to Enlighten — Stephen Few Other authors to read or follow: Edward Tue, Naomi Robbins, Mike Bostock, Bret Victor Data/information management Examples of data from your own job Fill in the questionnaire on your screen with an example of one source of data that you might utilise in your job. Keep it brief, but submit multiple answers if you like. The results will appear to everyone on the next slide in… Your example data Data structure Likely to be out of your control: Results of a questionnaire Export from a simulation, model, or design tool Logs from monitoring equipment Scraping websites Verbal or written input from experts Previous work and general literature Experience and engineering judgement The process of producing information from the data will involve some degree of analysis, but it is also where sensible choices can be made about the information structure. Variations in data structure Data can have many different structures. Part of data analysis is cleaning and tidying the data. Consider…

Treatment A Treatment B John Smith — 2 Jane Doe 16 11 Mary Johnson 3 1 Transposed as…

John Smith Jane Doe Mary Johnson Treatment A — 16 3 Treatment B 2 11 1 Or tidied as…

Name Treatment Result John Smith A — Jane Doe A 16 Mary Johnson A 13 John Smith B 2 Jane Doe B 11 Mary Johnson B 1

Dont be afraid to change your data structure to support analysis and information presentation. Information structure – focus on content The output of analysis should yield information. At this stage it can be very tempting to start presenting the information, indeed you may wish to start considering the final published form prior to the information being complete. However, it requires discipline to keep the concept of structuring the content separate from presenting it. For example, setting up the structure of your report, is separate from deciding which levels of heading are going to be in bold. Configuration control Both data and information should be under some form of configuration management, ideally supporting: Versioning Change control Baselines Access control Backup/recovery Also consider maintaining an auditable trail of how the information was generated from the data. Data/Information tools Spreadsheets: Excel, Calc, Numbers, Google Sheets Databases: Access, DOORS, SQL, MBSE tools Formats: CSV, JSON, XML Languages: Matlab, Python, R, LaTeX, Markdown Mini-exercise You have 3 minutes to skim and rate a paper based on: ‘How well you understood the paper’ ‘How useful you think it is’ Results Document presentation Assume the information we wish to publish is best presented in the form of a document. The definition of ‘best’ here will depend on your audience and what the information is – as discussed previously.

We’ll also assume that the information is already developed in terms of both content and structure. The format that this is captured in might vary depending on the tool that we choose to use. For reference let’s have a look at some examples of content and structure… Content and structure – LibreOffice Writer

NB: Structure is less explicit here, as it is a WYSIWYG tool. Content and structure – Markdown

Example document ======

Demonstrating the information *content* for a document, and a bunch of different aspects of document *structure* (the funny-looking parts).

## Lists

Could be: * Enumerated * Unordered * Sub-lists

## Links

Content and structure – HTML

Example document

Demonstrating the information content for a document, and a bunch of different aspects of document structure (the funny-looking parts).

Lists

Could be:

• Enumerated
• Unordered
  • Sub-lists

Content and structure – LaTeX

\section{Example document}\label{example-document}

Demonstrating the information \emph{content} for a document, and a bunch of different aspects of document \emph{structure} (the funny-looking parts).

\subsection{Lists}\label{lists} Could be: \begin{itemize} \item Enumerated \item Unordered \begin{itemize} \item Sub-lists \end{itemize} \end{itemize}

Presenting the document In all the preceeding examples the content was the same, although the syntax used to provide the structure was different. However, presentation of that content depends on the styling that is added based on the structure. Styling will also have it’s own syntax that is tool/language specific. The capability of different tools to provide styling also varies significantly. Next we will run through a bunch of different document presentation areas where we should make concious decisions about styling, this is better known as typography. Typeface A general ‘font family’, typefaces include many different fonts with variations in size and emphasis (bold, italic, etc). Typefaces (and fonts) may be classified as either sans-serif, or serif.

Serifed fonts are considered easier to read in print than sans-serif. However, the science on this appears to be inconclusive. Conversely sans-serif are sometimes preferred for on screen reading, as they scale better at low resolutions. Interesting typefaces Some typefaces have been designed to assist dyslexic readers, however their efficacy is disputed.

Sans Forgetica is designed to be intentionally difficult to read, as this prompts your brain to engage in deeper processing. Headings Typically a document may have many levels of heading. Too many levels and you will lose the reader! ALL CAPS, ‘Title Case’, and ‘Sentence case’ can be used at different levels of heading, along with changes in size, colour and font. Normal text – size and spacing Size: choose for legibility and to match the page (see later). Letter spacing: best to stick with the default! Setting: Either flush-le ragged-right, or justified. Justified text is achieved by the tool modifying the inter-word spacing, so choose justifed text only when the line is long enough — hyphenation may still be necessary to avoid sloppy spacing (if your tool supports this). Advanced tools may support microtypography, which subtly adjusts other aspects of the text to improve readability and appearance. Justified text is considered to be a problem for dyslexics, due to the uneven spacing and distracting ‘rivers’ of white space. Kerning:

(credit xkcd.com) Spaces between sentences If you answered ‘one space’ then you’re doing it right! Double spacing is an artefact of victorian typewriter usage and is no longer relevant. Paragraphs Provide a pause in reading, and may be shown by either an initial indent or a slight space between blocks of text. Indents are more common in printed literature, whilst spacing is more prevalent on the web (where there are less space constraints). If you’re working in a WYSIWYG tool then you shouldn’t be inserting an extra carriage return between paragraphs. This is mixing up content with presentation. Weighting and emphasis Change one parameter at a time.

A roadmap of fonts in a family of type, originally from Bringhurst, reproduced by Boulton. Page layout – lines Line length: 66 characters is considered ideal, but anything 45 to 75 characters is ok (including punctuation and spaces). Longer might be ok for discontinuous texts (e.g. bibliographies). Line spacing: ‘leading’ is usually slightly more than character height, giving a small gap between lines. Sometimes much larger spacing (1.5 or double-space) may be requested to allow for handwritten review comments. Page layout – textblock Margins: textblock width should be defined to achieve the right line length based on the typeface size and page size. Textblock height depends only on what size margins you leave — don’t be stingy on the margins or your page will look ugly! Also worth considering are binding and on-screen reading. Headers and footers: may carry information about the section and the page, or about the publication itself. The latter only seems necessary if there is a danger that pages may be reproduced out-of- context. Lists Avoid over-punctuating lists. Be consistent in list structure and punctuation. Enumerate lists when items have an order, or where they need to be referenced later (although be aware that this may imply a priority). Special characters Use non-breaking spaces where words should not be separated. Dashes – come in various lengths, choose the correct one for your purpose: The hyphen - is used to join words. The en dash – is used in ranges. En dashes or em dashes — are used in a similar way to brackets. The minus sign − is a separate character altogether.

NB: These are content not presentation! Notation, quantities and units Try to stick with standard choices for symbols representing variables (but don’t forget to also define them!). Consider using a different typeface or italic font for variables. Use SI units as far as possible. Take care when typesetting numbers and units, some tips: Insert a small non-breaking space between numbers and units Ensure you have the SI prefix on your units correct (e.g. 10 Kg is not ten kilograms, it is ten Kelvin grams!) Consider raising units to a negative power in place of the divide symbol Units in tables and figures In tables and figures consider using a slash to denote the units. This is recommended by the BIPM as the correct method of expressing values for multiple quantities.

1200 Fixed 20 ◦C efficient model 1000 Fixed 155 ◦C efficient model

800 Fixed 20 ◦C full model Speed / rads−1 Steady-state thermal tests 600 Datasheet values

400

200

0 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 Torque / mNm

0.8 6.8 13.6 20.4 26.8 32.7 38.3 43.7 48.9 54.2 59.2 Mean current / A

Figure 5.1: Speed-torque curve for fixed temperature simulations, datasheet and steady-state test values for the MMT motor at 24 V Equations Equations are usually set centred, with a reference number on the right-hand side of the page. ˆ ˆ θb = max(θb, min(−θb, ∫ ωb dt)) (3.32)

Use a proper equation editor! Abbreviations (acronyms & initialisms) Very rarely do readers wish that an author had used more abbreviations! Define abbreviations both the first time they are used, and within an abbreviations list. Notes and references Notes: use end-notes or side-notes for digressions that do not belong in the main text. References are a subset of notes. References: Use proper reference management soware; autogenerate bibliographies. Consider hyperlinks if your document will be presented in digital format. Don’t cite fake references! Cross-references Where appropriate, cross-references within the document should be made, including: Chapters and sections Figures Tables Equations Pages Above/below Always use your tool’s cross-referencing functionality for these. Figures Figures should appear as soon as possible aer, but not before, they are referenced in the text. Text in figures should be horizontal (or at least oblique). Text should be legible. All figures should have captions below them. See the Graphic Presentation section for more. Tables Tables should appear as soon as possible aer, but not before, they are referenced in the text. Numbers in columns should be aligned on the decimal. Heavy gridlines are not necessary; a few horizontal rules are ok, but white space is usually better. Quoted numeric precision should reflect accuracy of measurement. A tables should have captions above them. Making decisions on style Start with prescribed document templates. Check whether your organisation has a house style / style guide. Choose another organisation’s manual of style: The Chicago Manual of Style Wikipedia Manual of Style The Guardian style guide BBC News style guide Document tools Word processing: Word, Writer, LyX, Pages, Google Docs Typesetting: InDesign, Scribus, Publisher, LaTeX Content editing (any text editor): Notepad, Notepad++, Emacs, vim For converting content and structure between tools try Pandoc. Break Five minutes only please! Exercise Review of the INCOSE system definition paper

Graphic presentation Visualizing MBTA Data An interactive exploration of Boston's subway system Monday 2/3 7:06 am

Mike Barry and Brian Card - June 10, 2014

Star

Boston’s Massachusetts Bay Transit Authority (MBTA) operates the 4th busiest subway system in the U.S. after New York, Washington, and Chicago. If you live in or around the city you have probably ridden on it. The MBTA recently began publishing substantial amount of subway data through its public APIs. They provide the full schedule in General Transit Feed Specification (GTFS) format which powers Google’s transit directions. They also publish realtime train locations for the Red, Orange, Blue, and Green lines. The following visualizations use data captured from these feeds for the entire month of February, 2014. Green Line data became available in October, 2014 so is not shown here. Also, working with the MBTA, we were able to acquire per-minute entry and exit counts at each station measured at the turnstiles used for payment. We attempt to present this information to help people in Boston better understand the trains, how people use the trains, and how the people and trains interact with each other.

The Trains

In a typical weekday, trains make approximately 1150 trips on the red, Average Number of Trips per Day orange, and blue lines starting at 5AM and continuing through 1AM the Weekdays Saturdays Sundays next morning On Saturdays trains make 870 trips and on Sundays they Is a diagram worth a thousand words? Sometimes no!

But sometimes yes! Always consider text before tables, and tables before graphics. Anscombes Quartet – data

Set 1 Set 2 Set 3 Set 4

x y x y x y x y 10.00 8.04 10.00 9.14 10.00 7.46 8.00 6.58 8.00 6.95 8.00 8.14 8.00 6.77 8.00 5.76 13.00 7.58 13.00 8.74 13.00 12.74 8.00 7.71 9.00 8.81 9.00 8.77 9.00 7.11 8.00 8.84 11.00 8.33 11.00 9.26 11.00 7.81 8.00 8.47 14.00 9.96 14.00 8.10 14.00 8.84 8.00 7.04 6.00 7.24 6.00 6.13 6.00 6.08 8.00 5.25 4.00 4.26 4.00 3.10 4.00 5.39 19.00 12.50 12.00 10.84 12.00 9.13 12.00 8.15 8.00 5.56 7.00 4.82 7.00 7.26 7.00 6.42 8.00 7.91 5.00 5.68 5.00 4.74 5.00 5.73 8.00 6.89 Anscombes Quartet – statistics All sets have the same: Mean (x¯ = 9.00, y¯ = 7.50) 2 2 Variance (σx = 10.00, σy = 3.75) Correlation (ρx,y = 0.816) Anscombes Quartet – graphics

For another fun example check out the Anscombosaurus! Two motivations for visualisation Discovery: To explore and understand a dataset or problem space As a step towards automation (debugging) To aid human-in-the-loop processes Working with data Presentation: For explanation Presenting information

The graphic may need to display the data, but the message should be the information What is the most popular visualisation in Systems Engineering?

Operation Concept of and Operations Verification and Maintenance Validation Project Requirements System Definition and Verification Architecture and Validation

Integration, Detailed Test, and Project Design Verification Test and Integration ImplementationImplementation

Time

But why is it a ‘V’? Dataset types Tables Networks Spatial (Geometry)

Attributes (columns)

Items Link (rows) Position Node (item) Cell containing value

Spatial (Fields) Multidimensional Table Trees Grid of positions

Cell

Value in cell Attributes (columns)

Value in cell

Items Items (nodes) Grids/Items

Attributes Links Positions Attributes Attributes Attributes Ordinal Categorical

Quantitative Encoding channels Magnitude Channels: Ordered Attributes Identity Channels: Categorical Attributes

Position on common scale Spatial region

Position on unaligned scale Color hue

Length (1D size) Motion

Tilt/angle Shape

Area (2D size)

Depth (3D position)

Color luminance

Color saturation

Curvature

Volume (3D size) Why are some channels more effective?

n Stevens Psychophysical Power Law: S = I Crowdsourced channel testing

Positions

Angles

Circular areas

Rectangular areas (aligned or in a treemap)

1.0 1.5 2.0 2.5 3.0 Log Error

Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design Keys and values Keys: Independent attributes (categorical or ordinal) Values: Dependent attributes (categorical, ordinal or quantitative)

Zero keys: Scatterplot One key: Bar chart, Line chart, Dot charts, Coloured scatterplot Two keys: Heatmap, Stacked bar chart, Coloured bar/line/dot charts Three or more keys: ‘Small multiples’ of the above Small multiples

4 4 0 0 ° ° 3 3 0 0 ° ° 2 2 0 0 ° ° 1 1 0 0 ° ° 125°

4 4 0 0 ° ° 3 3 0 0 ° ° 2 2 0 0 ° ° 1 1 0 0 ° ° 90°

4 4 0 0 ° ° 3 3 0 0 ° ° 2 2 0 0 ° ° 1 1 0 0 ° ° 55°

left right Categorical keys Choose a sensible order for the key. Don’t connect points between categorical data.

60 60 50 50 40 40 30 30 20 20 10 10 0 0 10-year-olds 12-year-olds 10-year-olds 12-year-olds

60 60 50 50 40 40 30 30 20 20 10 10 0 0 Female Male Female Male

Bars and Lines: A Study of Graphic Communication Networks and trees Both are highly relevant to Systems Engineering. Networks: Visual modelling languages (SysML, LML, OPM, Simulink) Interfaces Stakeholder relationships Trees: Work Breakdown Structures System Breakdown Structures Filesystems Node–Link diagrams (networks and trees) Intuitive, but limited in network size (consider interactivity or separate views). Link density = number of links per node. Trees have link density of one. Maximum link density for effectiveness is around 3 or 4. Consider layout: Automatic (e.g. force-directed) or manual Reading direction Information density (see later) Minimise edge crossings Minimise ratio between longest and shortest edges Credit: Mike Bostock Credit: Mike Bostock Matrix views (networks and trees) In graphs of more than 20 vertices, matrix views typically perform better; the exception being where path finding is important.

Credit: Brian Staats Enclosure (trees) Show hierarchical structure through containment rather than connection. Credit: Mike Bostock Credit: Mike Bostock Spatial data Where data is spatial, it is usually beneficial to present it spatially. Geometry: Chloropeth maps Fields: Isocontours, Vector fields Documen Great Western Route Modernisation Programme Project GW ISI Architecture: Interface Map - Wales Instance Date: 01/01/2014 A B C GWISI Prepared by WSP | Parsons Brinckerhoff for Network Rail Performance View Incidents Combined Delays Source: Standard Hotspots: Hide 2014 2015 2016 2017 2018 2019 2020 2021

Key No. of incidents 0 1+ 44+ 66+ 110+ 221+ 353+ 662+ 1214+

To Merthyr Tydfil To Rhymney

To Aberdare Abercynon Jn

Ebbw Vale To

To Treherbert Pontypridd Jn Ebbw Vale Parkw

Maesteg To Coryton

n J N Heath Jn t S n ee u Radyr Jn Q

Tondu Jn

Cardiff Queen Street Po rt T S a w lb M M Queen St S Jn a a a n o rg r B se t a g R B P a P m M a I r o C L a a m D id a Lo a M r g n r o n N r g M G e t d p d k id a o E n y iff o e w d m o N d c W r a a le E r lu W e th y s D E n To Jn Jn Jn Jn Jn Jn Jn C Ll o yn Jn C Carmarthen c fi A k J N R e n p F F o D Tu Knuckle Yrd M M Lo Radyr Branch Jn I n F F C n a a th F e rg E rg i C a l a Jn a w E rd m m ck N i Y A o T ff Swansea Loop E Jn a M b L Penarth Curve N Jn rd b n R J a e J k A n rg y S r L a W p a Swansea Maliphant m o o r o P D k L n Penarth Curve S Jn Dpt p s h t it ia w in ck N SWANSEA Lo

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Penarth Colour Categorical: There are a limited number of discriminable bins (max 6–12), ensure that there is clear separation between them. Use variations in colour hue. Ordered: Colour scales should be perceptually linear. Use variations in colour luminance, saturation and/or hue. Rainbow colourmaps (e.g. ‘Jet’) are a poor default, as they are perceptually unordered and nonlinear. Try Viridis or Cividis. Consider colour-blind users (Cividis is better). Use online tools such as colorbrewer to choose a palette.

Credit: Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data, Jamie R. Nuñez, Christopher R. Anderton, Ryan S. Renslow Or, taken from a tweet by Matthias Bussonnier: Information density

(Also called data-ink ratio)

Above all else show the data. — Edward Tue

Amount of information encoded, vs empty space in the graphic. Generally higher information density is preferred. Subtract unnecessary ink (both data and non-data). De-emphasize remaining non-data ink. Emphasize remaining data ink. Labelling graphics Always label graphics! (items and attributes) Ensure labels are legible (axis, font, size). Avoid abbreviations. Use horizontal labels wherever possible. Rotating the graphic can make this easier. Oblique labels are a compromise. Make sure all encoding is labelled. Legends are ok, directly labelling the data is better. Producing graphics 1. For each item, choose the attribute(s) you wish to display 2. For each attribute to display, choose an appropriate channel to encode it 3. Choose a layout and labelling structure 4. If appropriate, choose how your item keys are sorted 5. Review and iterate Graphics tools Drawing: Visio, Inkscape Data drawing: Tableau, Excel, Google charts Data linking: D3 (javascript), Shiny (R), Matlibplot (Python), Visio Lunch

extuitive.co.uk/ip

Personal graphical grievances Unnecessary graphics

50% 50% Lack of labelling

16 14 12 10 8 6 4 2 0 Poor fonts and/or legends

0 5 10 15 20 25 30 35 Abbreviations 120

100

80

60

40

20

0 PBA TRW AFD-BB Use of angles or areas

A B C D Unnecessary dimensions

60

40

20

0 John Rosie Barry Mary Erroneous linkages

200 180 160 140 120 100 80 60 40 20 0 Peugeot Fiat Volkswagen Honda Vauxhall Irrelevant colours

30

25

20

15

10

5

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Unsorted data

Gorilla

Lion

Buffalo

Monkey

Wildebeest

Tiger

Zebra

Elephant

Giraffe

0 10 20 30 40 50 60 Scale or baseline issues

Us Competitor A Competitor B 35 50 40

30 35 45 30 25 40 25 20 20 35 15 15 10 30 10 Group exercise Improve upon specific graphics A comparison of population and how people travel Greater Sydney and its global city peers

Tokyo Berlin 13.6m 3.5m 6,200 people/ km2 3,900 people/ km2

Los Angeles Melbourne 13.0m 4.3m 1,050 people/ km2 460 people/ km2

Chicago Greater Boston 4.7m 9.5m 2 3,400 people/ km2 1,300 people/ km

Greater Greater London Sydney 8.7m today 2 5,800 people/ km 5m 410 people/ km2

New York (f ve boroughs) Singapore 8.4m 5.4m 7,000 people/ km2 11,000 people/ km2 Paris San Francisco 8.4m (Bay area) 6,000 people/ km2 7.7m 425 people/ km2 Greater Sydney in 2056 Global City Non-Car Mode Share 8m 610 people/ km2 Major City Non-Car Mode Share

Car Mode Share

Figure 13: Private vehicle mode share – international comparison

Taken from the TfNSW Future Transport Strategy

Taken from the seminal work of Eric Honour (https://asew.com.au) 1. What do you think the overall message is? (information) 2. What is the background data? (items and attributes) 3. What type are the attributes? (ordinal/quantitative/categorical) (keys/values) 4. What are the channel encodings that have been used? 5. What different (/better) encodings could be used? 6. Sketch out a new version and label it. Publication Remember the basics! Spell check Check links and references Set document properties Remove comments and version history Check formatting (in final publication format) Work in a suitable format Raster drawing tools manipulate pixels in an image. Except in rare cases, they do not embed the data. Vector drawing tools manipulate shapes in a coordinate system. They allow data to be directly represented and embedded. Benefits of vector formats: Vector → raster is easy, raster → vector is difficult and messy Vector files are typically smaller Vector files are easier to edit Vector images scale infinitely Deliver in a suitable format Word and Excel are editing tools, with reading modes bolted on. Due to proprietary formats they also require the recipient to own a copy of the tool. PDF is a better alternative. Delivering in PDF will: Reduce ‘accidental’ editing Reduce plagiarism Be more likely to reproduce correctly Be supported by many free viewers HTML is emerging as an even better standard. Image formats

What image format should I use?

Is part or all of it a vector image?

No Yes

Do you need it to work Do you need animation? in Microsoft Office?

No

Would you sacrifice some Yes detail for a small file size?

Yes No Yes

Do you want No transparency?

Yes No

portable network graphics joint photographic experts group graphics interchange format scalable vector graphics windows/enhanced metafile bitmap .png .jpeg / .jpg .gif .svg .wmf / .emf .bmp Advanced techniques Interactive graphics Interactivity is useful to handle complexity, it: Allows extra data to be shown without cluttering the graphic Allows the user to query the data Provides a lower level of detail Allows connection between views Engages and draws-in the reader Avoid unnecessary interactivity, and do not rely on it. Multiple views A presentation of the data is only one possible view of it. Different views may be useful for: Different stakeholders Presenting different information (based on the same data) Showing different levels of abstraction to develop understanding Document Reference Number London North Western (LNW) Project Originator Doc.ID Discipline Seq. Number Version Instance Date: 01/01/2014 Platform length assessment for: 1 2 3 4 5 DRAFT Prepared by WSP | Parsons Brinckerhoff for Network Rail Class 158/0 2 car, 2 units (90.28 m) 2014 2015 2016 2017 2018 2019 2020 2021

To Penrith, Carlisle and Scotland

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l a o r n i v C a a l B h o a e e

a h h n

Arnside l h R D U C K r t s n t Stephen and Carlisle

r n g k p

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Name John Welford Date Checked Name Kevin Gedge Date Approved Name Date Page Drawn by: Signature by: Signature by: Signature 1 of 1 Levels of abstraction Present to reflect Systems Thinking – take the reader through multiple levels of abstraction…

Credit Bret Victor use arrow keys

"In science, if you know what you are doing, you should not be doing it. In How do we explore? If you move to a new city, you might learn the engineering, if you do not know what you are doing, you should not be territory by walking around. Or you might peruse a map. But far more doing it. Of course, you seldom, if ever, see either pure state." effective than either is both together — a street-level experience with

—Richard Hamming, The Art of Doing Science and Engineering higher-level guidance.

Likewise, the most powerful way to gain insight into a system is by How can we design systems when we don't know what we're doing? moving between levels of abstraction. Many designers do this instinctively. But it's easy to get stuck on the ground, experiencing concrete systems The most exciting engineering challenges lie on the boundary of theory with no higher-level view. It's also easy to get stuck in the clouds, and the unknown. Not so unknown that they're hopeless, but not working entirely with abstract equations or aggregate statistics. enough theory to predict the results of our decisions. Systems at this boundary often rely on emergent behavior — high-level effects that arise This interactive essay presents the ladder of abstraction, a technique for indirectly from low-level interactions. thinking explicitly about these levels, so a designer can move among them consciously and condently. When designing at this boundary, the challenge lies not in constructing the system, but in understanding it. In the absence of theory, we must I believe that an essential skill of the modern system designer will be develop an intuition to guide our decisions. The design process is thus using the interactive medium to move uidly around the ladder of one of exploration and discovery. abstraction. Transitioning graphics Animated transitions between views of the same data can be used to help aid understanding. Research has shown that animated transitions between related data graphics significantly improve visual perception. These benefits are greater if the animations are staged. Analysis of climbers anatomy survey results

We show each respondent by a segment in the chart with two colours side-by-side, one colour represents whether they have Palmaris Longus in neither ( ), one ( ), or both hands ( ), the other represents whether they suffer from Dupuytren's contracture in neither ( ), one ( ), or both hands ( ).

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Palmaris Longus Explorable explanations Explorable explanations are reactive and explorable documents that allow a reader to: Understand the authors underlying models Play with model assumptions Provide contextual information to learn related material Cross check the authors claims There are a large number of examples available. Most are built in HTML, however the Computable Document Format does exist as well. A recent development is the Observeable coding system, which provides a reactive programming environment to support explorable explanations, visualisations and active reading.

Speed reading There are a few technologies around such as Spritz to facilitate speed reading. Spritz E-books E-books are arguably the future of reading: ‘Paperless office’ Searchable Distributable Compact Resizable (reflowable text) There are a variety of formats, readers and creation tools available, formats can be converted easily. Summary Discussion The end Feedback [email protected] @extuitive