produce three documents: a dashboard that uses visual encodings to show structure and patterns in a data set; a story script that describes these and identifies important features that are revealed; a design justification that explains your design decisions with coherent arguments that

EPM948 Communication & Presentation COURSEWORK INSTRUCTIONS 2016/17
V6 – 12/12/16 changes from original release highlighted in yellow 1 / 4
Your assessed task is to produce three documents:
a dashboard that uses visual encodings to show structure and patterns in a data set;
a story script that describes these and identifies important features that are revealed;
a design justification that explains your design decisions with coherent arguments that
draw upon established best practice.
The three documents must be submitted through Moodle by Sunday 22nd January 2017.
See Moodle for the exact deadline and submit well in advance of this.
Late work will not be marked – a mark of zero will be returned if work is not submitted on time.
This individual piece of assessed coursework work will account for 100% of your module mark
The Scenario
You are working for Transport for London (TfL) as part of the ‘data analytics’ team that manages
and develops London’s Cycle Hire Scheme. Your remit relates to the cycle hire stations in a given
postcode and you have access to data describing the status of a series of these stations over a
particular period. Your task is to produce a single static dashboard that uses graphics to show key
characteristics relating to the status of the stations as a mechanism for reporting and decisionmaking.
This graphical summary will be used to establish the status of the stations and support ongoing
plans to redistribute bikes to ensure that stations have a good balance of available bikes
and docks – so that those using the scheme can collect and park bikes at all stations at all times.
Specifically, the dashboard will be used by the data analytics team and senior officers at TfL to …
i. find differences – stations, days or times that have contrasting characteristics to others;
ii. detect trends in bike and dock availability over time in the selected postcode;
iii. identify where and when the scheme is failing – with docks or bikes unavailable;
iv. compare stations and time periods, concurrently where possible;
v. investigate whether ongoing or periodic trends are evident in the data.
There are various actions that the team might consider given this information …
1. rebalancing stations – regularly moving bikes from one station to another
2. extending stations – increasing capacity by adding docks to existing stations
3. adding stations – building new facilities where demand seems high
Your job is to present the data in ways that can inform such decisions and, having done so, make
recommendations for action.
The data analytics team is also considering commissioning a visual analytics system for use in this
process. In addition to the static dashboard, you must also provide a prototype example that is
your recommendation for such a system. This must be an annotated version of your dashboard that
describes and illustrates the dynamic analytical features that you think should be added to your
dashboard in a visual analytics system to be commissioned in the future. So, you must produce a
static graphic (a screen dump of your dashboard) with labels and annotation that show a dynamic
system that might be used for this scenario in the future.
You should use the annotations on the dashboard screen-dump to show your knowledge of visual
analytics functionality and capability that could usefully be applied to this scenario. You should
also use the opportunity to show that you can label effectively.
EPM948 Communication & Presentation COURSEWORK INSTRUCTIONS 2016/17
V6 – 12/12/16 changes from original release highlighted in yellow 2 / 4
The Brief
You must produce a packaged workbook using Tableau v10 (TWBX). This must contain the original
TfL Cycle Hire data that you have been allocated and a series of graphics designed for the data
analytics team. You must address the scenario graphically in a single static dashboard that
contains multiple related graphics designed to enable the data analytics team to perform the tasks
listed above. Your graphics must use established principles for effective design and communication
to present actionable information to the data analytics team. How you design your graphical
output – the specific data and the way in which you choose to represent this – is entirely up to you.
However, you must use this opportunity to demonstrate that you have achieved the module
learning outcomes – so please check these on Moodle and use them to guide your work.
You must also submit a story script, in which you describe the detail, structure and patterns that
your graphics reveal in the context of the scenario. The script will be read by those viewing the
dashboard and should relate directly to it. It should contain and explain your suggestions for action.
Imagine that you are using the script to present your findings to the data analytics team. The script
should include the things that you would say in a short presentation that uses the dashboard.
Finally, you must provide a design justification (PDF) that explains and supports your design and the
decisions made. This justification should relate the tasks you are addressing to theories and practice
of good data visualization design as discussed in the lectures and the associated books, papers
and web-sites. You might want to include sections on layout, visual variables used, design principles
considered, etc. as you explain your design decisions and consider their implications. You could
use the dashboard guidelines introduced in the lectures (Layout; Symbolization; Colour) to frame
and justify your design decisions and should make specific reference to approaches that you have
seen that influence your design ideas. Imagine you are documenting your decisions and showing
that they represent best practice in a way that would be useful to colleagues from the data
analytics team as they develop data designs in the future. Record, rationalise and justify your
design decisions and reflect on the extent to which they represent the data well and are effective.
The penultimate page of the design justification must contain the prototype example that
annotates the ‘dashboard’ worksheet with clear descriptive labels to represent and specify
imagined dynamic features that could be added to this static dashboard in the proposed visual
analytics system. You should show your understanding of interactions and analytical functionality
that would help the data analytics team with their analysis (and your ability to label and explain
effectively) through labels, arrows and other informative annotations on this prototype example.
The final page should include a complete list of the references to all the sources you have
consulted in producing your work, including Web pages.
The Data
An individual data set will be made available to you through a text file on the EPM948 Moodle
homepage. You’ll need to download this and open it in Tableau.
Each data set will contain hourly information regarding the number of bikes and the number of
docks available at a series of bike stations within a particular postcode over a period of time.
Time periods and postcodes vary between students, as will the number of stations, data items and
patterns contained within – you will each have different structure and patterns to identify and this is
likely to result in different designs, different stories and different actionable information.
You will need to process your data and having considered it may want to select a subset of
particular bike stations, days of the week or times of day as the focus for your dashboard. If you do
so, then you will need to justify these choices and explain the implications as per the scenario.
Note that you will gain credit for showing some complexity in your data with clarity – we are looking
for elegant, well-informed graphics that show structure and trend clearly. So, any sub-setting of
your data will need to be well justified. Whilst acceptable if appropriate to the data set and task
under consideration, you will need to explain why you have decided upon a particular focus if you
choose to use a subset of the data in your dashboard. Remember, we are looking for data dense
graphics and well-informed recommendations made through actionable information.
EPM948 Communication & Presentation COURSEWORK INSTRUCTIONS 2016/17
V6 – 12/12/16 changes from original release highlighted in yellow 3 / 4
The exercise is intended to allow you to apply and present the visual design skills and knowledge
that you have developed during the module. Submissions will be given a single mark, awarded
according to the rubric available through the Design Justification assignment – please check this to
get a feel for what is expected for each grade for each criterion and to guide your approach.
In general terms, we are looking for the following:
• Solutions that meet the task objective by clearly showing patterns in the data they present.
A high-quality submission will use visual techniques to emphasise the important and deemphasise
the unimportant. It should follow good practice in its design – as detailed in the
lectures and recommended reading and as demonstrated in the examples we have seen.
• The degree of sophistication of the graphical techniques you apply.
You should show that you have made full use of the range of recommended approaches
to visual presentation of data by developing visual solutions that meet the task objectives
and describe and rationalise the design decisions fully. Sophistication does not necessarily
mean complexity. We are looking for elegant, effective, clear, informed visuals.
• The evidence provided in your design justification that you have understood and applied
good practice in data visualization design when presenting the data.
Justifications should refer explicitly to established theory and literature on visualization
design through appropriate citations and demonstrate an ability use this to make effective
design decisions. In the case of graphics, often ‘less is more’ – but the process of selecting
what to show and how to show it needs thorough description and evaluation of design
alternatives. You will need to use information that we have considered in the lectures and
that are documented in the literature to explain the influences on your design decisions.
• The quality of your ideas about interactive possibilities for using visual analytics.
Marks will be awarded for the relevance and sophistication of the visual analytics
techniques suggested in your prototype example, the quality of the annotated design and
the degree to which the approaches that you recommend be used in the proposed
dynamic system for VA are rationalised, explained and communicated in your justification &
design document. There is room for plenty of creative thinking about the use of analytic
capability through visual interfaces here – be ambitious when explaining possible
interactions. Use your experience of interactive visual data exploration to inform your ideas.
• The extent to which you are deemed to have met the project brief.
A good submission will need to have successfully achieved the objectives set out in the
scenario above – emphasising trends and highlighting interesting characteristics.
Academic Conduct
This is an individual piece of work and you will each be working with a different data set.
You are welcome, and even encouraged, to support each other with general help in using the
software, and in thinking about the data and the trends and patterns within it. However, you must
not share your own findings, designs or your rationale with other students.
Accusations of academic misconduct (collusion) may arise if these are discussed or shared.
Those found guilty of academic misconduct will receive a mark of zero for this piece of assessed
work. Further penalties may be applied in line with University policy on such matters.
All submitted work will be analysed using the Turnitin plagiarism detection service. Where academic
misconduct is deemed to have occurred a mark of zero will be returned. Where poor academic
conduct is deemed to have occurred marks will be reduced significantly to account for this.
EPM948 Communication & Presentation COURSEWORK INSTRUCTIONS 2016/17
V6 – 12/12/16 changes from original release highlighted in yellow 4 / 4
You will need to submit three documents – separate submission areas are available on the module
homepage for each of these:
1. WORKBOOK – a Tableau Packaged Workbook (TWBX)
A Tableau packaged workbook (TWBX) contains data as well as graphics – we will need the data
to be able to see your graphics and mark your work. Be sure to get the format right and include the
data. If there are no data, you will receive no marks.
The workbook must contain a dashboard named ‘dashboard’. This must use static graphics to
present information and communicate findings established through your analysis that are relevant
to the scenario. It is the focus of the assessment and will be marked according to the criteria
described here. Markers will not consider other worksheets or dashboards – you will thus need to
describe any assumptions or data processing methods in the design justification document.
The dashboard must be sized at 1400*800 – landscape. It must not rely upon any interaction – you
must produce a static graphic with no dynamic features for inclusion in the PDF and printing.
2. TEXT – Story Script (text)
A 250-word description of what the graphics show, that addresses the scenario. Create text in a
word processor or text editor and paste it into the text entry box. Be sure to add spaces after all full
stops. Use blank lines to separate any paragraphs. Do not use any other formatting such as bullets,
bold or italics. Markers will use a screen-reader to read the script as they consider the dashboard.
3. DOCUMENT – Design Justification Document (PDF)
The document should contain the design justification, prototype example showing visual analytics
possibilities and references to work that informs your design. It must be in PDF format, with font size
at 11pt minimum. This single PDF must consist of exactly 4 pages1 of A4 that include, in this order :
i. the design justification – explaining and rationalising the design choices made – 2 PAGES;
ii. the prototype example – an annotated version of the dashboard showing how visual
analytics could be beneficially applied to the dashboard to address the scenario – 1 PAGE;
iii. complete references – to all sources consulted in producing your work, including Web
pages, using Harvard or an established alternative – 1 PAGE.
All three items – Workbook, Story Script and Design Justification – must be submitted via Moodle
before the specified deadline. Work is only considered ‘submitted’ if a readable digital copy is
uploaded through Moodle on time using the appropriate assignment mechanism.
Late submissions will not be marked. A mark of zero will be returned in such cases other than where
the University’s procedures for reporting extenuating circumstances have been followed and the
Board of Assessment has accepted any such circumstances. You are strongly advised to check the
submission deadline on Moodle immediately and to submit your work well before it.
Submissions will not be marked if they are late, in a format other than that stated here or based
upon data other than that allocated to the submitting student. Submitted workbooks in formats
other than TWBX, in other versions of Tableau than that stated here, or that do not contain the data
used in the graphics as part of the submission will not be marked. Marks of zero will be returned in
such cases.
1 No title or contents pages please, unless you have been diagnosed with a Specific Learning Disability by
Learning Success at City University. In this case, please add an additional title page with a yellow sticker that
informs markers of your condition and any allowances. In these cases we will accept an additional title page.

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Is Huge Information Corrupting the U.S. Election Course of?

As the 2020 election cycle ramps up, voters can expect a flurry of targeted advertisements fueled by big data on their doorsteps, inboxes and social media feeds. While microtargeting based on demographic information is not a new trend in campaign strategy, campaigns traditionally relied on analyzing voter behavior within broader categories such as age or gender before big data was easily accessible.

Molly Kozlowski

立中式速繪 動態姿勢繪圖技巧 ポーズが描ければ 動きも描ける たてなか流クイックスケッチ

作者: 立中順平  
出版社:楓書坊 |譯者: 游若琪
規格:平裝 / 217頁 / 19 x 25.7 x 1.08 cm / 普通級 / 部份全彩 / 初版
購買請點我【 博客來書店
◆注意,如果有瀏覽器有安裝檔廣告的程式 連接AP 有可能失效◆ 

  ➊ 建立正確的心態
  ➋ 練習簡單畫全身的速繪技巧▁▁火柴人練習
  ⑴ 將全身分成15個部位,
  「頭 部、胸部、骨盤」是橢圓形。
  ⑵ 注意基本結構,不要注意輪廓和細節
  ⑶ 立體化
  ⑷ 創造不對稱平衡
  1993年開始在Disney Animation Japan擔任動畫師。
  後來進入Answer Studio,目前是自由工作者。
  曾參與《跳跳虎歷險記》(Disney)、《棒球大聯盟》(電視版)、《鑽石王牌》、《YURI !!!on ICE》、《佐賀偶像是傳奇》等作品。
由曾經在華特迪士尼動畫工作室與日本動畫公司Answer Studio的日本資深動畫師立中順平撰寫的速繪教學書
第一章節:速繪繪畫 P1-73.

Design College students’ Summer season Break

With summer break fast approaching, graphic design students like me are trying to figure out productive ways to spend their time. Work for money? Work for experience? Summer classes?

I’ve spent the past few months doing everything I can to
find an internship this summer. Finding a company that isn’t an MLM and will
actually pay good money for your design work is tough. Luckily, graphic design
is a field that’s in demand, so there are a lot of good options out there.

The other option for getting design experience during the summer
break is freelance work, but that comes with its own slew of issues. There’s
nothing worse than beginning to work with a client and getting excited for a
project just for them to look at you with a face like the Surprised Pikachu Meme
when you start to discuss cost.

With two weeks left in the semester, here’s hoping we figure
something out soon!