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

EPM948 Communication & Presentation COURSEWORK INSTRUCTIONS 2016/17 V6 – 12/12/16 changes from original release highlighted in yellow 1 / 4 Overview 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 Marking 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 emphasis 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 rationalized, 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 Submission 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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