ArashLari Week 11
From LMU BioDB 2017
Contents
Development Terms
- Read: The Data-Driven Design Era in Professional Web Design
- By: Lassi A. Liikkanen
Outline and Presentation
What is Data Driven Design?
- Traditionally, products were designed by the designers intuition and opinion
- This is because collecting information about user activity has been difficult until recently
- The rise of technology and internet based services has led to evidenced-based design
- Companies and developers want to know that their intended users will be able to easily use their service before it affects sales
- Designing based off of results empirical user evidence is called data driven design
- There are assistive and agentive generative tools to help creative tasks
- A generative design process basically means designing and redesigning based on how the previous iteration was received
- It’s basically an assortment of tools at the disposal of the designers and the developers that they can use in a multitude of ways to gauge how effective their design is.
- The basic idea of this design philosophy is to collect data, combine it with other data, and analyze it for implementation in the final design
- There are assistive and agentive generative tools to help creative tasks
Data Driven Design of Web Services
- Web interaction design is a field that utilizes data design driven solutions frequently
- Major internet companies often build their own experiment-management platforms so they can run many different experiments in parallel with automation
- Data-collection can be separated into two types of solutions: Active and Passive
- Active data collection is reliant on user input, and as such it’s considered qualitative
- It doesn’t really fit the mold of DDD very well if the scale is large
- Surveys are often plagued with many issues such as reluctance to participate and low quality answers that don’t provide very much insight
- In smaller cases it is very useful, such as using an online focus group to get detailed reactions and responses
- This is costly, which is why large corporations don’t often do this
- Passive data collection, or passive tracking is any kind of recording of user activity
- Screen recordings, heat maps, experiment management, and descriptive behavioral analytics are some passive tracking tools
- Screen recordings are full recordings of the users screen for later analysis.
- Provides a very detailed view and a lot of useful implementation
- However, raises privacy and ethical concerns and can’t really be automated to gain insight
- Screen recordings, heat maps, experiment management, and descriptive behavioral analytics are some passive tracking tools
- Heat maps are a way to visualize the most frequently clicked on and hovered on spots of a page
- It isn’t always very clear because some pages might be context specific, but it still can provide enough information to help optimize the design of the page
- Experiment management is basically having 2 or more types of designs be tested on to find which features and design choices should be kept or removed
- It allows developers to find fail new ideas quickly so they don’t have to waste time with subpar designs
- They can be automated but their shortcoming is the numbers aren’t always that insightful
- Behavioral analytics are the precursor to all current DDD solutions
- It’s all the contextual data related to the visit, such as the amount of time spent and on what pages, what elements were clicked and in what order, etc.
- This information is more useful for business and marketing decisions rather than design decisions.
- Many companies offer analytics solutions for developers
- Google is the biggest by far, but there are others such as Adobe Analytics, KISSMetrics, and IBM Tealeaf
- Many companies offer analytics solutions for developers
- Active data collection is reliant on user input, and as such it’s considered qualitative
Conclusion
- Data driven design provides designers a strong incentive to adopt a hypothesis-driven approach to design research
- Having a clear hypothesis is important as it will affect the way one interprets data and identify which results are the most significant
- The age of Data Driven Design draws heavily upon designer moral, integrity, and candor.
- Ethics of how data is collected and used is very important, and consent is key in ethical data acquisition.
- The future of data driven design will be with tools that couple seamlessly with design processes, be adaptive to change, and show maturity in addressing ethical questions.
- Designers will embrace more quantitative data as tools that allow for scalability become available
- Design will introduce assistive and agentive tools that do things with us and for us
- What will we use for our project?
- We won’t use any of the passive tools directly
- Although useful, we do not have the means to get enough different users to get fruitful information using these methods
- Although we might implement experiment-management within our own small group and see what we collectively thinks works best
- We will be using active data collection, and ask our fellow classmates to browse our site and give us feedback as they use it
- This level of interactivity with the end-user provide useful insight
- We won’t use any of the passive tools directly
Electronic Notebook
Acknowledgements
- I worked with my homework partners Hayden, Mary, and Nicole. We mostly communicated via phone call or text message.
While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source. ArashLari (talk) 01:21, 14 November 2017 (PST)
References
- Liikkanen, L. (2017). The Data-Driven Design Era in Professional Web Design. Accessed November 13, 2017, from http://delivery.acm.org/10.1145/3130000/3121355/p52-liikkanen.pdf?ip=157.242.223.254&id=3121355&acc=ACTIVE%20SERVICE&key=80B0E63637265656%2E958C566062FD1C18%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=829067610&CFTOKEN=20249523&__acm__=1510614806_1e8b314e23f771f9b139d99596801365
- LMU BioDB 2017. (2017). Week 11. Retrieved November 13, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_11
Links
BIOL/CMSI 367-01: Biological Databases Fall 2017
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Shared Journals:
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- ArashLari Week 5 Journal
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