This document discusses developing a product to gather information from users to present to hackathon attendees. It tested several methods for gathering data, including freeform interviews, structured question lists, and paper forms. It determined that structured notes assigned to questions may be the best format. Creating an effective digital tool for self-service data gathering poses challenges. Interviews can provide more useful data but are labor intensive. Information for event planners often comes from representatives of community groups rather than directly from users. Highlighting archetypal users may help effectively summarize bulk research.
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The race is on to gain strategic and proprietary insights into changes in customer preferences before your competitors. This workshop will cover how and why machine learning is the tool for marketers to drive revenue and increase market share. The adoption of machine learning does not happen overnight. We will discuss the Five Es of machine learning maturity – Educating, Exploring, Engaging, Executing and Expanding. Hear real-world examples of using machine learning to accelerate revenue, identify new customers and introduce new products based on machine learning capabilities.
Next DSS MIA Event - https://datascience.salon/miami/
Presentation on collaboration tools and tips for lawyers by Dennis Kennedy and Tom Mighell for ABA TECHSHOW 2009, Based on their book, The Lawyer's Guide to Collaboration Tools and Technologies: Smart Ways to Work Together.
A Hybrid Approach to Data Science Project ManagementElaine K. Lee
A talk about how Civis Analytics, a data science consultancy and software company, does project management using a blend of approaches from academia, consulting, and software engineering.
Data Science Salon: Adopting Machine Learning to Drive Revenue and Market ShareFormulatedby
The race is on to gain strategic and proprietary insights into changes in customer preferences before your competitors. This workshop will cover how and why machine learning is the tool for marketers to drive revenue and increase market share. The adoption of machine learning does not happen overnight. We will discuss the Five Es of machine learning maturity – Educating, Exploring, Engaging, Executing and Expanding. Hear real-world examples of using machine learning to accelerate revenue, identify new customers and introduce new products based on machine learning capabilities.
Next DSS MIA Event - https://datascience.salon/miami/
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How content analytics can be brought into research. The presentation was given as a webinar for the IE Business school where John Griffiths is a visiting professor.It features examples of the use of Purefold transmedia as a research methodology and the use of demographic replicator research bots. Part of the Cloud of Knowing project
This presentation will examine the purpose and application of information architecture for the so-called ‘next generation’ of information tools, including blogs and wikis. We will introduce ‘needs based’ information architecture, the methodology used for organising and designing information-rich environments in a way that allows people to use them more easily. We will then look at how the best practice principles behind this approach apply equally well to emerging technologies.
Presented at Open Publish 2007, by Patrick Kennedy of Step Two Designs.
Bram Wessel on UX Techniques for better Information ModelingBram Wessel
Bram Wessel's presentation at Taxonomy Bootcamp 2013 on how to use techniques from the User Experience discipline to develop and refine better Information Models
Requirements Engineering for the HumanitiesShawn Day
This workshop explores how requirements engineering can be employed by digital and non-digital humanities scholars (and others) to conceptualise and communicate a research project.
requirementsEngineeringAs the field of digital humanities has evolved, one of the biggest challenges has been getting the marrying technical expertise with humanities scholarly practice to successfully deliver sustainable and sound digital projects. At its core this is a communications exercise. However, to communicate effectively demands an ability to effectively translate, define and find clarity in your own mind.
How content analytics can be brought into research. The presentation was given as a webinar for the IE Business school where John Griffiths is a visiting professor.It features examples of the use of Purefold transmedia as a research methodology and the use of demographic replicator research bots. Part of the Cloud of Knowing project
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User Centered Design: guarantee that your business process automation project...Bonitasoft
Wide user acceptance is one of the biggest challenges companies face when launching a new project, product, or service. Any of these can fail for a variety of reasons, but failure is often due to a disappointing user experience.
The process of User Centered Design actively takes into account the needs, expectations, and characteristics of end users at each stage of the development process, leading ultimately to better user satisfaction.
The tools and processes manager of a large French automotive group recently noted, "You have to be user-centric to successfully digitize your processes." End users can feel, “This was actually designed with me in mind - my wants and needs were actually considered before a tool was imposed on me to use.”
From layout to delivery of the first iteration and through continuous improvement, learn how to use the Bonita UI Designer as an iteration tool to guarantee an ideal match with the actual needs of end users.
video: https://youtu.be/vmZgeJ86738
User Centered Design: guarantee that your business process automation project...
Hack for
1.
2. As well as being an idea for an approach to hackathons this is:
A product to gather information from a group of users &
present the collected data to hackathon attendees
4. Methods for gathering data:
Free Form Interview Email List of Questions
Give out form with paper
and pen
Structured list of interview
questions + notes
Tested with: Saha & Noelle Tested with: Ian Tested with: Noel Tested with: Noel & Jeremy
Pros:
-Natural & Conversational
-Interviewer needs
Pros:
-Structured
-Digital Data
-Flexible time demands
Pros:
-Structured
-Flexible time demands
-No technology needed for
user
Pros:
-Structured
-Can be flexible with follow
up / new questions if needed
Cons:
-Interviewer needs to be well
enough versed to ask the
right questions
-No Structure
Cons:
-Burden of need to be concise
-Can be put off indefinitely
-No interaction between
interviewer / interviewee
Cons:
-Burden of need to be
concise
-Analog data
-Can be put off indefinitely
Cons:
-Taking notes on the computer
is tricky and seems like you are
distracted
Result:
Good but labour intensive
and unstructured ;/
Result:
Still awaiting response :(
Result:
Refused by test subject!
Result:
Good but labour intensive ;/
Some hastily A->B tested methods done on site at NYC Big Apps
5. Resulted in:
Notes..
I think the end form for this data is most likely to be a series of notes that could be assigned to
a central list of questions.
Cases where I tried to get people to write answers in their own words failed & transcribed
conversations probably would have too much data.
Notes are good because they are in summary form, but bad because not in persons voice.
I kinda wanted to create a sense of the people being hacked for so there would be a
connection between hacker and personality of user.
6. Initial Conclusions:
Further exploration is probably warranted, but it could be hard to make an effective ‘self
service’ digital tool for gathering the data from people
Would need to be quite compelling interface, or people clearly incentivized to participate.
Still good if possible because can achieve more scale.
So maybe coming up with a good digital interface for gathering the info is the main product
challenge.
Interviews are going to gather more useful data but its going to be quite labour intensive and
dependent on a central organizer.
7. Other Observations:
Subject Matter Experts / Reps from Community Organisations
From talking to Noelle from the EDC, Noel for Big Apps, and Jeremy for Code for America it
became clear that information about people & their needs rarely comes directly from the
people to the planners / organisers.
Conclusions are typically presented by reps from organizations who work closely with the
groups in question, or subject matter experts.
Practically speaking it seems important for this product to allow room for input from experts /
reps as a way to summarise problems for user groups that have already been identified.
Archetypal Users
Jeremy mentioned the idea of ‘Archetypal Users’ - identifying people from the research group
(or fabricating them by generalizing some observed trends) who are a good representation of
the likely product user.
Highlighting users like this in detail as a way to summarize bulk research might be a good
practical way to present information.