Establishing best practices to improve usefulness and usability of web interfaces providing atmospheric data

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Establishing best practices to improve usefulness and usability of web interfaces providing atmospheric data.

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  • GROWING audience of climate data

    Not climatologists, meteorologists

    Obligation to provide
  • very often have to build page though not web designers
  • easy to check out on Amazon

    Lots of research into that

    We want same for climate
  • If you can demonstrate loyal following, it may inspire funding agencies to support you
  • Page visits follow Weibull distribution– “time to failure” concept in engineering/usability.

    2 kinds: positive aging– longer it is in service more likely to fail.

    negative aging– more time it is in service, less likely it is to fail.

    Page visits exhibit negative aging.

    Hopefully get loyal users
  • *general guidelines to be described later in presentation
  • 1 of 8 CSCs that were established by DOI to deliver state-of-the-art climate research.

    ACIS- daily fines res.
    station, gridded.
    temp, precip vars

    Not WRCC
  • what are some basic things people might want to do on this site? Test several applications
  • what are some basic things people might want to do on this site? Test several applications
  • what are some basic things people might want to do on this site? Test several applications
  • In perfect scenario, wireframing of page before first line of code

    We learned about usability after starting this project
  • what are some basic things people might want to do on this site? Test several applications
  • User clicks on a link trying to access data and text (metadata) is displayed.
    Thinks clicking on the text will get him to data
    This info was reduced and put into a mouseover popup box, original spot he clicked leads to data
    Users in round 2 did not have this issue.
  • note change in qmarks
  • Only 1 time in first round when people really used help We changed color and size of
  • Give example of how users had trouble with station finder, thought it would give data.
  • STOP early
    User sees dropdown menu (a chrome browser function) meant to indicate autofill.
    It looks like a dropdown menu, but is not. the user’s choices aren’t available so frustrating
    Note that only the county number is shown in the field. Once we put both station name and number in as well as removed arrow, all users recognized that autofill available.
  • what are some basic things people might want to do on this site? Test several applications
  • what are some basic things people might want to do on this site? Test several applications
  • Note: these are from questions asked after testing
  • background: user asked to find data from DEC 2013. Thinks it is relatively current, looks at a dashboard that provides “current climate information”
  • background: user asked to find highest temperature recorded in Elko in March. Tries to use data lister and enter in “March” or POR
  • Establishing best practices to improve usefulness and usability of web interfaces providing atmospheric data

    1. 1. Establishing best practices to improve usefulness and usability of web interfaces providing atmospheric data Nina S. Oakley Britta Daudert
    2. 2. Atmospheric data are increasingly important to a broad audience Resource Managers Ecologists Social ScientistsPublic Health Officials Policy Makers Farmers Educators Hydrologists Geologists Engineers
    3. 3. Web has become favored way to disseminate atmospheric data
    4. 4. Data can be frustrating to access I just want to download a year of data for Reno Airport... what do I click?
    5. 5. Usability addresses this issue • Developed from e-commerce needs (for web) • “The extent to which a web product can be used to achieve goals with effectiveness, efficiency, and satisfaction.” (ISO, 2014) • Focuses on user rather than developer needs • Assumes users are busy people trying to accomplish tasks • Users (not developers) decide whether a product is easy to use (Dumas & Redish, 1999)
    6. 6. Why is usability important to atmospheric science? • Often many sites to access same data • Users have “reservoir of goodwill”, leave site if frustrated • E-commerce: loyal users spend more money than first- time users (Nielsen, 2000) • Loyal following = funding? • Usability testing relatively cheap! Krug, 2005
    7. 7. Time spent on site before leaving Nielsen, 2011 • Users leave web pages in ~10-20 seconds • Make clear, strong value proposition to get them to remain longer
    8. 8. How to employ usability? • Follow general usability guidelines • literature, usability.gov • Perform usability testing on your site • We attended training • nngroup.com
    9. 9. Site tested: SCENIC Southwest Climate ENvironmental Information Collaborative • wrcc.dri.edu/csc/scenic • Serves researchers in DOI SW-CSC • Interface to ACIS database
    10. 10. SCENIC allows for customizable queries, analyses List data (several formats) Create summaries, perform statistical analyses
    11. 11. SCENIC creates high-resolution graphics
    12. 12. Methods: Usability lab • Choice of Mac or PC, any browser • Facilitator works with participant • Camtasia software for screen recording Krug, 2005
    13. 13. Methods: Recruiting participants • 5 participants uncover 80% of usability issues Nielsen 2000, 2012
    14. 14. Methods: Recruiting participants • Performed 2 rounds of testing with 5 participants • Made improvements between rounds • Test representatives of target user group • Not necessarily your colleague down the hall • Sought people in ecology, resource management • Compensate participants! • Provides motivation to show up, give quality feedback
    15. 15. Methods: Designing test questions • PART 1: Online, 3 Tasks • 1) List data for all stations in Shasta County, CA that recorded snowfall and precipitation data for all dates December 15-December 31, 2013 • 2) Find the highest temperature ever recorded in March at Winnemucca AP, Nevada • 3) Find the lowest minimum temperature among grid points approximately covering Pyramid Lake in December 2013
    16. 16. Methods: Designing test questions • PART 2: Written, Standardized Usability Scale (SUS) • Standard usability test, results interpreted based on large number of usability studies • Produces valid results on small sample sizes (Brooke, 1986; Bangor 2009) • 10 questions, Likert-style scale– 5 choices between agree strongly/disagree strongly • Gives a score or “grade” to the usability of a site
    17. 17. Methods: Designing test questions • PART 3: Verbal, 7 Questions • Questions on interpretation of common terms used in climate data (raw data, tool, product, climate anomaly map, etc) • Card sorting activity to inform on how people search for climate data (where, when, what, type, source) • General questions, discussion about site
    18. 18. Methods: Researching general usability guidelines • Overall goal: reduce cognitive load on user • No need to reinvent wheel (in most cases) • Not specific to climate data, web pages in general Krug, 2005
    19. 19. Methods: Researching general usability guidelines • Adhere to web conventions • Navigation along top of page, links recognizable, search bar in upper right or left, ?=help
    20. 20. Example: User expected links, got text
    21. 21. Methods: Researching general usability guidelines • Be consistent within pages • Color scheme, formatting, layout same throughout SCENIC • Navigation menu always available • Provide help texts • However, most users muddle through first
    22. 22. Example: Help texts help!
    23. 23. Methods: Researching general usability guidelines • Hide unnecessary options • Make labels clear and meaningful • was much more successful that “submit” • Page headings match link name
    24. 24. Example:Autofill mistaken for dropdown menu; getting users to recognize autofill
    25. 25. • Round 1: • Mean = 63 • Round 2: • Mean = 67.5 Results: How did participants rate SCENIC?
    26. 26. Results: How did participants rate SCENIC? • Round 1: Mean = 63 • Round 2: Mean = 67.5 Somewhere between “OK” and “Good” Bangor et al. 2009
    27. 27. Results: How participants search for data • N = 14 (15 participants, 1 abstaining) to meet requirements for significant results (Tullis and Wood, 2004) • WHERE (location) most important, SOURCE (originator of data) least important
    28. 28. Results: Labeling Challenging • Gridded or modeled data? • All gridded data here modeled, not observed • Participants found gridded “more descriptive and useful” • Climate anomaly maps and time series? • Participants agreed on, liked these names Time Series Climate Anomaly Map
    29. 29. Example: Labeling
    30. 30. Results: Labeling Challenging • Tool and product misleading • General agreement “tool” manipulates data, “product” static • Term “Data Tools” did not illicit desired response, changed to “Data Analysis” • Raw data • Some thought had QC applied, some not • Used “Data Lister” • “Historic” data • Confusing, replaced with “Data Lister”
    31. 31. Example: Confusion about historic vs. current data
    32. 32. Results: Biggest challenge • Getting participants to utilize data analysis tools • Want to list data first– all participants! • Some say they would do analysis themselves • Are analysis tools valuable for this audience? • How to motivate people to know they are available? Analysis Tools Data Lister
    33. 33. Example: Muddling and listing data
    34. 34. Conclusions • Usability testing extremely valuable • Applies to SCENIC and future projects • Removed many issues on site • Learned about how people use web • Still improvements to be made • Testing informs on issues, not always clear how to solve • Usability is challenging!
    35. 35. Conclusions- Recommendations • Perform testing early and often • Work with target audience • Consider the way your audience searches for atmospheric data • Naming/labeling most challenging task • Test names on participants, compare with other agencies • Adhere to general usability guidelines • Usability.gov; Krug, 2005, Don’t Make Me Think good places to start
    36. 36. Moving Forward • Broad survey on how people look for climate data • Standardization of terms (labels) across agencies • Interpretation of atmospheric data • Research what help tools are most effective • video, forums, text, tutorials • Other groups in atmospheric science share usability testing results
    37. 37. Thank you! World Usability Day is coming up! November 13 2014 This project was supported by DAS EDGES 2013

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