Waving Not Drowning Practical Tips for staying on Top of Photo Field Data

1. Waving Not Drowning Practical Tips for staying on Top of Photo Field Data EPIC Conference Workshop, 25th September 2006 Jan Chipchase Nokia, Mobile HCI Group NOKIA

2. Attendees / Contributors • Anjali Kelkar Illinois Institute of Technology • Laura Forlano Communications, Columbia University • Divya Jindal, Microsoft • Dionne Smith Brand Trust • Todd Wilkens Adaptive Path • Roland Moore Pacific Institute for Research and Evaluation • Jan Chipchase Nokia Mobile HCI Group, Tokyo • Roberto Holguin in/situm, Mexico • James Beebe Gonzaga University , Spokane • Kathi Kitner Intel People & Practices Group NOKIA

3. Why Are We Here? • Field studies can involve multiple team members generating thousands of digital images. How do you move from photo data sitting unused and unloved on multiple hard-disks to being a valued, relevant resource? • This workshop will cover how to: • Collect, manage and stay in control collections of thousands of photos • Maintain data integrity • Consider moral & legal requirements • Ensure that relevant data is easy to retrieve and use • All within real-world constraints (i.e. running a field project, lack of sleep, intermittent power, crashing hard disks, buggy software, sullen subcontractors, etc.) NOKIA

4. Additional Topics to Cover • How to store data? • How to share? Within groups? • Structure way of re-visiting data? • How to notate photos? • Process for taking photos… pros and cons of different types of camera… • User identity, degrees of anonymisation • Quality: resolution, composition • What makes a good ethnographic image? • How to select what images to use for reporting? • When to delete? What to delete? • Backup strategies? • Photos in storytelling? NOKIA

5. Software PC • Irfanview (shareware) good for keyboard shortcuts, rapid image editing, and batch changes • Adobe Elements (buggy, slow on laptop, good for setting up subcontractors to work in a hurry) • Picasa (freeware) • Qualitative data analysis • ATLAS.ti (able to annotate selected parts of images) • Nvivo 7 Mac • iPhoto • Image Capture • Photoshop • Online • Flickr (good for key word tagging) • Shutterfly NOKIA

6. The Challenge right data right format right person right time How does this affect how we collect and manage the data? NOKIA

7. Sample Field Study • 10 days in one location • 6 team members • Varying graphics skills • Range of equipment – pc, macs, camera brands • Internal, external subcontractors • Everyone has their preferred ways of doing things • 20+ study participants • Participant diaries • Variety of data collection methods – shadowing, in-depth interviews, diaries, observations, wallet mapping, disposable camera studies, online blogs, Flickr photo diaries >> differing privacy requirements NOKIA

8. NOKIA

9. Collect, Manage & Make Use of Photo Data Data from various sources Usable collections 1024 x 768 Presentations, web, email Original size Print Backup NOKIA

10. Institutional Review Board (IRB) • IRBs are also known as Committees for the Protection of Human Subjects • Formal vs informal • Age • Different levels of vulnerability seen for minors, with more protections needed • An element of rear covering! • But actually a degree of flexibility when engaged – an educational process for IRB members and applicant alike NOKIA

11. The Process

12. Before We Get Started • Camera setup • Time & date Nikon world time • Sequential vs. restart • File naming • Folders • Image resolution >> sufficient but not more • Adding contact information inside memory • Storage setup • Folder naming • Memory cards: process me >> empties • Data manager >> someone to take overall responsibility for photo processing NOKIA

13. Camera Equipment Good for ethnographic–style work: • Good quality display for showing participant’s photos • Small enough to carry anywhere • Steady shot • Good zoom • Video good enough for presentations • Responsive refresh times more time taking photos than waiting for camera to charge up • Rapid on • Rotating head supports more subtle photography • Disable flash • Night vision (Sony F717 pretty good, Sony F828 Using • SLR’s, compacts, minis, camera phones, disposable, Polaroid NOKIA

14. Consent • Data Consent • USA Example • UK Example • India Example • Photo ownership, rights separate from Data Consent • Different rights according to how the photo is used • What does it mean to ‘sell’ an photo? • Sold to magazine • Appears on a web site that accepts adverts? • On a web site? • Used in a paid-for workshop at a conference? • Model consent • Consent to use photos featuring people NOKIA

15. Data Consent Low Literacy Users NOKIA

16. Process Multiple Sources Team, participants NOKIA

17. Keeping Participants in Control • Sufficiently aware of data collection process • Asking permission prior to starting data collection • Asking permission again in new privacy-breaching situations • De-mystify equipment • Allow participants to frame photos • Rewards before data consent is signed • Encouraged to delete any or all digital data • Send participants a copy of the data post-study • Print or digital NOKIA

18. Process Multiple Sources Team, participants Backup ‘Data Manager’ NOKIA

19. Secure Backup NOKIA

20. Process Multiple Sources Team, participants Backup Clean up, filtering, basic metadata, re-naming ‘Data Manager’ Working duplicates to team, clients, stakeholders NOKIA

21. Basic Metadata • Sufficient metadata to make sorting easier later on • Photographer • Study • Location • Participant • Data gathering method • + NOKIA

22. Photos As Metadata NOKIA

23. Filtering Filtering NOKIA

24. Filtering NOKIA

25. Naming, Re-Naming • Naming strategies • projectname-location-participant-method-uniquenumber • optima-helsinki-f12-interview-001.jpg • optima-hki-f12-ini-001.jpg • optima-hki-f12-001.jpg • optima-hki-001.jpg >> Demo: batch re-naming NOKIA

26. Process Multiple Sources Team, participants Backup Clean up, filtering, basic metadata, re-naming Working duplicates to team, clients, stakeholders ‘Data Manager’ Collections, detailed metadata Collections NOKIA

27. Collection • Personal favourites • Themes • Detailed metadata • Things to watch out for NOKIA

28. Process Multiple Sources Team, participants Backup Clean up, filtering, basic metadata, re-naming Working duplicates to team, clients, stakeholders ‘Data Manager’ Collections, detailed metadata Collections 1024 x 768 Presentations, web, email Original size Print Backup NOKIA

29. Batch Processing • Versions • Collections • Writing metadata to files • Awareness of who has what data • Data clean up >> delete, delete, delete NOKIA

30. Use & Reporting • Process optimised for digital publishing • Photo-rich Power point & PDF • Web • Archive • Email attachments >> naming • NXPowerLite • For compressing presentations NOKIA

31. Typical No-Stress Volumes Multiple Sources Team, participants 6,000 photos 6,000 Clean up, filtering, basic metadata, re-naming 1,500 ‘Data Manager’ Collections, detailed metadata 400 + 50 + … Collections 1024 x 768 Presentations, web, email Original size Print Backup NOKIA

32. Full Circle: Returning Data To Participants Multiple Sources Team, participants Clean up, filtering, basic metadata, re-naming ‘Data Manager’ Collections, detailed metadata Collections 1024 x 768 Presentations, web, email Original size Print Backup NOKIA

33. Process Recap Multiple Sources Team, participants Backup Clean up, filtering, basic metadata, re-naming Working duplicates to team, clients, stakeholders ‘Data Manager’ Collections, detailed metadata Collections 1024 x 768 Presentations, web, email Original size Print Backup NOKIA

34. /learn to swim /end NOKIA