Data management case: Design of working/living environment

Dis­claimer: The use case pre­sent­ed below is inspired by a real-world study, in which research teams faced spe­cif­ic data-relat­ed chal­lenges from a storage/processing per­spec­tive, pri­va­cy and com­pli­ance with GDPR point of view, or eth­i­cal con­sid­er­a­tions and insti­tu­tion­al eth­i­cal review.  We hope this case-study will pro­vide you with insight into what may be required for your own work and trig­ger inter­est­ing dis­cus­sions on such key aspects of research activ­i­ties. How­ev­er, the advice pro­vid­ed here should not be direct­ly applied to any oth­er research project. Please con­sult with rel­e­vant experts in your insti­tu­tions.

Project background

Due to the 2019/2022 pan­dem­ic, more peo­ple start­ed work­ing from home. This project aims to iden­ti­fy key ele­ments in a com­bined working/living envi­ron­ment (hybrid space) and to sug­gest cus­tomized designs for dif­fer­ent user groups — based on the type of activ­i­ties and hybrid space con­di­tions. The research team will start by observ­ing how peo­ple adjust­ed their “work-at-home” envi­ron­ment by gath­er­ing infor­ma­tion that peo­ple shared on social media. This ini­tial phase enables them to iden­ti­fy the most inter­est­ing cri­te­ria for achiev­ing a bal­anced hybrid work envi­ron­ment. The team then recre­ates sev­er­al 3D test envi­ron­ments using a vir­tu­al real­i­ty envi­ron­ment, allow­ing par­tic­i­pants to “expe­ri­ence” their new­ly cre­at­ed hybrid space. The team iter­ates and improves the test designs through col­lab­o­ra­tive ses­sions with fel­low researchers and stu­dents from their insti­tu­tions, who par­take in Vir­tu­al Real­i­ty (VR) test tri­als. Each par­tic­i­pant is engaged in mul­ti­ple dis­cus­sions regard­ing the ini­tial and enhanced iter­a­tions of the design. Once the team has iden­ti­fied sev­er­al inter­est­ing hybrid space setups for remote work, they would like to get the opin­ion of the non-aca­d­e­m­ic part of the pop­u­la­tion. To this end, they invite groups of peo­ple (5 to 10) to spend a few hours in their lab to test the envi­ron­ment using a VR head­set and col­lect feed­back from the group on each select­ed design.

Research data man­age­ment con­sid­er­a­tions

Data collection and storage

The data col­lect­ed dur­ing this exper­i­ment is sum­ma­rized below:

• Images obtained from social media plat­forms (Insta­gram and sim­i­lar), the prove­nance of each image will be not­ed to facil­i­tate the iden­ti­fi­ca­tion of asso­ci­at­ed licens­es and copy­right notices in the future.
• The inter­views to refine the designs and the focus group feed­back will be record­ed, includ­ing audio and/or video record­ing.
• The VR envi­ron­ments are also part of the data pro­duced dur­ing the project.

Once the study is com­plet­ed, the research team intends to make all sup­port­ing data avail­able. This includes reports on the design refine­ment process (inter­views), the assess­ment by peo­ple (focus groups) and the vir­tu­al envi­ron­ment and its asso­ci­at­ed pub­lic source of inspi­ra­tion (images from social media). Final­ly, the research team wants to show how the envi­ron­men­t’s test­ing took place using pic­tures of the ses­sions. There­fore, the research group will have to ensure:

• The preser­va­tion of proof of con­sent from all par­tic­i­pants who agreed to use their image as part of pub­li­ca­tion (in pictures/videos).
• The safe­keep­ing of the list of par­tic­i­pants, as the team needs to keep track of who reviewed which design.

In facil­i­tat­ing data shar­ing regard­ing par­tic­i­pants’ input on the designs, the research team will sum­ma­rize the dis­cus­sions dur­ing the inter­views and focus groups, focus­ing only on the appre­ci­a­tion of the hybrid work­spaces. The sum­maries will be sent to the rel­e­vant par­tic­i­pants for review before pub­li­ca­tion. It is decid­ed that it will not be pub­licly avail­able if the rel­e­vant par­tic­i­pant does not explic­it­ly approve the sum­ma­ry.

The team will also acquire video and image edit­ing tools to blur and hide participant’s face in videos and pic­tures. This will increase the amount of mate­r­i­al they can share with­out jeop­ar­diz­ing the participant’s anonymi­ty.

At the end of the exper­i­ment, the team intends to share the “opti­mal” hybrid work­space design pub­licly. These designs are “unusu­al” research data, requir­ing more infor­ma­tion from the copyright/legal sup­port team to copyright/licensing on such out­put.

Addi­tion­al­ly, the team would like to share the designs found on social media to pro­vide infor­ma­tion on how those designs came to be and used as an inspi­ra­tion for the new designs. This amounts to a pub­lic dis­play of designs obtained from a third par­ty.

Key con­sid­er­a­tions on data col­lec­tion and stor­age:

• For this project, any insti­tu­tion­al­ly approved stor­age for per­son­al data is suf­fi­cient. No spe­cif­ic addi­tion­al secu­ri­ty mea­sures are required. The prin­ci­pal inves­ti­ga­tor may fol­low the gen­er­al rules and reg­u­la­tions of their insti­tu­tion.
• Two types of per­son­al data should be clear­ly dis­tin­guished in both the DMP (Data Man­age­ment Plan) and the stor­age solu­tion itself:
• The per­son­al admin­is­tra­tive data col­lect­ed to orga­nize the exper­i­ments (par­tic­i­pant lists, con­sent forms…).
• The per­son­al research data that they wish to use in analy­sis and to pro­duce pub­li­ca­tions (demo­graph­ic infor­ma­tion: age range, domain of activ­i­ty, audio record­ing, tran­scrip­tions)
• The project is han­dled by a sin­gle research group, lim­it­ing the need for data shar­ing dur­ing the project. The research team must ensure that only rel­e­vant project mem­bers have access to the project data.
• Data shar­ing will occur dur­ing archival when the results are pub­licly avail­able through a research data repos­i­to­ry and pub­li­ca­tions.
• The research team will have to keep track of the prove­nance of images col­lect­ed on social media to ensure that their usage for the project does not vio­late licens­es or copy­right laws.

Ethics

While infor­ma­tion is being col­lect­ed from human par­tic­i­pants, the need for per­son­al infor­ma­tion is lim­it­ed (age range, work habits at home/ the office, edu­ca­tion lev­el, opin­ion about the designs). The use of per­son­al infor­ma­tion for admin­is­tra­tive uses includes organ­is­ing focus group ses­sions and track­ing par­tic­i­pa­tion in the V.R. part of the exper­i­ment.

How­ev­er, VR exper­i­ments are known to cre­ate dis­com­fort for some peo­ple (nau­sea, ver­ti­go, dizzi­ness), and par­tic­i­pants must be warned. Addi­tion­al­ly, par­tic­i­pat­ing in a VR exper­i­ment may require par­tic­i­pants to come on-site, which in pan­dem­ic times requires spe­cif­ic atten­tion.

In gen­er­al, research with human par­tic­i­pa­tion requires ethics review, but addi­tion­al­ly, for some insti­tu­tions, the use of 3rd par­ty mate­r­i­al from social net­works can be sub­ject to an eth­i­cal review as well — because we are indi­rect­ly inter­act­ing with peo­ple through their online con­tri­bu­tions.  In any case, the usage of pic­tures or oth­er mate­r­i­al col­lect­ed on the Inter­net is sub­ject to spe­cif­ic copy­rights, which will have to be fol­lowed.

Key Con­sid­er­a­tions on Ethics

• Vir­tu­al Real­i­ty exper­i­ment expos­es par­tic­i­pants to spe­cif­ic risks. Check exist­ing con­sent forms regard­ing V.R. exper­i­ments, as dis­com­fort with such tools is fre­quent.
• Anony­mous summaries/reports of inter­ac­tions can be sent to the par­tic­i­pants to ensure that they are aware of what will be report­ed about their activ­i­ties. The research team will keep track of the ini­tial con­sent (to par­tic­i­pate in the exper­i­ment) and the con­sent to pub­lish the anony­mous sum­ma­ry of their par­tic­i­pa­tion in the interview/focus group.
• This study is per­formed at a time when COVID-19 is still active. Par­tic­i­pat­ing in activ­i­ties relat­ed to VR head­sets implies on-site pres­ence. Par­tic­i­pa­tion must then be vol­un­tary, and par­tic­i­pants who feel dis­com­fort must be allowed to leave. Addi­tion­al­ly, the research team must abide by cur­rent safe­ty reg­u­la­tions (ventilation/space and such).

Privacy and legal aspects

Spe­cif­ic atten­tion must be giv­en to audio record­ings of inter­views and focus groups and the stor­age of signed informed con­sent forms, which con­tain per­son­al­ly iden­ti­fi­able infor­ma­tion about the par­tic­i­pants. Pub­li­ca­tion of images of par­tic­i­pants in V.R. gear in com­bi­na­tion with audio record­ings could make the par­tic­i­pants iden­ti­fi­able.

To ensure that designs and research data do not pose copy­right or licens­ing issues, researchers are rec­om­mend­ed to keep track of the prove­nance (web­site, URLs…) of the data (images, user com­ments, rat­ings, and so on they col­lect online to facil­i­tate license retrieval. The team should keep track of the URL of the data and the URL of the asso­ci­at­ed copy­right and pri­va­cy notice. This will ease the work of the IP/Copyright sup­port team. Addi­tion­al­ly, researchers must ensure that they abide by the licens­es under which the 3rd par­ty mate­r­i­al used in this research was made avail­able for pub­lic use.

Key con­sid­er­a­tions on pri­va­cy and legal aspects:

• As always, the researchers should check the insti­tu­tion­al pri­va­cy guide­lines.
• It is advised to seek legal advice to guar­an­tee that data col­lect­ed from social media can be used for research pub­li­ca­tion. Unless the research team is famil­iar with such process­es, advice from the insti­tu­tion’s privacy/legal team is required.
• To ensure prop­er reuse of exist­ing con­tent and legal pro­tec­tion for the cre­at­ed con­tent, advice from the copy­right team is required here.
• Should the research team want to use images of par­tic­i­pants using the VR head­set to sup­port pub­li­ca­tions or in pre­sen­ta­tion, the research team must ensure that they have the appro­pri­ate proof of con­sent from the par­tic­i­pant.
  
  

Acknowl­edge­ment: this use case was writ­ten joint­ly by data stew­ards from TU Eind­hoven, Uni­ver­si­ty of Twente, and TU Delft. We would like to thank the data stew­ards of these uni­ver­si­ties who con­tributed to the use case.