Data management use case: a living lab in Kathmandu 

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 

The project aims to cre­ate inclu­sive and resilient dwelling clus­ters for urban reset­tle­ment in Kath­man­du (Nepal) and estab­lish a liv­ing lab mod­el to devel­op trans­par­ent and inte­grat­ed method­ol­o­gy of analy­sis, plan­ning and design of the dwelling clus­ters. In this con­text, the exper­i­men­tal set­up is con­sid­ered as a ‘liv­ing lab’ as it involves con­tin­u­ous inputs from cit­i­zens liv­ing with­in the dwelling clus­ters who help by defin­ing prob­lems and eval­u­at­ing solu­tions. The over­all project is meant to last for a year, but the work described cov­ers only the first step of the project — the ini­tial explorato­ry study per­formed as part of an MSc the­sis over a few months. The results of this step will pro­vide insight into key stake­hold­ers and their roles with­in the social sys­tem being stud­ied. 

This project: 

• Employs a par­tic­i­pa­to­ry plan­ning and design approach, and a sur­vey to map social and spa­tial liv­ing pat­terns of res­i­dents. 
• Sup­ports the inte­gra­tion of mas­ter’s stu­dents in the projects who will con­duct field research for the project. 
• Involves col­lab­o­ra­tion with con­sor­tium part­ners (oth­er uni­ver­si­ty work­ing on dwelling clus­ter, local gov­ern­men­tal agen­cies, and an NGO (Non-Gov­ern­men­tal Orga­ni­za­tion)) as the research out­puts will be used in pilot projects for local urban devel­op­ments (e.g., con­struc­tion projects). 

Research data man­age­ment con­sid­er­a­tions 

Data col­lec­tion and stor­age: 

Var­i­ous types of data are col­lect­ed and processed by the research team. There may be a dis­tinc­tion between the data that will be used for research analy­sis (research data) and the data that will be required for project (admin­is­tra­tion data). In this project, research data includes geospa­tial data (such as drone images, maps and his­tor­i­cal land sur­vey data) and the inter­view data (such as audio record­ings, notes and inter­view tran­scripts). Admin­is­tra­tive data includes con­tracts and agree­ments between the research team and local gov­ern­ment agen­cies; and agree­ments between the research team and local cit­i­zens. The con­tracts between par­ties should exist pri­or to the start of the project and be acces­si­ble to all par­ties. The col­lec­tion of informed con­sent from cit­i­zens which com­prise per­son­al­ly iden­ti­fi­able infor­ma­tion and, there­fore, requires adher­ence to GDPR and pri­va­cy reg­u­la­tions will have to be stored care­ful­ly as well. 

Field work in remote loca­tions can bring chal­lenges for secure data stor­age, par­tic­u­lar­ly if a reli­able inter­net con­nec­tion is unavail­able. Inter­views are record­ed using a tape recorder (or sim­i­lar inter­nal mem­o­ry), the man­age­ment of the tapes and trans­fer of the infor­ma­tion onto dig­i­tal stor­age is out­lined in the pro­jec­t’s data man­age­ment plan. Sev­er­al lev­els of data shar­ing are required to enable data access by the research team, local gov­ern­ment agen­cies and con­sor­tium part­ners. It is expect­ed that the research out­comes will be shared with all stake­hold­ers involved but the raw data (interview/personal infor­ma­tion) will not be shared beyond the research team. 

Key con­sid­er­a­tions on data col­lec­tion and stor­age:

• Sen­si­tive per­son­al data should be col­lect­ed and stored using ded­i­cat­ed secure devices. 
• Per­son­al data that can be made (pseudo)anonymous is made so as ear­ly as pos­si­ble. 
• A secure stor­age loca­tion should be acces­si­ble by the research team and exter­nal part­ners (e.g. an insti­tu­tion­al cloud stor­age solu­tion). 
• Access con­trol should be man­aged by the research team so that rel­e­vant stake­hold­ers are grant­ed access to rel­e­vant research data at spe­cif­ic times under suit­able pri­va­cy reg­u­la­tions. 
• Some admin­is­tra­tive data, such as informed con­sent, may only be accessed by mem­bers of the research team. 
• Per­son­al data should not be shared beyond the research team; only aggre­gat­ed data should be shared. 
• Research out­puts are dis­sem­i­nat­ed via the project website/blog. 

Ethics 

Since res­i­dents par­tic­i­pate in this research there are var­i­ous eth­i­cal con­sid­er­a­tions. Par­tic­i­pants may belong to ‘risk’ pop­u­la­tions due to their social-eco­nom­ic sta­tus. The research team decid­ed that Ind­vid­ual par­tic­i­pants must remain as anony­mous as pos­si­ble dur­ing the research process — par­tic­i­pants were not invit­ed to dis­close their iden­ti­ty. As this research is con­duct­ed in a for­eign coun­try (Nepal), we can­not expect all par­tic­i­pants to speak the same lan­guage as the Euro­pean research team. Spe­cif­ic arrange­ments must be put in place to guar­an­tee that the inter­vie­wees can pro­vide informed con­sent. The researchers must inform the par­tic­i­pants about the pur­pose and the exper­i­men­tal pro­to­col they will par­tic­i­pate in (includ­ing data man­age­ment), as well as the par­tic­i­pants’ rights in a lan­guage that is clear and under­stand­able (Nepali and/or Eng­lish). It may be that par­tic­i­pants are not able/willing to sign forms, nor pro­vide their real names. The pro­ce­dure for col­lect­ing informed con­sent should be out­lined and reviewed by the appro­pri­ate ethics com­mit­tee, includ­ing the poten­tial use of alias­es. 

Key con­sid­er­a­tion on ethics: 

• Apply for eth­i­cal approval/advice ear­ly — as the com­plex set-up of the project (type of col­lect­ed data, informed con­sent, impli­ca­tions on deci­sion mak­ing for the com­mu­ni­ties involved, dura­tion of the project, etc.) might require fur­ther reviews. 
• Informed con­sent doc­u­ments must always be under­stand­able by par­tic­i­pants — when work­ing abroad, lan­guage bar­ri­ers must be con­sid­ered. 

Pri­va­cy & legal aspects 

This project involves the col­lec­tion and pro­cess­ing of diverse types of sen­si­tive per­son­al data, such as geo­graph­ic loca­tion of cit­i­zens, house­hold com­po­si­tions, finan­cial infor­ma­tion, and health con­di­tions. If this is the case, the con­sent doc­u­ments must men­tion them clear­ly. To share this sen­si­tive data with local project part­ners locat­ed in a coun­try out­side of the Euro­pean Eco­nom­ic Area (EEA), a data trans­fer agree­ment is required. This comes in addi­tion to com­ply­ing with insti­tu­tion­al poli­cies, Euro­pean data pro­tec­tion laws (GDPR) and local pri­va­cy laws. Giv­en the sen­si­tiv­i­ty of the data, and its per­son­al nature, the research team must keep track of their data pro­cess­ing (GDPR require­ment). The eas­i­est way to do so is to describe the expect­ed process in a data man­age­ment plan (DMP) before the project starts and request feed­back from the sup­port team (Pri­va­cy team, and data sup­port team) to ensure the ini­tial plan is ade­quate. Should the solu­tion be adjust­ed as the project goes along, the DMP should be updat­ed, and changes should be reviewed by the rel­e­vant team. 

Key con­sid­er­a­tions on pri­va­cy and legal aspects: 

• Usu­al­ly, mas­ter’s stu­dents own the copy­right on their work. This, in com­bi­na­tion with their par­tic­i­pa­tion in larg­er projects, where own­er­ship is out­lined in con­sor­tium agree­ments, or oth­er project doc­u­ments, may cre­ate ten­sion regard­ing the own­er­ship of the out­put. Make sure all admin­is­tra­tive doc­u­ments fram­ing the project regard­ing data shar­ing and own­er­ship are acces­si­ble and read by all project mem­bers. 
• As the research out­puts will be used in pilot projects for local urban devel­op­ments (e.g., con­struc­tion projects), Intel­lec­tu­al Prop­er­ty Rights (IPR) should be spec­i­fied and approved by con­sor­tium part­ners. 
• Fol­low trav­el­ling advice from your insti­tu­tions 
• Check with legal advi­sor and con­tract man­ag­er regard­ing the inclu­sion of mas­ter’s stu­dents’ involve­ment in a research project. 

Acknowl­edge­ment: this use case was writ­ten joint­ly by data stew­ards from TU Eind­hoven, Uni­ver­si­ty of Twente, and TU Delft. We would like to thank Con­nie Clare, for her help with the prepa­ra­tion, the data stew­ards of the uni­ver­si­ties who con­tributed to the use case. Mem­bers of the pri­va­cy and ethics of the uni­ver­si­ties did pro­vide their input on this use case.