Fact checking: The impact of data stewardship 

Intern­ship type: Com­mu­ni­ca­tion & case study devel­op­ment 
Institution(s): TU Delft
Dura­tion: 3 months (min­i­mal)
Hours/week: 20 (min­i­mal)
Pre­ferred start date: Feb­ru­ary / March, Sep­tem­ber 2022
Super­vi­sor name & con­tact details:  Yan Wang (Data Stew­ard Coor­di­na­tor, TU Delft) y.wang-16@tudelft.nl 

Project description

The added val­ue of data stew­ard­ship has been wide­ly praised and pro­mot­ed in acad­e­mia. There are sev­er­al reports high­light­ing the progress and achieve­ments on this top­ic, for instance the nation­al coor­di­na­tion of data stew­ard edu­ca­tion in Den­mark, pro­fes­sion­al­is­ing data stew­ard­ship in the Nether­lands, and the year­ly report of TU Delft data stew­ards achieve­ments (2018, 2019, 2020). There are also inspir­ing sto­ries demon­strat­ing exem­plary cas­es of mak­ing data FAIR and its impact. 

When eval­u­at­ing the impact of data stew­ard­ship, peo­ple tend to look for quan­ti­ta­tive mea­sure­ments, such as the num­ber of resolved research data man­age­ment (RDM) requests; num­ber of stu­dents trained; num­ber of pub­lished datasets; dataset cita­tions and down­loads; and more. Whilst these are key met­rics of good RDM and FAIR data prac­tice,  RDM activ­i­ties and chal­lenges encoun­tered in research projects are much more diverse and com­plex. The impact and use­ful­ness of data stew­ard­ship is not lim­it­ed to the afore­men­tioned top­ics, but can be qual­i­ta­tive­ly mea­sured by eval­u­at­ing  var­i­ous issues encoun­tered by researchers and the RDM sup­port requests fre­quent­ly solved by data stew­ards through­out  the entire research process. Unfor­tu­nate­ly, there has not been much inves­ti­ga­tion into  these qual­i­ta­tive insights and the added val­ue of the data stew­ard­ship with­in research insti­tu­tions.

The intern­ship project serves as a ‘fact check’ that aims to col­lect qual­i­ta­tive evi­dence to ver­i­fy  the impact of data stew­ard­ship. The pro­gramme of work  will explore the dif­fer­ent types of RDM chal­lenges that arise dur­ing the research life­cy­cle and the ben­e­fits of data stew­ard­ship. This pro­posed ‘fact-check’ will  also serve as a review and reflec­tion of the data stew­ard­ship regard­ing its scope (e.g. range of data stew­ard­ship roles and respon­si­bil­i­ties), approach (e.g. means and tools that data stew­ards used to tack­le issues), capac­i­ty allo­ca­tion (e.g. resources required to ful­fil the demands from researchers) and ser­vice gap (e.g. new issues that no exist­ing solu­tion avail­able from the stan­dard ser­vices at the uni­ver­si­ty). In addi­tion to quan­ti­ta­tive mea­sures, such qual­i­ta­tive insights could help to design a frame­work for eval­u­at­ing the impact of data stew­ard­ship. 

The intern will liaise with data stew­ards and researchers across all TU Delft fac­ul­ties, and devel­op case stud­ies that: 

• Show­case exam­ples of good RDM prac­tices among researchers from var­i­ous dis­ci­plines.
• Iden­ti­fy the role of data stew­ards in pro­mot­ing open sci­ence and FAIR data prac­tices.
• Cat­e­gorise dif­fer­ent types of sup­port pro­vid­ed by data stew­ards and eval­u­ate their per­ceived added val­ue by researchers.
• Pro­vide essen­tial inputs for the devel­op­ment of the eval­u­a­tion frame­work of data stew­ard­ship

Case stud­ies will be pub­lished as ded­i­cat­ed arti­cles on the 4TU.ResearchData web­site and pub­lished with­in our social media chan­nels (Slack, Twit­ter and LinkedIn) and newslet­ter. The intern will have an oppor­tu­ni­ty to present their work at meet­ings, con­fer­ences and as a peer-reviewed pub­li­ca­tion. 

Prerequisite skills

• Good com­mu­ni­ca­tion and writ­ing skills are essen­tial, and expe­ri­ence of con­duct­ing inter­views is desir­able.
• A goal-ori­ent­ed mind­set is nec­es­sary. The can­di­date is expect­ed to be prag­mat­ic and coop­er­a­tive while think­ing inde­pen­dent­ly. 
• Research expe­ri­ence or famil­iar­i­ty with the research life­cy­cle in science/engineering/design/social sci­ence dis­ci­plines is desir­able.  

Benefits for interns

The intern will: 

• Obtain holis­tic insights into data stew­ard­ship activ­i­ties from an insti­tu­tion­al per­spec­tive.
• Con­nect with  researchers and data stew­ards from dif­fer­ent dis­ci­plines and gain insights into challenges/opportunities of dis­ci­pli­nary data man­age­ment.
• Learn and prac­tice case study devel­op­ment and ser­vice analy­sis skills which are fun­da­men­tal for both research and prac­tice.

How to apply

Please send your CV and cov­er let­ter (in Eng­lish, 2 page max for each) to researchdata@4tu.nl with the sub­ject line ‘4TU.ResearchData Intern­ship Pro­gramme’. In your cov­er let­ter please include your moti­va­tion for apply­ing for this project. Please briefly explain what inter­ests you the most in this project, and feel free to men­tion any­thing par­tic­u­lar that you would like to explore/learn from this project. All appli­ca­tions will be sub­ject to a review process. 

For ques­tions about the project activ­i­ties, please con­tact the super­vi­sor, Yan Wang (y.wang-16@tudelft.nl). For more infor­ma­tion about how to apply, con­tact the com­mu­ni­ty man­ag­er, Con­nie Clare (c.e.clare@tudelft.nl).