Site icon 4TU.ResearchData

4TU.ResearchData’s First Community Call | Building a Culture of Collaboration

On Fri­day 30th April, we host­ed our first com­mu­ni­ty call based on the theme:
‘Build­ing a Cul­ture of Col­lab­o­ra­tion’.

The one-hour long event brought 30 atten­dees togeth­er from eight research insti­tu­tions to cel­e­brate the six month anniver­sary of the 4TU.ResearchData com­mu­ni­ty and learn about build­ing a cul­ture of col­lab­o­ra­tion.

The event show­cased high­lights from com­mu­ni­ty mem­bers; updates about the com­mu­ni­ty-led work­ing groups; and, an inspi­ra­tional keynote talk from The Tur­ing Way Com­mu­ni­ty Lead, Malvi­ka Sha­ran.

📥 Down­load the slides from the event and watch the record­ing!

https://community.data.4tu.nl/wp-content/uploads/2021/05/4TU.ResearchData-_-The-first-community-call-20210430_103225-Meeting-Recording-1.mp4

Community Highlights: Value for members  

The aim of the com­mu­ni­ty is to pro­vide an inclu­sive space for mem­bers to con­nect and exchange knowl­edge and ideas about the best prac­tices for the cre­ation and reuse of FAIR data

Since the com­mu­ni­ty was ini­ti­at­ed in Octo­ber 2020, we have wel­comed more than 60 researchers and data sup­port­ers to the com­mu­ni­ty plat­form and Slack work­space. Here’s some of the feed­back we received from com­mu­ni­ty mem­bers when we asked them about their per­son­al high­lights and expe­ri­ences…

Updates from the community-led working groups   

In Jan­u­ary, the com­mu­ni­ty estab­lished three month­ly work­ing groups for data stew­ards and oth­er data sup­port­ers from the 4TU part­ner insti­tu­tions (TU Delft, TU/Eindhoven and the Uni­ver­si­ty of Twente). 

The aim of the work­ing groups is to pro­vide a sup­port net­work for the data stew­ards and cre­ate oppor­tu­ni­ties for them to dis­cuss and learn about impor­tant top­ics relat­ed to research data man­age­ment. The expec­ta­tion is that co-devel­op process­es and doc­u­men­ta­tion that can be scaled up and imple­ment­ed across the 4TU.ResearchData part­ner and mem­ber insti­tu­tions.

FAIR and Reproducible Code:
Train the Trainer sessions  

Nico­las Dintzn­er kicked off the round of work­ing group updates by report­ing on the progress made by the FAIR and Repro­ducible Code work­ing group. This work­ing group is focused on how data stew­ards can empow­er researchers to cre­ate FAIR soft­ware through train­ing and sup­port. 

Dur­ing meet­ings, group mem­bers share expe­ri­ences about the best prac­tices for writ­ing FAIR and repro­ducible code.

So far, the group has dis­cussed how tools, inte­grat­ed devel­op­ment envi­ron­ments (IDEs), ver­sion con­trol, writ­ing and test­ing, doc­u­men­ta­tion, col­lab­o­ra­tion, licens­ing, and shar­ing and archiv­ing of code can be used to improve code man­age­ment and qual­i­ty. 

Ear­ly group dis­cus­sions revealed that mem­bers have dif­fer­ent skill sets when it comes to writ­ing and man­ag­ing code. There­fore, the next step is to organ­ise ‘train the train­er’ ses­sions where data stew­ards can learn from one anoth­er in a sup­port­ive envi­ron­ment. Dur­ing these ses­sions, the more advanced mem­bers will teach the less advanced mem­bers the nec­es­sary skills to sup­port researchers with code man­age­ment. 

Train­ing ses­sions will start in June this year using the ‘Best prac­tices for writ­ing repro­ducible code’ course mate­r­i­al devel­oped by Barabara Vreede at Utrecht Uni­ver­si­ty.

Privacy and GDPR:
A comparison of institutional workflows

San­tosh Ilam­paruthi fol­lowed with a pre­sen­ta­tion about the Pri­va­cy and GDPR work­ing group, a col­lab­o­ra­tion that focus­es on pro­vid­ing advice for researchers about the appro­pri­ate han­dling of per­son­al or com­mer­cial­ly sen­si­tive data. 

In order to under­stand the roles and respon­si­bil­i­ties of data stew­ards at 4TU.ResearchData part­ner insti­tu­tions in help­ing researchers to achieve pri­va­cy and GDPR com­pli­ance, the group has recent­ly under­tak­en a ‘gap analy­sis’ to com­pare insti­tu­tion­al work­flows and iden­ti­fy top­ics for fur­ther dis­cus­sion. 

Select­ed top­ics were ‘data access’, ‘data trans­fer’ and ‘data anonymi­sa­tion’. Pro­posed out­puts of this work­ing group include:

Engagement and Education:
Disciplinary guides about data management 

The focus of the Engage­ment and Edu­ca­tion work­ing group is to exchange and syn­the­size efforts relat­ed to data man­age­ment train­ing for dif­fer­ent audi­ences across the 4TU.ResearchData part­ner insti­tu­tions.

Dur­ing the com­mu­ni­ty call, Yan Wang explained that the work­ing group has two main objec­tives. 

The Keynote: Building Open Communities of Collaboration 

Com­mu­ni­ty Lead, Malvi­ka Sha­ran, show­cased the inspir­ing work of The Tur­ing Way, an open source com­mu­ni­ty-dri­ven guide to repro­ducible, eth­i­cal, inclu­sive and col­lab­o­ra­tive data sci­ence.

It’s a book, com­mu­ni­ty, open source project and col­lab­o­ra­tion all in one!

“The Tur­ing Way’s moon­shot goal is to make repro­ducibil­i­ty too easy not to do,” says Malvi­ka. 

The Tur­ing Way guide aims to pro­vide data sci­en­tists in acad­e­mia, indus­try, gov­ern­ment and the third sec­tor with all the infor­ma­tion they need at the very begin­ning of their project so that their work can be eas­i­ly under­stood, repro­duced and reused. 

Start­ing as a ‘Guide for Repro­ducible Research’ that cov­ered aspects of ver­sion con­trol, test­ing and con­tin­u­ous inte­gra­tion, the project has now expand­ed to include guides on ‘Project Design’, ‘Com­mu­ni­ca­tion’, ‘Col­lab­o­ra­tion’ and ‘Eth­i­cal Research’. It also includes a ‘Com­mu­ni­ty Hand­book’ so that their process­es and com­mu­ni­ty prac­tices can be reused by oth­ers. 

Collaboration at the community’s core

Two years (plus 150 sub­chap­ters, >250 GitHub con­trib­u­tors and thou­sands of users) lat­er, the Tur­ing Way com­mu­ni­ty has con­tin­ued to grow with col­lab­o­ra­tion at the heart of the project.

What is the key to build­ing an open com­mu­ni­ty of col­lab­o­ra­tion? Here are our top 10 take home mes­sages from Malvika’s talk: 

  1. Under­stand your com­mu­ni­ty mem­bers. Iden­ti­fy their inter­ests; grant access to skills, and sup­port their needs. 
  2. Design for inten­tion­al col­lab­o­ra­tion. Define path­ways for col­lab­o­ra­tion and ‘label unla­belled doors’ so that it’s easy for peo­ple to nav­i­gate their path and get involved. 
  3. Doc­u­ment all the process­es. Be explic­it­ly open about col­lab­o­ra­tions and let com­mu­ni­ty mem­bers know where, when and how they can par­tic­i­pate. 
  4. Fos­ter a safe and inclu­sive work­space. Pro­vide guide­lines, such as a code of con­duct, to encour­age safe and enjoy­able par­tic­i­pa­tion. 
  5. Pro­vide an open source frame­work for knowl­edge exchange. This means that every­one can freely read, reuse, mod­i­fy and dis­trib­ute resources, there­by lead­ing to col­lab­o­ra­tion, peer-pro­duc­tion and project sus­tain­abil­i­ty. 
  6. Encour­age men­tor­ship and cre­ate space for the review of work to main­tain and improve resources.
  7. Wel­come exter­nal con­tri­bu­tions and col­lab­o­ra­tions. For exam­ple, shar­ing best prac­tices from oth­er com­mu­ni­ties can be a valu­able con­tri­bu­tion to your com­mu­ni­ty. 
  8. Make your work glob­al. Trans­late resources into oth­er lan­guages so that oth­ers can ben­e­fit from them. 
  9. Cre­ate a sense of shared own­er­ship that inspires con­tri­bu­tions. If the project belongs to the com­mu­ni­ty then every­one will feel respon­si­ble.
  10. Recog­nise all con­trib­u­tors so that efforts are not hid­den or ignored. Pro­vide an oppor­tu­ni­ty for com­mu­ni­ty mem­bers to build their CV through their con­tri­bu­tions!

With special thanks to…

See you in the next Call!

Exit mobile version
Skip to toolbar