Blogs

PeerJ Award Winners at SORTEE 2023

The third annual SORTEE conference was held virtually in October 2023, continuously over 24 hours to cover all time zones. There were 266 registered participants from 36 countries. The conference programme included plenary talks, 5 workshops, 5 hackathons and 8 unconference sessions. During the closing sessions two winners were announced for the SORTEE “Student Award” and “Researcher Award”. These awards have been renamed and redesigned to increase transparency, equity and inclusions. In the new award process, nominations were initially assessed for eligibility, then eligible candidates were entered as finalists into a lottery to select the winner for each award. The lottery was run using a random ‘spin the wheel’ program, requiring one re-spin to ensure fulfilment of SORTEE Diversity, Equity and Inclusion policy. The winner of the ‘Student Award’ was: Euan Young affiliated with the University of Groningen in the Netherlands. The winner of the ‘Researcher Award’ was Birgit Szabo affiliated with the University of Bern in Switzerland.

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Complexities of reuse and synthesis in the open data landscape

Open data offers immense opportunities for ecologists and evolutionary biologists. The more good quality data are available, the more questions can be answered—and at broader spatial and temporal scales and at greater taxonomic generality. However, making use of open data is far from straightforward.

At this year’s SORTEE conference, Rose Trappes and Alfredo Sánchez-Tójar co-organized a productive unconference to tackle this complex topic. For that, they invited three experienced panellists: Matt Grainger, Antica Culina and Benno Simmons, and held a discussion about the opportunities and challenges of data reuse and data synthesis in the fast-moving world of open data. We heard from researchers experienced in reusing and synthesising data, as well as those active in creating open data resources for ecologists and evolutionary biologists.

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SORTEE member voices – Félicie Dhellemmes

[SORTEE member voices is a weekly Q&A with a different SORTEE member]
   

Name: Félicie Dhellemmes (she/her)
 

Date: 28 June 2023.
 

Position: Post-Doc.
 

Research and/or work interests:
Behavioral ecology, movement ecology, individual differences in behavior, foraging.
   

How did you become interested in open research?
I became interested in ORT research practices pretty early on when it became evident to me that if we wanted the public to trust science (in the context of climate, for example), science had to be exemplary and as trustworthy as possible.
   

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SORTEE member voices – Saeed Shafiei Sabet

[SORTEE member voices is a weekly Q&A with a different SORTEE member]
   

Name: Saeed Shafiei Sabet
 

Date: 8 December 2022.
 

Position: Research Fellow.
 

Research and/or work interests:
Animal behavior, Anthropogenic noise, predator-prey interactions,
noise impacts, wildlife, anti-predator behavior, fish, crustaceans.
   

How did you become interested in open research?
To be able to share our findings and behavioral observations in a more
clear and available way.
   

What is an open/reliable/transparent science practice that you admire but have not yet adopted in your own work?
Data availability and access.
   

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SORTEE member voices – Malgorzata (Losia) Lagisz

[SORTEE member voices is a weekly Q&A with a different SORTEE member]
   

Name: Malgorzata (Losia) Lagisz

Date: 30 June 2023.  

Position: Research Fellow.
 

Research and/or work interests:
I am a biologist with research experience and skills in different fields of science. I often venture outside biological topics and data, for example, into biomedical, environmental, conservation, or even social sciences. In my research, I use research synthesis methods, such as systematic reviews/maps and meta-analyses.
   

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SORTEE member voices – Gabe Winter

[SORTEE member voices is a weekly Q&A with a different SORTEE member]
   

Name: Gabe Winter (they/any)

Date: 2 June 2023.  

Position: PhD candidate at Friedrich-Schiller University Jena, Germany.
 

Research and/or work interests:
I am an ecologist, currently working with intra-individual variability in behaviour, but also super excited about open, transparent and reproducible research and data science.
   

What ‘ORT’ practice have you introduced into your research practice that you’ve found really helpful?
Having well documented R scripts have improved a lot my own reproducibility. Before, when I had to pause my analysis for a couple months (during field/lab work season, for example), it used to be tricky to remember what I was doing, and I usually had to start everything from the beginning. Now, using commented R markdowns I can simply continue from where I stopped every time. It takes some time to comment everything, but that same time (and more) is saved when I don’t have to re-analyse from scratch.
   

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