Interviews with Data Holders -Mad Schultz, PhD Student, NORD University

Who are you, and what is the name of your institute? 

We are PhD students at the Faculty for Bioscience and Aquaculture at NORD university in Bodø. Nord university is situated in sub-Arctic Norway with easy access to areas important for understanding the effects of global warming on marine systems.
My name is Mads Schultz and I work with zooplankton in the North Atlantic and Arctic. I started working on zooplankton in 2017 and have done extensive sampling on different projects since then, working on different vessels under very different circumstances. Participating in different projects have given me an insight into how differently researchers manage data during and after sampling. It is through this lens I understand the need for a standardized way of managing and storing data.
Cesc Gordo Vilaseca is participating in this workshop with me. Cesc has worked a good deal on climate change impact on fish communities as well as zooplankton communities both in marine and limnic systems. He has firsthand experience working with larger datasets derived from international databases and is used to piecing together information on a larger scale. Cesc has as well carried out sampling of his own and is familiar with obstacles that can arise when collecting samples and gathering data.

What type of data does your institute produce, how is it produced, and in which regions do you operate? 

NORD university has three ongoing data sets from the local sub-Arctic fjords.
The Zooplankton time series comprises samples collected in three fjords: Mistfjorden, Saltfjorden and Skjerstad fjord. These locations have all been sampled since 1980 and during the past decade, the temporal resolution has been increased. The sampling has been standardized since start of the project and each sampling consists of vertical trawls taken in six replicates. One replicate is measured for dry weight, while the rest is stored in a 4% formalin solution. CTD data is connected to each sampling. The samples are analysed for species abundances but are stored for later use in other projects.
The Benthos time series comprises samples collected at six stations. Three stations are located in Skjerstad fjord, two stations are located in Saltfjorden and one station is located on the shelf outside Bodø. The time series was started in 2013 and is collected annually in May/June. Each sampling consists of grab samples taken in three replicates. Environmental data collected for each sampling include a CTD, total organic carbon, granulometry, Redox, pH and sediment temperature. The samples are sorted and analysed for species abundances.
The third data set is the newest and comprises video recordings from two cameras located in the Saltfjorden Marine Protected Area. This project was started in March 2023 and can be followed live. The videos will be analysed for fish species abundances and behaviour.

How will your project add value to existing data flows? 

As per now, the data flow from these projects are limited as a standardized way of storing the data has not yet been successfully implemented. We aim to implement standardized protocols for managing and storing the data, which in turn will enable the data to become useful both for smaller and larger future projects.

What is the expected impact of your proposed project?

We aim to have a centralized database stored locally at NORD university, where data can be added and amended by faculty researchers, technical staff and students. The database will be set up in Darwin Core format for publication into EMODnet Biology.

How will this involvement or opportunity enhance your institute’s capacity?

By getting different perspectives and streamlining data management, we allow for the best possible outcome for our projected aim. Managing data from multiple projects with many different people involved, we need to make sure that the solution created is sturdy and as many scenarios as possible have been accounted for. By participating in this workshop, more perspectives are taken into account, and we ensure the success of the project, which in turn will enable NORD university to produce even more high-quality data.