Presentation Open Access

Boosting complex Systems Research through RSE Collaboration

Kelling, Jeffrey; Tripathi, Richa; Calabrese, Justin M.

Citation Style Language JSON Export

  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.7719360", 
  "language": "eng", 
  "title": "Boosting complex Systems Research through RSE Collaboration", 
  "issued": {
    "date-parts": [
  "abstract": "<p>Stochastic simulations of complex systems from domains including physics, biology, ecology or economics often require large system sizes, long time scales, and numerous replications to fully explore model behavior. The simple rules defining many models can lead researchers to prefer familiar but inefficient programming techniques, which severely hinder progress<br>\nby creating computational bottlenecks. While such studies often benefit from combined domain-specific, statistical, and programming knowledge, few individual researchers span the full range of necessary skills. Here, we present a collaboration on the neutral model of biodiversity in dendritic river networks, where the goal is to analyze biodiversity data across the world&rsquo;s major river systems. We show how we achieved large performance gains by engaging the problem at its foundations and thereby enabled research at a new scale.</p>", 
  "author": [
      "family": "Kelling, Jeffrey"
      "family": "Tripathi, Richa"
      "family": "Calabrese, Justin M."
  "id": "7719360", 
  "event-place": "Paderborn, Germany", 
  "type": "speech", 
  "event": "deRSE23 - Conference for Research Software Engineering in Germany (deRSE23)"
All versions This version
Views 154154
Downloads 4545
Data volume 106.5 MB106.5 MB
Unique views 131131
Unique downloads 4141


Cite as