This report presents the program and outcomes of Dagstuhl Seminar "Research Infrastructures and Tools for Collaborative Networked Systems Research" (24462). The seminar brought together experts from the network and distributed systems testbed community, scientists who rely on testbeds for their research, and representatives from funding agencies. It focused on bridging the gap between the services provided by large-scale testbed infrastructures and the needs of researchers conducting cutting-edge experiments. Discussions centered on enhancing the value and impact of research infrastructures by improving collaboration, streamlining experiment workflows, and developing testbed-agnostic tools. The goal was to make experimental research more modular, adaptable, and reproducible, ensuring that experiments and evaluation software can be easily modified, extended, and ported across different testbed environments. Key topics included strategies to improve research quality, reproducibility, and reusability, enhance the discovery process, and maximize the efficient use of research infrastructure resources.
@Article{carle_et_al:DagRep.14.11.60, author = {Carle, Georg and Fdida, Serge and Keahey, Kate and Schulzrinne, Henning and Gallenm\"{u}ller, Sebastian}, title = {{Research Infrastructures and Tools for Collaborative Networked Systems Research (Dagstuhl Seminar 24462)}}, pages = {60--91}, journal = {Dagstuhl Reports}, ISSN = {2192-5283}, year = {2025}, volume = {14}, number = {11}, editor = {Carle, Georg and Fdida, Serge and Keahey, Kate and Schulzrinne, Henning and Gallenm\"{u}ller, Sebastian}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.11.60}, URN = {urn:nbn:de:0030-drops-228197}, doi = {10.4230/DagRep.14.11.60}, annote = {Keywords: Research Infrastructures, Testbeds, Reproducibility, \{FAIR: Findability, Accessibility, Interoperability, and Reuse of digital assets\}, Infrastructure usage and sharing, Artifact Evaluation, Optimizing reuse of data} }
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