How does software fit into the FDO landscape?

In academic research virtually every field has increased its use of digital and computational technology, leading to new scientific discoveries, this trend is likely continue. Reliable efficient scholarly requires researchers be able validate extend previously generated results. the era, implies that objectsKahn Wilensky 2006 used in should Findable, Accessible, Interoperable Reusable (FAIR). These objects include (but are not limited to) data, software, models (for example, machine learning), representations physical objects, virtual environments, workflows, etc. Leaving any these out FAIR process may result a loss rigor have severe consequences long term for field, such as reproducibility crisis. extended abstract, we focus on software object (FDO). The FDO framework De Smedt et al. 2020 describes FDOs being actionable units knowledge, which can aggregated, analyzed, processed by different types algorithms. Such algorithms must implemented one form or another. also large stacks supporting enabling responsible data science increasing reproducibility. This key ingredient framework, adhere principles. Software plays multiple roles: it DO itself, creating (e.g., data) helps make them available public via repositories registries). However there need specify more detail how non-data DOs, particular fit framework. Different classes intrinsic properties ways relate other DOs. means while they, principle, subject high-level principles, differences depending their type properties, requiring an adaptation so implementations aligned itself. holds true software. (executability, composite nature, development practices, continuous evolution versioning, packaging distribution) specific needs considered For open source typically developed social coding platforms, where releases distributed through package management systems, unlike published archival repositories. platforms do provide archiving, permanent identifiers, metadata, somewhat better, similarly commitment identifiers publication system well, metadata missing elements. (FAIR4RS, Chue Hong 2021) working group dedicated significant effort building community consensus around developing principles customized providing methods understand address gaps. presentation will highlight importance landscape why related) needed (vs those originally data). Our goal here contribute together, consider all essential today's research, enthusiastic about contributing our expertise helping shape landscape.