## 2 FAIRification of ROs with OpenBio.eu  
Although FAIR guidelines concern data, we can very easily extend them to tools and workflows. For example, data may describe biomedical entities (i.e., gene expression), by defining appropriate formats. Similarly, we can easily create data structures to describe tools and workflows. Therefore, FAIR principles can and should be applied to all types of ROs that take part in scientific analysis. This last characteristic is demanding of another crucial requirement; that is, that the digital resource should also be embeddable, thus extending the conceptualization of the FAIR principles with an embeddable dimension, i.e., FAIR-E (\"E\" for embeddable). In OpenBio.eu, the incorporated ROs are conceptualized as integrated constructs that contain both the code required for installation (or download in the case of a dataset RO) and the semantic description required for connecting them with other ROs. Coupled with semantic web technologies, the process allows for the exploitation of linked-data architectures as connections between FAIR ROs [23], and, at the same time, it hides the representation details from users, providing a more abstract level of interaction with the system. In this setting, FAIR-E overcomes the conceptual gap between the problem to be solved and its computational solution, since usually software is described in terms of functionality (how), and problems are formulated in terms of the task to be tackled (what) [24]. To state it in a more direct manner, the design philosophy underlying OpenBio.eu considers the data and the software that operates on the data as neighbor concepts, and, at least in terms of their semantic content, as identical concepts. On Table 1 we list all FAIR principles as they were originally published [21], along with how OpenBio.eu implements them. Generally, the top four FAIR principles are im-plemented as follows:_Findability_ in OpenBio.eu is achieved by having all ROs indexed in the same searchable repository. Moreover, OpenBio.eu follows an additive model, in the sense that ROs cannot be deleted and cannot be edited. Nevertheless, users can \"fork\" the RO of any other user and create an identical RO to which they can apply any edit that they wish. Each fork creates a new RO and is assigned a unique ID with a permanent URL. _Accessibility_ is an inherent feature of OpenBio.eu. All content is free and open source. All content is not only directly accessible but also installable on any modern computer. All content is available even to anonymous users. Moreover, content is available through a REST API. _Interoperability_. ROs in OpenBio.eu can be exported into two basic formats: as a BASH executable or in Common Workflow Language (CWL) format. (a) BASH is the most standard command-line interface on Linux and OSX (with MS Windows support as well). Even though BASH is not a workflow language, per se, it offers a flexible enough framework to effectively code and arrange the individual steps of a workflow [25; 26]. A key characteristic served by OpenBio.eu is to hide the complexity of BASH by pulling it at the front-end of the workflow orchestration process via its graphical workflow editing interface. This makes it unnecessary for the user to learn any domain-specific programming language (DSL), thus improving flexibility in workflow design, and at the same time easing the adaptation and sharing of workflows. (b) Workflows are exported in CWL through an algorithm that converts BASH function calls to directed acyclic graphs (DAGs). Through CWL, the interoperability of devised workflows between any contemporary operating system is achieved, allowing for the inclusion of ROs and workflows into a wide variety of Workflow Management Systems (WfMSs) such as CWL Tool, Galaxy [27; 28], Nextflow