Another issue is that annotators face technical difficulties when it comes to scaling up for the purpose of annotating hundreds of millions of documents [14]. This is partly due to the fact that numerous existing solutions were introduced even decades ago, and either have not been tested with huge corpora or have limited scaling abilities. Modern technologies such as virtualized computing and hosting in \"serverless\" environments can help to resolve this issue [15,16]. Another important consideration is that existing benchmarks are application-specific [17]. Annotators work within many parameters that can have a detrimental effect on their efficacy. Tuning the parameters of an annotator for a specific test is a form of introducing bias when compared with other annotators. A remedy for this is to have independent third-party tools tune the parameters of the annotators during testing. There are already frameworks for automatic parameter tuning in large and complex workflows [18,19]. Of course, this would require the \"wrapping\" of the parameter space in a common format for all tested tools. We argue that all approaches to the solution of the aforementioned problems and challenges are tightly connected with the FAIRification process [20], the process of making research (and not only) digital resources findable, accessible, interoperable, and reusable, for both humans and machines [21]. For example, making ontologies and lexicographic resources findable and accessible will help annotators to generalize their concepts, expand their domains, and support more languages. Making BTA tools interoperable will help with both benchmarking and scaling in modern computational environments. Moreover, making all workflows reusable will help with locating and correcting possible biases in comparison studies. The work presented in this paper is about making BTA processes FAIR compliant. This is achieved by using the OpenBio.eu platform, an open science online environment where researchers can create, edit, share, re-combine, export, execute, rate, and collaborate on managing tools, data, and workflows (called hereafter Research Objects, or ROs) [22]. The purpose of the platform is to offer data stewardship services that will aid the reuse of data beyond their original scope. The code for ROs can be anything that is executable in a local computer. These can be simple scripts, source code, binaries, Docker, or any other containerization format. All information is imported into ROs through an intuitive UI without having to know any Domain Specific Language (DSL). A user only needs to insert the installation instructions that she would have to write in an execution environment; in other words, importing a tool in OpenBio.eu requires exactly the same steps as importing it in an operating system such as Linux [22]. In the context of the above-described framework, this work demonstrates the synthesis, orchestration, and deployment of BTA workflows via the combination of respective open-source ROs, all of which were appropriately imported and installed in OpenBio.eu. A total of five corpora, 169 ontologies, and six known tools for BTA were imported. The effort required to add some of these ROs in an open science environment such as OpenBio.eu is pointed out as a means of highlighting the challenges involved with the setup and configuration of BTA open-source computational resources. The remainder of this paper is organized as follows: Section 2 introduces the main architecture of OpenBio.eu and demonstrates how it enables the FAIRification of research objects; Section 3 presents, in detail, a set of ROs in BTA, their functionality, and other remarks from their FAIRification process; Section 4 presents how the FAIRified ROs can be combined in complex workflows, which can help with tasks such as comparison and scaling in high-performance computing environments; finally, Section 5 presents some concluding remarks, limitations, and future work directions.