From recipes for creating chemical mixtures (buffers, tissue culture media) to computational procedures and systems (software documentation, accession number formats), the landscape of scientific practice in biology is full of protocols. In concrete research setting, protocols are coordination mechanisms that formalize and systematize procedures and know-how required to conduct research (whether in the lab or field), including ways to develop and handle materials, instruments, setups, systems and pipelines in ways that facilitate coordination towards research goals. They can be either highly standardized and common across contexts (e.g. MS medium, IPEN) leading to problems of lack of appropriateness or highly contextualized leading to problems of lack of interoperability. Given their centrality for research practice in applied biology, focusing on protocol practices is crucial for addressing issues of technology transfer, reproducibility and effective epistemic coordination both inside the local research environment and across geographically distributed settings.
This symposium encourages researchers to think about cooperative processes in biological practice through the design, use and modification of protocols. Its aims are both critical, exploring pertinent ethical and technical issues related to protocol use, and constructive, by facilitating creative imaginings for a future for protocol design through appropriate digital formats and diverse technologies. These aims are pursued by creating a space for a transdisciplinary "trialogue", merging three different worlds: a) academic studies of scientific practice, b) applied biology practice in agriculture c) and forefront innovation in decentralized science infrastructure.
The session is organized as part of the PHIL_OS project.
The practice-turn in science studies has illuminated how scientific knowledge production operates as a dynamic and local process. Case studies of lab environments have highlighted the ways in which experimental and analytical procedures involve all kinds of contingencies, mishaps, on-the-spot solutions and accidents but at the same time contain such contingencies by being, as a whole, highly regimented and standardized systems. One of these elements that are used to foster stability are protocols. Protocols come in many different forms, dwelling in a continuum from material procedures (e.g. buffer mixtures for tissue culture of endemic species) to digitalised distributed mechanisms (genomic databases). Their main function is coordinative and rests in reducing the need for “articulation work", that is the work of making research practices legible through ordering, sorting, codifying and documenting.
In contrast to other domains of collaborative activity, scientific articulation work is not just operational but has epistemic import, since the object of articulation is mostly the production of data and knowledge. The informational explosion in contemporary science dominated by a push towards data-intensive methods makes scientific coordination highly complex and scientific protocols reflect this complexity, often by producing unexpected results which invite a range of non-standard coping strategies that break the flow of the procedure (interpreting, retro-fitting, discarding, explaining etc). This view approaches protocols not only as record keeping media but also as dynamic objects with their own impetus, prioritizing their performative rather than representational nature (exemplified especially by algorithmic protocols). Ethnographic research between lab and field, helps to keep track of protocol modifications and the factors that govern the decision-making that underlies these decisions.
In this paper, grounded on empirical fieldwork of Greek plant science, I investigate protocols as means of inviting cross-domain collaboration, encouraging individual agency as well as improving or shattering communication, interoperability and reproducibility.
Protocols in agriculture go beyond routine procedures; they are frameworks designed to optimize efficiency, enhance productivity, ensure sustainable practices across the agricultural sector and facilitate communication within agricultural research and practice.
The process of protocol development in agriculture begins with leveraging existing scientific literature and adapting procedures to meet regional needs, available equipment, and the educational level of the practitioners involved. Protocols are customized for specific tools and devices that may be available in individual labs, ensuring that resources are used effectively. Additionally, devices undergo calibration to maintain accuracy, with protocols continuously tested and refined based on user feedback. This cycle of testing and feedback promotes constant improvement and allows for broader applicability of protocols across different contexts, ultimately supporting a standardized approach to agricultural practice.
Practical examples of these protocols include in vitro tissue culture techniques for plant shoot and root induction, which allow for rapid propagation of high-quality plant material. Protocols for ex vitro plant acclimatization help plants transition from controlled environments to outdoor conditions, improving survival rates. Other protocols, such as avocado ripeness assessments through sampling, dry matter, and oil content analysis, or soil analysis for crop suitability, provide essential data that aid farmers in making informed decisions. Leaf analysis protocols for determining plant nutritional needs further contribute to precision agriculture, ensuring optimal resource use and crop health.
Through standard protocols, agricultural research transforms into actionable practices, creating a structured chain of information that flows from research institutions to the hands of farmers. Overall, agricultural protocols provide consistency and increased reliability, leading to better agricultural outcomes and sustainable practices.
This paper explores AI agent-based simulations to contrast two governance models: data-driven compliance zones and experimental sandboxes for adaptive agricultural governance. Under the European Union’s Green Deal, farms are increasingly digitized, integrated into the Farm Sustainability Data Network (FSDN). Automated drones, soil sensors, and AI audits ensure adherence to sustainability metrics, reducing governance to machine-readable indicators and compliance alerts. While promising efficiency and transparency, this model shifts decision-making from farmers to externalized protocols, standardizing practices and prioritizing measurement over adaptability. In contrast, we propose AI-driven exploratory sandboxes as bottom-up governance spaces where stakeholders, such as farmers, policymakers, scientists, and citizen groups, use AI agents to simulate and negotiate agricultural policies in real-time. These sandboxes function as virtual policy labs, enabling participatory decision-making and scenario-building before real-world implementation. Here, data is treated as a communal resource similar to crops in the fields, fostering collaboration rather than bureaucratic oversight. Farms become living laboratories, where AI-assisted decision-making supports citizen science and policy co-creation. By comparing these two scenarios of AI adoption, we argue that sandboxes rather than evidence-based policy modelling offer a more democratic and adaptive governance approach. Rather than reinforcing rigid compliance structures, sandboxes facilitate situated experimentation and stakeholder engagement, challenging the bureaucratic rigidity of technocratic oversight and opening new pathways for flexible, community-driven agricultural futures.