@Andrawaag Thanks a lot for your comment, Andra. I don’t necessarily agree with several of your points, and thus had to sort out for myself over the past few days, why I still feel that you have highlighted a key point regarding businesses and a future DES’ interactions with them.
My short answer is data (infrastructure, service) quality. I agree with your argument that quality (across the range of criteria) is at the core of business’ capitals, capacities and experiences. Businesses can add a level of quality to data, infrastructures and services that research a) might not be interested in (since its not needed for the progress of knowledge and insight), and b) simply can’t provide due to contextual constraints (short-term project-based work, insufficient funding and resources, different institutional focuses and priorities, …).
Verified and high-quality data in efficient infrastructures, therefore, is something that specifically companies can contribute to capacity building (fact-based knowledge, research and expertise), to knowledge and technology transfer, and thus to tangible benefit sharing for the protection of biodiversity and the achievements of the SDGs.
The question thus becomes: Which characteristics does a DES infrastructure need to have to be acceptable and even desirable for companies? That is, what are the key traits required by companies to consider and then implement links between their own and the DES infrastructure, and to share certain information (eg. metadata) or (sub)sets of their data with the DES network?
In the context of biodiversity conservation and ABS, for me the second phase of benefit sharing so far had been characterized by a) non-monetary benefit sharing being associated with (basic) biodiversity research, while b) businesses are predominantly associated with monetary benefit sharing. However, what if the DES provides the context and functionality, which encourages businesses to share their seriously high-quality datasets with the world?
High-quality data and especially high-quality designed-for-purpose datasets are dearly and urgently needed across the range of conservation applications (I have explored and provided statistical arguments for conservation genomics eg. here). In addition, there is an evolving landscape of free and open-source software (FOSS; include: data) business models, which provide the foundations for some very successful small to large companies.
What would be needed for this to work?