Available databases of relevance for the development of an internet of things (IoT) data management platform for livestock farming were identified through a survey in the five partner countries. Experiments with accelerometers were carried out to identify parameters and classifiers of lameness. A list of key environmental indicators was identified. The indicators include categories within energy, nutrient use, soil/land issues, biodiversity, water, carbon footprint and economy. The indicators form the basis for a farm-based life cycle assessment (LCA) where economic drivers are integrated. System analysis has been performed by indicating the identified stakeholders. A web platform representing the mutual relations between different actors was developed and prepared for continuous updating of economic consequences of lameness. Available databases with data on animal health form the basis for farmers and advisors to compare and benchmark different production systems and methods in terms of sustainability, including indicators within energy, nutrient use, soil/land issues, biodiversity, water, carbon footprint and economy. Specifically, the guidelines for the use of accelerometers for lameness detection were outlined. Based on the results, good dairy farming practices were developed within animal health, milk hygiene, feeding, animal welfare, environmental impact and socioeconomic benefits as guidelines for advisors and farmers. Also, these results are useable for researchers in their pursuit of further designing and implementing information management systems in precision livestock.