{'fraction_non_alphanumeric': 0.01328125, 'fraction_numerical': 0.0, 'mean_word_length': 4.985981308411215, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Data Analytics in Aquaculture

Aquaculture’s specific challenges today reveal needs and problems directly related with the quality of data collected by the professional in this industry. As the feeding of the fish is a large part of the cost in the production, that must be addressed appropriately and in sync with the most recent optimization methods. With this paper we show the impact of data analytics in the improvement of the production techniques in aquaculture. In that, we consider the state of the art methods of statistics and data mining that permit a deeper insight into the aquaculture reality through the collected datasets, either from daily data or from sampling to sampling data. This must be tuned to the expert knowledge of the fish farmers, their procedures and technology in use today. In this paper we also review the state of the art of data analytics methodology in aquaculture, the data available deriving from the procedures characteristic to this business, and propose mathematical models that permit a deeper insight on the data. Moreover, we address the data unknowns and strategies developed that will contribute to the success of the business, leading to discover valuable information from the data that can be made usable, relevant and actionable.