{'fraction_non_alphanumeric': 0.012953367875647668, 'fraction_numerical': 0.0, 'mean_word_length': 6.578431372549019, '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}}
Enabling Decision-Making Analytics for Collaborative Information Exchanges of Digital Precinct Models

This research identifies patterns of conflicting interorganisational information exchange requirements in precinct modelling and simulation (M&S) depending on the interaction and expertise of the collaborating actors. Internationally surveying leading experts, it extends multicriteria decision analysis with partitioning matrices of superposed orders from the eigenvectors of comparative datasets. The results are applied to real-world industry tasks and exchanges established for building M&S to combine and reuse them as models for precinct assets including energy infrastructure and also for supporting modular information exchanges between digital precinct models.