{'fraction_non_alphanumeric': 0.01978891820580475, 'fraction_numerical': 0.0008795074758135445, 'mean_word_length': 5.481481481481482, '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}}
Joint handling of semantic knowledge resources and their alignments

With the adoption of the Semantic Web vision , semantic knowledge resources (KR), which include taxonomies, structured vocabularies and ontologies, acting as pivotal resources, are nowadays commonly used. This is a direct consequence of the desire to attach formal semantic meaning to manipulated data. These KR, developed by different communities with various needs and purposes, are by nature heterogeneous. This heterogeneity leads to the development of systems for finding the correspondences between entities of different KR, called alignment [2]. In addition, KR increasingly involve large volumes of formalized knowledge, containing hundred of thousand entities, which raises the question of generating and validating alignments between large resources. In order to help finding and reusing these more and more available KRs, a significant effort has been made for providing multi-knowledge resources repositories. This effort is particularly noticeable in the biomedical domain, where classifying existing objects is a secular tradition. However, to the best of our knowledge, there is no currently available framework which offers the possibility to handle both multiple KRs together with their respective alignments, while keeping their native semantics and offering a support for a transparent visualization of these resources. In addition, with the development of the ontology matching domain, as different systems could be used to generate alignments and sometimes relying on user input, either for mappings validation purpose or initial alignment providing, it is a crucial issue to keep track of users and involved alignment methods or tools. To fill this gap, we have designed the K-Ware framework [1] which complement existing multi-knowledge resources repositories. Its aim is not to provide a single access point for all available biomedical ontologies and alignments. Rather, it is a framework which could be embedded within projects that have an extensive use of multiple KRs and their respective alignments. In particular, enabling a support for multi point of view navigation and hierarchical visualization of any KR relevant for a dedicated purpose or suitable for a given project.