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1. Reasoning about modern datacenter infrastructures using partial histories

   https://doi.org/10.1145/3458336.3465276  

   Sun, Xudong; Suresh, Lalith; Ganesan, Aishwarya; Alagappan, Ramnatthan; Gasch, Michael; Tang, Lilia; Xu, Tianyin (June 2021, In Proceedings of the 18th Workshop on Hot Topics in Operating Systems (HotOS-XVIII))

   null (Ed.)

   Modern datacenter infrastructures are increasingly architected as a cluster of loosely coupled services. The cluster states are typically maintained in a logically centralized, strongly consistent data store (e.g., ZooKeeper, Chubby and etcd), while the services learn about the evolving state by reading from the data store, or via a stream of notifications. However, it is challenging to ensure services are correct, even in the presence of failures, networking issues, and the inherent asynchrony of the distributed system. In this paper, we identify that partial histories can be used to effectively reason about correctness for individual services in such distributed infrastructure systems. That is, individual services make decisions based on observing only a subset of changes to the world around them. We show that partial histories, when applied to distributed infrastructures, have immense explanatory power and utility over the state of the art. We discuss the implications of partial histories and sketch tooling for reasoning about distributed infrastructure systems. 

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2. An Ontology of Dark Patterns Knowledge: Foundations, Definitions, and a Pathway for Shared Knowledge-Building

   https://doi.org/10.1145/3613904.3642436  

   Gray, Colin M.; Santos, Cristiana Teixeira; Bielova, Nataliia; Mildner, Thomas (May 2024, CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems)

   Deceptive and coercive design practices are increasingly used by companies to extract profit, harvest data, and limit consumer choice. Dark patterns represent the most common contemporary amalgamation of these problematic practices, connecting designers, technologists, scholars, regulators, and legal professionals in transdisciplinary dialogue. However, a lack of universally accepted definitions across the academic, legislative, practitioner, and regulatory space has likely limited the impact that scholarship on dark patterns might have in supporting sanctions and evolved design practices. In this paper, we seek to support the development of a shared language of dark patterns, harmonizing ten existing regulatory and academic taxonomies of dark patterns and proposing a three-level ontology with standardized definitions for 64 synthesized dark pattern types across low-, meso-, and high-level patterns. We illustrate how this ontology can support translational research and regulatory action, including transdisciplinary pathways to extend our initial types through new empirical work across application and technology domains. 

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3. Modifier Ontologies for frequency, certainty, degree, and coverage phenotype modifier

   https://doi.org/10.3897/BDJ.6.e29232  

   Endara, Lorena; Thessen, Anne; Cole, Heather; Walls, Ramona; Gkoutos, Georgios; Cao, Yujie; Chong, Steven; Cui, Hong (November 2018, Biodiversity Data Journal)

   Background: When phenotypic characters are described in the literature, they may be constrained or clarified with additional information such as the location or degree of expression, these terms are called “modifiers”. With effort underway to convert narrative character descriptions to computable data, ontologies for such modifiers are needed. Such ontologies can also be used to guide term usage in future publications. Spatial and method modifiers are the subjects of ontologies that already have been developed or are under development. In this work, frequency (e.g., rarely, usually), certainty (e.g., probably, definitely), degree (e.g., slightly, extremely), and coverage modifiers (e.g., sparsely, entirely) are collected, reviewed, and used to create two modifier ontologies with different design considerations. The basic goal is to express the sequential relationships within a type of modifiers, for example, usually is more frequent than rarely, in order to allow data annotated with ontology terms to be classified accordingly. Method: Two designs are proposed for the ontology, both using the list pattern: a closed ordered list (i.e., five-bin design) and an open ordered list design. The five-bin design puts the modifier terms into a set of 5 fixed bins with interval object properties, for example, one_level_more/less_frequently_than, where new terms can only be added as synonyms to existing classes. The open list approach starts with 5 bins, but supports the extensibility of the list via ordinal properties, for example, more/less_frequently_than, allowing new terms to be inserted as a new class anywhere in the list. The consequences of the different design decisions are discussed in the paper. CharaParser was used to extract modifiers from plant, ant, and other taxonomic descriptions. After a manual screening, 130 modifier words were selected as the candidate terms for the modifier ontologies. Four curators/experts (three biologists and one information scientist specialized in biosemantics) reviewed and categorized the terms into 20 bins using the Ontology Term Organizer (OTO) (http://biosemantics.arizona.edu/OTO). Inter-curator variations were reviewed and expressed in the final ontologies. Results: Frequency, certainty, degree, and coverage terms with complete agreement among all curators were used as class labels or exact synonyms. Terms with different interpretations were either excluded or included using “broader synonym” or “not recommended” annotation properties. These annotations explicitly allow for the user to be aware of the semantic ambiguity associated with the terms and whether they should be used with caution or avoided. Expert categorization results showed that 16 out of 20 bins contained terms with full agreements, suggesting differentiating the modifiers into 5 levels/bins balances the need to differentiate modifiers and the need for the ontology to reflect user consensus. Two ontologies, developed using the Protege ontology editor, are made available as OWL files and can be downloaded from https://github.com/biosemantics/ontologies. Contribution: We built the first two modifier ontologies following a consensus-based approach with terms commonly used in taxonomic literature. The five-bin ontology has been used in the Explorer of Taxon Concepts web toolkit to compute the similarity between characters extracted from literature to facilitate taxon concepts alignments. The two ontologies will also be used in an ontology-informed authoring tool for taxonomists to facilitate consistency in modifier term usage. 

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4. Modest flooding can trigger catastrophic road network collapse due to compound failure

   https://doi.org/10.1038/s43247-022-00366-0  

   Dong, Shangjia; Gao, Xinyu; Mostafavi, Ali; Gao, Jianxi (February 2022, Communications Earth & Environment)

   Abstract Compound failures occur when urban flooding coincides with traffic congestion, and their impact on network connectivity is poorly understood. Firstly, either three-dimensional road networks or the traffic on the roads has been considered, but not both. Secondly, we lack network science frameworks to consider compound failures in infrastructure networks. Here we present a network-theory-based framework that bridges this gap by considering compound structural, functional, and topological failures. We analyze high-resolution traffic data using network percolation theory to study the response of the transportation network in Harris County, Texas, US to Hurricane Harvey in 2017. We find that 2.2% of flood-induced compound failure may lead to a reduction in the size of the largest cluster where network connectivity exists, the giant component, 17.7%. We conclude that indirect effects, such as changes in traffic patterns, must be accounted for when assessing the impacts of flooding on transportation network connectivity and functioning. 

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5. Modular ontology modeling

   https://doi.org/10.3233/SW-222886  

   Shimizu, Cogan; Hammar, Karl; Hitzler, Pascal (April 2023, Semantic Web)

   Kirrane, Sabrina; Ngonga Ngomo, Axel-Cyrille; Kirrane, Sabrina; Ngonga Ngomo, Axel-Cyrille (Ed.)

   Reusing ontologies for new purposes, or adapting them to new use-cases, is frequently difficult. In our experiences, we have found this to be the case for several reasons: (i) differing representational granularity in ontologies and in use-cases, (ii) lacking conceptual clarity in potentially reusable ontologies, (iii) lack and difficulty of adherence to good modeling principles, and (iv) a lack of reuse emphasis and process support available in ontology engineering tooling. In order to address these concerns, we have developed the Modular Ontology Modeling (MOMo) methodology, and its supporting tooling infrastructure, CoModIDE (the Comprehensive Modular Ontology IDE – “commodity”). MOMo builds on the established eXtreme Design methodology, and like it emphasizes modular development and design pattern reuse; but crucially adds the extensive use of graphical schema diagrams, and tooling that support them, as vehicles for knowledge elicitation from experts. In this paper, we present the MOMo workflow in detail, and describe several useful resources for executing it. In particular, we provide a thorough and rigorous evaluation of CoModIDE in its role of supporting the MOMo methodology’s graphical modeling paradigm. We find that CoModIDE significantly improves approachability of such a paradigm, and that it displays a high usability. 

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