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1. Incentivising use of structured language in biological descriptions: Author-driven phenotype data and ontology production

   https://doi.org/10.3897/BDJ.6.e29616  

   Cui, Hong; Macklin, James; Sachs, Joel; Reznicek, Anton; Starr, Julian; Ford, Bruce; Penev, Lyubomir; Chen, Hsin-Liang (November 2018, Biodiversity Data Journal)

   Phenotypes are used for a multitude of purposes such as defining species, reconstructing phylogenies, diagnosing diseases or improving crop and animal productivity, but most of this phenotypic data is published in free-text narratives that are not computable. This means that the complex relationship between the genome, the environment and phenotypes is largely inaccessible to analysis and important questions related to the evolution of organisms, their diseases or their response to climate change cannot be fully addressed. It takes great effort to manually convert free-text narratives to a computable format before they can be used in large-scale analyses. We argue that this manual curation approach is not a sustainable solution to produce computable phenotypic data for three reasons: 1) it does not scale to all of biodiversity; 2) it does not stop the publication of free-text phenotypes that will continue to need manual curation in the future and, most importantly, 3) It does not solve the problem of inter-curator variation (curators interpret/convert a phenotype differently from each other). Our empirical studies have shown that inter-curator variation is as high as 40% even within a single project. With this level of variation, it is difficult to imagine that data integrated from multiple curation projects can be of high quality. The key causes of this variation have been identified as semantic vagueness in original phenotype descriptions and difficulties in using standardised vocabularies (ontologies). We argue that the authors describing phenotypes are the key to the solution. Given the right tools and appropriate attribution, the authors should be in charge of developing a project’s semantics and ontology. This will speed up ontology development and improve the semantic clarity of phenotype descriptions from the moment of publication. A proof of concept project on this idea was funded by NSF ABI in July 2017. We seek readers input or critique of the proposed approaches to help achieve community-based computable phenotype data production in the near future. Results from this project will be accessible through https://biosemantics.github.io/author-driven-production. 

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2. Author-Driven Computable Data and Ontology Production for Taxonomists

   https://doi.org/10.3897/biss.5.75741  

   Cui, Hong; Ford, Bruce; Starr, Julian; Macklin, James; Reznicek, Anton; Giebink, Noah; Longert, Dylan; Léveillé-Bourret, Étienne; Zhang, Limin (September 2021, Biodiversity Information Science and Standards)

   It takes great effort to manually or semi-automatically convert free-text phenotype narratives (e.g., morphological descriptions in taxonomic works) to a computable format before they can be used in large-scale analyses. We argue that neither a manual curation approach nor an information extraction approach based on machine learning is a sustainable solution to produce computable phenotypic data that are FAIR (Findable, Accessible, Interoperable, Reusable) (Wilkinson et al. 2016). This is because these approaches do not scale to all biodiversity, and they do not stop the publication of free-text phenotypes that would need post-publication curation. In addition, both manual and machine learning approaches face great challenges: the problem of inter-curator variation (curators interpret/convert a phenotype differently from each other) in manual curation, and keywords to ontology concept translation in automated information extraction, make it difficult for either approach to produce data that are truly FAIR. Our empirical studies show that inter-curator variation in translating phenotype characters to Entity-Quality statements (Mabee et al. 2007) is as high as 40% even within a single project. With this level of variation, curated data integrated from multiple curation projects may still not be FAIR. The key causes of this variation have been identified as semantic vagueness in original phenotype descriptions and difficulties in using standardized vocabularies (ontologies). We argue that the authors describing characters are the key to the solution. Given the right tools and appropriate attribution, the authors should be in charge of developing a project's semantics and ontology. This will speed up ontology development and improve the semantic clarity of the descriptions from the moment of publication. In this presentation, we will introduce the Platform for Author-Driven Computable Data and Ontology Production for Taxonomists, which consists of three components: a web-based, ontology-aware software application called 'Character Recorder,' which features a spreadsheet as the data entry platform and provides authors with the flexibility of using their preferred terminology in recording characters for a set of specimens (this application also facilitates semantic clarity and consistency across species descriptions); a set of services that produce RDF graph data, collects terms added by authors, detects potential conflicts between terms, dispatches conflicts to the third component and updates the ontology with resolutions; and an Android mobile application, 'Conflict Resolver,' which displays ontological conflicts and accepts solutions proposed by multiple experts. a web-based, ontology-aware software application called 'Character Recorder,' which features a spreadsheet as the data entry platform and provides authors with the flexibility of using their preferred terminology in recording characters for a set of specimens (this application also facilitates semantic clarity and consistency across species descriptions); a set of services that produce RDF graph data, collects terms added by authors, detects potential conflicts between terms, dispatches conflicts to the third component and updates the ontology with resolutions; and an Android mobile application, 'Conflict Resolver,' which displays ontological conflicts and accepts solutions proposed by multiple experts. Fig. 1 shows the system diagram of the platform. The presentation will consist of: a report on the findings from a recent survey of 90+ participants on the need for a tool like Character Recorder; a methods section that describes how we provide semantics to an existing vocabulary of quantitative characters through a set of properties that explain where and how a measurement (e.g., length of perigynium beak) is taken. We also report on how a custom color palette of RGB values obtained from real specimens or high-quality specimen images, can be used to help authors choose standardized color descriptions for plant specimens; and a software demonstration, where we show how Character Recorder and Conflict Resolver can work together to construct both human-readable descriptions and RDF graphs using morphological data derived from species in the plant genus Carex (sedges). The key difference of this system from other ontology-aware systems is that authors can directly add needed terms to the ontology as they wish and can update their data according to ontology updates. a report on the findings from a recent survey of 90+ participants on the need for a tool like Character Recorder; a methods section that describes how we provide semantics to an existing vocabulary of quantitative characters through a set of properties that explain where and how a measurement (e.g., length of perigynium beak) is taken. We also report on how a custom color palette of RGB values obtained from real specimens or high-quality specimen images, can be used to help authors choose standardized color descriptions for plant specimens; and a software demonstration, where we show how Character Recorder and Conflict Resolver can work together to construct both human-readable descriptions and RDF graphs using morphological data derived from species in the plant genus Carex (sedges). The key difference of this system from other ontology-aware systems is that authors can directly add needed terms to the ontology as they wish and can update their data according to ontology updates. The software modules currently incorporated in Character Recorder and Conflict Resolver have undergone formal usability studies. We are actively recruiting Carex experts to participate in a 3-day usability study of the entire system of the Platform for Author-Driven Computable Data and Ontology Production for Taxonomists. Participants will use the platform to record 100 characters about one Carex species. In addition to usability data, we will collect the terms that participants submit to the underlying ontology and the data related to conflict resolution. Such data allow us to examine the types and the quantities of logical conflicts that may result from the terms added by the users and to use Discrete Event Simulation models to understand if and how term additions and conflict resolutions converge. We look forward to a discussion on how the tools (Character Recorder is online at http://shark.sbs.arizona.edu/chrecorder/public) described in our presentation can contribute to producing and publishing FAIR data in taxonomic studies. 

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3. Zero-Shot Reward Specification via Grounded Natural Language

   Parsa Mahmoudieh; Deepak Pathak; Trevor Darrell (July 2022, International Conference on Machine Learning)

   Reward signals in reinforcement learning are expensive to design and often require access to the true state which is not available in the real world. Common alternatives are usually demonstrations or goal images which can be labor-intensive to collect. On the other hand, text descriptions provide a general, natural, and low-effort way of communicating the desired task. However, prior works in learning text-conditioned policies still rely on rewards that are defined using either true state or labeled expert demonstrations. We use recent developments in building large-scale visuolanguage models like CLIP to devise a framework that generates the task reward signal just from goal text description and raw pixel observations which is then used to learn the task policy. We evaluate the proposed framework on control and robotic manipulation tasks. Finally, we distill the individual task policies into a single goal text conditioned policy that can generalize in a zero-shot manner to new tasks with unseen objects and unseen goal text descriptions. 

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4. Households’ Intended Evacuation Transportation Behavior in Response to Earthquake and Tsunami Hazard in a Cascadia Subduction Zone City

   https://doi.org/10.1177/0361198120920873  

   Chen, Chen; Buylova, Alexandra; Chand, Cadell; Wang, Haizhong; Cramer, Lori A.; Cox, Daniel T. (July 2020, Transportation Research Record: Journal of the Transportation Research Board)

   null (Ed.)

   Earthquakes along the Cascadia subduction zone would generate a local tsunami that could arrive at coastlines within minutes. Few studies provide empirical evidence to understand the potential behaviors of local residents during this emergency. To fill this knowledge gap, this study examines residents’ perceptions and intended evacuation behaviors in response to an earthquake and tsunami, utilizing a survey sent to households in Seaside, OR. The results show that the majority of respondents can correctly identify whether their house is inside or outside a tsunami inundation zone. Older respondents are more likely to identify this correctly regardless of any previous disaster evacuation experience or community tenure. The majority of respondents (69%) say they would evacuate in the event of a tsunami. Factors influencing this choice include age, motor ability, access to transportation, and trust in infrastructure resiliency or traffic conditions. While the City of Seaside actively promotes evacuation by foot, 38% of respondents still state they would use a motor vehicle to evacuate. Females and older respondents are more likely to evacuate by foot. Respondents with both higher confidence in their knowledge of disaster evacuation and higher income are more likely to indicate less time needed to evacuate than others. Generally, respondents are more likely to lead rather than follow during an evacuation, especially respondents who report being more prepared for an evacuation and who have a higher perceived risk. This study showcases a unique effort at empirically analyzing human tsunami evacuation lead or follow choice behavior. 

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5. Opening the Door to Registered Reports: Census of Journals Publishing Registered Reports (2013–2020)

   https://doi.org/10.1525/collabra.24404  

   Montoya, Amanda Kay; Krenzer, William Leo; Fossum, Jessica Louise (January 2021, Collabra: Psychology)

   Registered reports are a new publication workflow where the decision to publish is made prior to data collection and analysis and thus cannot be dependent on the outcome of the study. An increasing number of journals have adopted this new mechanism, but previous research suggests that submission rates are still relatively low. We conducted a census of journals publishing registered reports (N = 278) using independent coders to collect information from submission guidelines, with the goal of documenting journals’ early adoption of registered reports. Our results show that the majority of journals adopting registered reports are in psychology, and it typically takes about a year to publish the first registered report after adopting. Still, many journals have not published their first registered report. There is high variability in impact of journals adopting registered reports. Many journals do not include concrete information about policies that address concerns about registered reports (e.g., exploratory analysis); however, those that do typically allow these practices with some restrictions. Additionally, other open science practices are commonly encouraged or required as part of the registered report process, especially open data and materials. Overall, many journals did not include many of the fields coded by the research team, which could be a barrier to submission for some authors. Though the majority of journals allow authors to be anonymous during the review process, a sizable portion do not, which could also be a barrier to submission. We conclude with future directions and implications for authors of registered reports, journals that have already adopted registered reports, and journals that may consider adopting registered reports in the future. 

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