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Classification of web-based Digital Humanities projects leveraging information visualisation techniques
<h2>Description</h2> <p>This dataset contains a list of 186 Digital Humanities projects leveraging information visualisation methods. Each project has been classified according to visualisation and interaction techniques, narrativity and narrative solutions, domain, methods for the representation of uncertainty and interpretation, and the employment of critical and custom approaches to visually represent humanities data.</p> <p> </p> <h2>Classification schema: categories and columns</h2> <p>The <code>project_id</code> column contains unique internal identifiers assigned to each project. Meanwhile, the <code>last_access</code> column records the most recent date (in DD/MM/YYYY format) on which each project was reviewed based on the web address specified in the <code>url</code> column.<br>The remaining columns can be grouped into descriptive categories aimed at characterising projects according to different aspects:</p> <p> </p> <p><strong>Narrativity.</strong> It reports the presence of information visualisation techniques employed within narrative structures. Here, the term narrative encompasses both author-driven linear data stories and more user-directed experiences where the narrative sequence is determined by user exploration [1]. We define 2 columns to identify projects using visualisation techniques in narrative, or non-narrative sections. Both conditions can be true for projects employing visualisations in both contexts. Columns:</p> <ul> <li> <p><code>non_narrative</code> (boolean)</p> </li> <li> <p><code>narrative</code> (boolean)</p> </li> </ul> <p> </p> <p><strong>Domain.</strong> The humanities domain to which the project is related. We rely on [2] and the chapters of the first part of [3] to abstract a set of general domains. Column:</p> <ul> <li> <p><code>domain</code> (categorical):</p> </li> <ul> <li> <p>History and archaeology</p> </li> <li> <p>Art and art history</p> </li> <li> <p>Language and literature</p> </li> <li> <p>Music and musicology</p> </li> <li> <p>Multimedia and performing arts</p> </li> <li> <p>Philosophy and religion</p> </li> <li> <p>Other: both extra-list domains and cases of collections without a unique or specific thematic focus.</p> </li> </ul> </ul> <p> </p> <p><strong>Visualisation of uncertainty and interpretation.</strong> Buiding upon the frameworks proposed by [4] and [5], a set of categories was identified, highlighting a distinction between precise and impressional communication of uncertainty. Precise methods explicitly represent quantifiable uncertainty such as missing, unknown, or uncertain data, precisely locating and categorising it using visual variables and positioning. Two sub-categories are interactive distinction, when uncertain data is not visually distinguishable from the rest of the data but can be dynamically isolated or included/excluded categorically through interaction techniques (usually filters); and visual distinction, when uncertainty visually “emerges” from the representation by means of dedicated glyphs and spatial or visual cues and variables. On the other hand, impressional methods communicate the constructed and situated nature of data [6], exposing the interpretative layer of the visualisation and indicating more abstract and unquantifiable uncertainty using graphical aids or interpretative metrics. Two sub-categories are: ambiguation, when the use of graphical expedients—like permeable glyph boundaries or broken lines—visually convey the ambiguity of a phenomenon; and interpretative metrics, when expressive, non-scientific, or non-punctual metrics are used to build a visualisation. Column:</p> <ul> <li> <p><code>uncertainty_interpretation</code> (categorical):</p> </li> <ul> <li> <p>Interactive distinction</p> </li> <li> <p>Visual distinction</p> </li> <li> <p>Ambiguation</p> </li> <li> <p>Interpretative metrics</p> </li> </ul> </ul> <p> </p> <p><strong>Critical adaptation.</strong> We identify projects in which, with regards to at least a visualisation, the following criteria are fulfilled: 1) avoid repurposing of prepackaged, generic-use, or ready-made solutions; 2) being tailored and unique to reflect the peculiarities of the phenomena at hand; 3) avoid simplifications to embrace and depict complexity, promoting time-consuming visualisation-based inquiry. Column:</p> <ul> <li> <p><code>critical_adaptation</code> (boolean)</p> </li> </ul> <p> </p> <p><strong>Non-temporal visualisation techniques.</strong> We adopt and partially adapt the terminology and definitions from [7]. A column is defined for each type of visualisation and accounts for its presence within a project, also including stacked layouts and more complex variations. Columns and inclusion criteria:</p> <ul> <li> <p><code>plot</code> (boolean): visual representations that map data points onto a two-dimensional coordinate system.</p> </li> <li> <p><code>cluster_or_set</code> (boolean): sets or cluster-based visualisations used to unveil possible inter-object similarities.</p> </li> <li> <p><code>map</code> (boolean): geographical maps used to show spatial insights. While we do not specify the variants of maps (e.g., pin maps, dot density maps, flow maps, etc.), we make an exception for maps where each data point is represented by another visualisation (e.g., a map where each data point is a pie chart) by accounting for the presence of both in their respective columns.</p> </li> <li> <p><code>network</code> (boolean): visual representations highlighting relational aspects through nodes connected by links or edges.</p> </li> <li> <p><code>hierarchical_diagram</code> (boolean): tree-like structures such as tree diagrams, radial trees, but also dendrograms. They differ from networks for their strictly hierarchical structure and absence of closed connection loops.</p> </li> <li> <p><code>treemap</code> (boolean): still hierarchical, but highlighting quantities expressed by means of area size. It also includes circle packing variants.</p> </li> <li> <p><code>word_cloud</code> (boolean): clouds of words, where each instance’s size is proportional to its frequency in a related context</p> </li> <li> <p><code>bars</code> (boolean): includes bar charts, histograms, and variants. It coincides with “bar charts” in [7] but with a more generic term to refer to all bar-based visualisations.</p> </li> <li> <p><code>line_chart</code> (boolean): the display of information as sequential data points connected by straight-line segments.</p> </li> <li> <p><code>area_chart</code> (boolean): similar to a line chart but with a filled area below the segments. It also includes density plots.</p> </li> <li> <p><code>pie_chart</code> (boolean): circular graphs divided into slices which can also use multi-level solutions.</p> </li> <li> <p><code>plot_3d</code> (boolean): plots that use a third dimension to encode an additional variable.</p> </li> <li> <p><code>proportional_area</code> (boolean): representations used to compare values through area size. Typically, using circle- or square-like shapes.</p> </li> <li> <p><code>other</code> (boolean): it includes all other types of non-temporal visualisations that do not fall into the aforementioned categories.</p> </li> </ul> <p> </p> <p><strong>Temporal visualisations and encodings.</strong> In addition to non-temporal visualisations, a group of techniques to encode temporality is considered in order to enable comparisons with [7]. Columns:</p> <ul> <li> <p><code>timeline</code> (boolean): the display of a list of data points or spans in chronological order. They include timelines working either with a scale or simply displaying events in sequence. As in [7], we also include structured solutions resembling Gantt chart layouts.</p> </li> </ul> <ul> <li> <p><code>temporal_dimension</code> (boolean): to report when time is mapped to any dimension of a visualisation, with the exclusion of timelines. We use the term “dimension” and not “axis” as in [7] as more appropriate for radial layouts or more complex representational choices.</p> </li> <li> <p><code>animation</code> (boolean): temporality is perceived through an animation changing the visualisation according to time flow.</p> </li> <li> <p><code>visual_variable</code> (boolean): another visual encoding strategy is used to represent any temporality-related variable (e.g., colour).</p> </li> </ul> <p> </p> <p><strong>Interaction techniques.</strong> A set of categories to assess affordable interaction techniques based on the concept of user intent [8] and user-allowed data actions [9]. The following categories roughly match the “processing”, “mapping”, and “presentation” actions from [9] and the manipulative subset of methods of the “how” an interaction is performed in the conception of [10]. Only interactions that affect the visual representation or the aspect of data points, symbols, and glyphs are taken into consideration. Columns:</p> <ul> <li> <p><code>basic_selection</code> (boolean): the demarcation of an element either for the duration of the interaction or more permanently until the occurrence of another selection.</p> </li> <li> <p><code>advanced_selection</code> (boolean): the demarcation involves both the selected element and connected elements within the visualisation or leads to brush and link effects across views. Basic selection is tacitly implied.</p> </li> <li> <p><code>navigation</code> (boolean): interactions that allow moving, zooming, panning, rotating, and scrolling the view but only when applied to the visualisation and not to the web page. It also includes “drill” interactions (to navigate through different levels or portions of data detail, often generating a new view that replaces or accompanies the original) and “expand” interactions generating new perspectives on data by expanding and collapsing nodes.</p> </li> <li> <p><code>arrangement</code> (boolean): methods to organise visualisation elements (symbols, glyphs, etc.) or multi-visualisation layouts spatially through drag and drop or according to a criterion via more automatic triggers.</p> </li> <li> <p><code>change</code> (boolean): visual encoding alterations involving different aspects of visualisation as a whole: the same content is presented with another visualisation technique; the change involves symbols or glyphs aspect (colour, size, shape, etc.); the visualisation type is unaltered, but the layout variant changes (e.g., to stacked layouts); or other changes like axes inversion and scale modifications. The presence of all the visualisation techniques involved in a change is reported.</p> </li> <li> <p><code>visualisation_filter</code> (boolean): filters to exclude or include visualisation elements with respect to defined criteria, without reloading or generating a new visualisation. Unlike options triggering the fetch of new data to alter the visualisation content, filters seamlessly operate on existing visual elements.</p> </li> <li> <p><code>collection_filter</code> (boolean): the interaction with visualised elements acts as a filter for a related collection or list of items (e.g., clicking a region on a map filters a list of items according to spatial metadata).</p> </li> <li> <p><code>aggregation</code> (boolean): changes to the granularity of visual elements according to a variable. It produces either visual data summarisations or segregations.</p> </li> <li> <p><code>btfw_interaction</code> (boolean): to identify the use of “breaking the fourth wall interactions” as defined [11]. It applies only to narratives.</p> </li> </ul> <p> </p> <p><strong>Narrative flow factors.</strong> Other categories aim to identify patterns in the design of narrative solutions. It is worth noticing that a project with multiple and diverse narratives can potentially report multiple design choices for the same column. Part of the factors and definitions from [12] are here re-used and adapted.</p> <p><em>Story layout </em>columns define the layout, or genre, of the narrative format:</p> <ul> <li> <p><code>document_layout</code> (boolean)</p> </li> <li> <p><code>slideshow_layout</code> (boolean)</p> </li> <li> <p><code>hybrid_layout</code> (boolean): mixing document and slideshow layouts.</p> </li> <li> <p><code>other_layout</code> (boolean): more complex solutions.</p> </li> </ul> <p><em>Role of visualisation</em> columns describe the role visualisations detain with respect to the entire story, in particular, with reference to the textual part of the narratives:</p> <ul> <li><code>equal_role</code> (boolean): visualisations and text play an equal role in the narrative.</li> <li><code>figure_role</code> (boolean): visualisations are supporting elements compared to the role of text.</li> <li><code>annotated_role</code> (boolean): visualisations are the drivers of the narrative.</li> </ul> <p><em>Story progression</em> columns categorise the shape of possible story paths:</p> <ul> <li> <p><code>linear_progression</code> (categorical): strongly author-driven or user-directed narrative. Possible values specify the potential to skip certain parts while not having a fully explorative experience:</p> </li> <ul> <li> <p>Skip</p> </li> <li> <p>No-skip</p> </li> </ul> <li> <p><code>user_directed</code> (bool): users can select a path among multiple alternatives and compose narrative pieces, providing a broder degree of interaction and exploration possibilities [1]. If a linear path can be suggested, here it remains merely one option among many others. Differently from a linear-skip approach, it has a low level of guidance oriented towards linear navigation.</p> </li> </ul> <p><em>Navigation input </em>columns define the ways users can move through the narrative:</p> <ul> <li> <p><code>button_input</code> (boolean)</p> </li> <li> <p><code>scroll_input</code> (boolean)</p> </li> <li> <p><code>slider_input</code> (boolean)</p> </li> </ul> <p><em>Navigation progress </em>columns describe methods through which the reader perceives its placement within the narrative:</p> <ul> <li> <p><code>text_progression</code> (boolean): text or numbers act as signifiers for user position.</p> </li> <li> <p><code>dots_progression</code> (boolean)</p> </li> <li> <p><code>visualisation_progression</code> (boolean): the visualisation used in the narrative, or a visualised progress widget acts as a signifier for user position.</p> </li> </ul> <p><em>Level of control </em>columns describe how much control a reader has over the text, visualisations, and animated transitions. Control could be discrete (D) when it triggers the motion, continuous (C) when it can act throughout all the keyframes, or hybrid (H) if it supports aspects of both. When animation is absent, control can be not available (NA). In particular, while visualisation control is related to the visualisation as a whole (e.g., the entire scatter plot moving up or down the page), the animated transition is related to more specific, data-relevant motion.<br>Columns:</p> <ul> <li> <p><code>text_control</code> (categorical):</p> </li> <ul> <li> <p>D</p> </li> <li> <p>C</p> </li> <li> <p>H</p> </li> </ul> <li> <p><code>visualisation_control</code> (categorical):</p> </li> <ul> <li> <p>D</p> </li> <li> <p>C</p> </li> <li> <p>H</p> </li> </ul> <li> <p><code>animation_control</code> (categorical):</p> </li> <ul> <li> <p>D</p> </li> <li> <p>C</p> </li> <li> <p>H</p> </li> <li> <p>NA</p> </li> </ul> </ul> <p> </p> <h2>References</h2> <p>[1] E. Segel and J. Heer, “Narrative Visualization: Telling Stories with Data,” IEEE Trans. Visual. Comput. Graphics, vol. 16, no. 6, pp. 1139–1148, 2010, doi: 10.1109/TVCG.2010.179.</p> <p>[2] M. Terras, J. Nyhan, and E. Vanhoutte, Defining Digital Humanities: A Reader. Routledge, 2016.</p> <p>[3] S. Schreibman, R. G. Siemens, and J. Unsworth, Eds., A companion to digital humanities. in Blackwell companions to literature and culture, no. 26. Malden, MA: Blackwell Pub, 2004.</p> <p>[4] C. Kinkeldey, A. M. MacEachren, and J. Schiewe, “How to Assess Visual Communication of Uncertainty? A Systematic Review of Geospatial Uncertainty Visualisation User Studies,” The Cartographic Journal, vol. 51, no. 4, pp. 372–386, 2014, doi: 10.1179/1743277414Y.0000000099.</p> <p>[5] G. Panagiotidou, H. Lamqaddam, J. Poblome, K. Brosens, K. Verbert, and A. Vande Moere, “Communicating Uncertainty in Digital Humanities Visualization Research,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 1, pp. 635–645, Jan. 2023, doi: 10.1109/TVCG.2022.3209436.</p> <p>[6] J. Drucker, “Humanities Approaches to Graphical Display,” Digital Humanities Quarterly, vol. 5, no. 1, 2011, Accessed: Sep. 17, 2024. [Online]. Available: <a href="https://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html">https://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html</a></p> <p>[7] F. Windhager et al., “Visualization of Cultural Heritage Collection Data: State of the Art and Future Challenges,” IEEE Trans. Visual. Comput. Graphics, vol. 25, no. 6, pp. 2311–2330, Jun. 2019, doi: 10.1109/TVCG.2018.2830759.</p> <p>[8] J. S. Yi, Y. A. Kang, J. Stasko, and J. A. Jacko, “Toward a Deeper Understanding of the Role of Interaction in Information Visualization,” IEEE Trans. Visual. Comput. Graphics, vol. 13, no. 6, pp. 1224–1231, 2007, doi: 10.1109/TVCG.2007.70515.</p> <p>[9] E. Dimara and C. Perin, “What is Interaction for Data Visualization?,” IEEE Transactions on Visualization and Computer Graphics, vol. 26, no. 1, pp. 119–129, Jan. 2020, doi: 10.1109/TVCG.2019.2934283.</p> <p>[10] M. Brehmer and T. Munzner, “A Multi-Level Typology of Abstract Visualization Tasks,” IEEE Trans. Visual. Comput. Graphics, vol. 19, no. 12, pp. 2376–2385, 2013, doi: 10.1109/TVCG.2013.124.</p> <p>[11] Y. Shi, T. Gao, X. Jiao, and N. Cao, “Breaking the Fourth Wall of Data Stories Through Interaction,” IEEE Trans. Visual. Comput. Graphics, pp. 1–11, 2022, doi: 10.1109/TVCG.2022.3209409.</p> <p>[12] S. McKenna, N. Henry Riche, B. Lee, J. Boy, and M. Meyer, “Visual Narrative Flow: Exploring Factors Shaping Data Visualization Story Reading Experiences,” Computer Graphics Forum, vol. 36, no. 3, pp. 377–387, 2017, doi: 10.1111/cgf.13195.</p> <p> </p> <h2>Fundings</h2> <p>Project funded by the European Union – NextGenerationEU under the National Recovery and Resilience Plan (NRRP), Investment I.4.1 - Borse PNRR Patrimonio Culturale.</p>
Minimal data set for "Cohort profile: The ENTWINE iCohort Study, a multinational longitudinal web-based study of informal care"
<p><strong>Title:</strong></p> <p>Minimal Data Set for the Reproduction of Findings in "Elayan et al., Cohort Profile: The ENTWINE iCohort Study, a Multinational Longitudinal Web-Based Study of Informal Care".</p> <p> </p> <p><strong>Study Summary:</strong></p> <p>The data sets provided herein are derived from the ENTWINE iCohort Study, a multinational web-based cohort study employing an intensive longitudinal design. The study integrates a two-wave panel survey (baseline and 6-month follow-up) with optional weekly diary assessments. The cohort comprises caregivers and care recipients from nine countries: the United Kingdom, the Netherlands, Italy, Sweden, Israel, Germany, Greece, Poland, and Ireland. The study aimed to examine the influence of personal, psychological, social, economic, and geographic factors on caregiving experiences.</p> <p>Participants were eligible if they met the following criteria: 1) residency in a participating country; 2) capability to respond to surveys in English, Swedish, German, Dutch, Italian, Greek, Hebrew, or Polish; 3) access to the internet and ability to use it; 4) at least 18 years of age; 5) self-declared cognitive and physical capacity to complete the surveys; 6) either providing care to an adult (aged ≥ 18 years) with a chronic health condition, disability, or other care need, or receiving care from an adult due to similar conditions.</p> <p>The detailed methodology and results of the study can be found in the associated manuscript. For the complete survey questionnaires, please refer to: Morrison V, Zarzycki M, Vilchinsky N, Sanderman R, Lamura G, Fisher O, et al. A Multinational Longitudinal Study Incorporating Intensive Methods to Examine Caregiver Experiences in the Context of Chronic Health Conditions: Protocol of the ENTWINE-iCohort. Int J Environ Res Public Health. 2022;19. doi: <a href="https://doi.org/10.3390/ijerph19020821">10.3390/ijerph19020821</a></p> <p> </p> <p><strong>Data files:</strong></p> <p>The repository contains the following data files:</p> <ol> <li>"cg_minimal_dataset" (available in dta, sav, rds, and xlsx formats): This is a minimal data set containing de-identified and processed data derived from the ENTWINE iCohort Caregiver Baseline Survey. The variables present in this data set are detailed in the associated codebook, "cg_minimal_dataset_codebook".</li> <li>"cr_minimal_dataset" (available in dta, sav, rds, and xlsx formats): This is a minimal data set containing de-identified and processed data derived from the ENTWINE iCohort Care Recipient Baseline Survey. The variables present in this data set are detailed in the associated codebook, "cr_minimal_dataset_codebook".</li> </ol>
Hypernym-LIBre: A free Web-based corpus from Hypernym Detection [ Hearst Pattern extractions from Hypernym-LIBre]
<p>Hypernym-LIBre ( DOI: 10.5281/zenodo.3662204 ) is a free Web-based corpus for Hypernym detection.</p> <p>Its part-of-speech tagged and dependency annotated version is present at this: (DOI: 10.5281/zenodo.3689303)</p> <p>Here we provide the hypernym-hyponym pairs that were extracted from Hypernym-LIBre using Hearst patterns. This is to further the usage of these extractions with more techniques and methods. We also provide the counts of each pattern in a separate file.</p> <p> </p> <p>Format:</p> <p>hyponym \t hypernym</p> <p> </p> <p>Format for the counts file:</p> <p>pair \t frequency of extraction</p> <p> </p> <p>There are 2 files, one with the pairs, one with unique pair and its counts. Both total ~430MB.</p>
CanVaxKB: A Web-based Cancer Vaccine Knowledgebase
<p>CanVaxKB is a web-based cancer vaccine knowledgebase. CanVaxKB collects, annotates and analyzes various types of cancer vaccines around the world. Currently it contains all cancer vaccines stored in the VIOLIN vaccine database. CanVaxKB also provides a user-friendly web interface for users to interactively search, compare, and analyze different cancer vaccines. The CanVaxKB website is here: https://violinet.org/canvaxkb. </p> <p>The Vaccine Ontology (VO) also includes the CanVaxKB stored cancer vaccine information, which is accessible at: https://github.com/vaccineontology/VO. </p> <p>The four supplemental files provided here are for the NCI Cancer paper about CanVaxKB. The citation for the CanVaxKB NCI Cancer is here:</p> <p>Eliyas Asfaw*, Asiyah Yu Lin*, Anthony Huffman*, Siqi Li*, Madison George*, Chloe Darancou, Madison Kalter, Nader Wehbi, Davis Bartels, Elyse Fleck, Nancy Tran, Daniel Faghihnia, Kimberly Berke, Ronak Sutariya, Farah Reyal, Youssef Tammam, Bin Zhao, Edison Ong, Zuoshuang Xiang, Virginia He, Justin Song, Andrey I. Seleznev, Jinjing Guo, Yuanyi Pan, Jie Zhang, Yongqun He. CanVaxKB: A Web-based Cancer Vaccine Knowledgebase. NCI Cancer. In press. </p>
Web-based Editor for Entity-Relationship Modeling with SQL Transformation Algorithm
<p>With the daily growth of data in all kinds of sectors, such as <span>Information Technolo</span><span>gies (IT)</span>, healthcare, education, commerce or telecommunication, it becomes important to use a high-performance system to manage all this data in the best possible way. Indeed, in the absence of good data management, it can be difficult for these sectors to prevent data loss, ensure safe maintenance or guarantee data security. For this reason, an effective data management system is the Entity-Relationship model. Indeed, thanks to this model, all kinds of sectors have the possibility of designing and organizing their data in relational databases, thus improving data security and better internal communication. Furthermore, it is interesting to modernize the classic approach of the Entity-Relationship model and its visual representations of data in the present day. The technologies of Augmented and Virtual Reality respond precisely to this challenge of innovation in the Entity-Relationship model. Therefore, the first objective of this thesis is to implement the Entity-Relationship model in a Meta-Modeling Platform for Augmented and Virtual Reality. The second objective is to implement an algorithm that transforms an Entity-Relationship model into SQL statements to create database tables. The Entity-Relationship model is used to design the logic of a database, and the implementation of the algorithm is used to create the database.</p>
InnoRate_Multi-component web-based survey_Dataset4_2021.12.28_v1
<p>This dataset has been collected by deploying an online survey to gather insight and analyse the needs and preferences of potential users and stakeholders of the InnoRate Platform of the InnoRate Project (H2020 GA 821518). We have gathered responses from 3 main stakeholder groups, namely innovators, investors and innovation intermediaries. The surveys for each stakeholder group (.docx format), along with the respective anonymised version of their responses (.xlsx format) are uploaded on Zenodo.</p>
A web-based tool for automatically linking clinical trials to their publications - example calculation
<p><strong>Objective</strong>: Evidence synthesis teams, physicians, policy makers, and patients and their families all have an interest in following the outcomes of clinical trials and would benefit from being able to evaluate both the results posted in trial registries and in the publications that arise from them. Manual searching for publications arising from a given trial is a laborious and uncertain process. We sought to create a statistical model to automatically identify PubMed articles likely to report clinical outcome results from each registered trial in ClinicalTrials.gov.</p> <p><strong>Materials and Methods</strong>: A machine learning-based model was trained on pairs (publications linked to specific registered trials). Multiple features were constructed based on the degree of matching between the PubMed article metadata and specific fields of the trial registry, as well as matching with the set of publications already known to be linked to that trial.</p> <p><strong>Results</strong>: Evaluation of the model using NCT-linked articles as gold standard showed that they tend to be top ranked (median best rank = 1.0), and 91% of them are ranked in the top ten.</p> <p><strong>Discussion</strong>: Based on this model, we have created a free, public web based tool at http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi that, given any registered trial in ClinicalTrials.gov, presents a ranked list of the PubMed articles in order of estimated probability that they report clinical outcome data from that trial. The tool should greatly facilitate studies of trial outcome results and their relation to the original trial designs.</p>
MetaPro: a web-based metabolomics application for MS data batch inspection and library curation
<p>MetaPro is a metabolomics web analysis platform built on the Aird data format with high performance and high compression. This platform includes a series of necessary functions for metabolomics analysis such as quality control, retention time(RT) alignment, target analysis, untarget analysis, manual integration, batch inspection, MS2 library establishment, and report export, providing efficient data analysis, management and visualization capabilities</p>
How Confidence in Prior Attitudes, Social Tag Popularity, and Source Credibility Shape Confirmation Bias Toward Antidepressants and Psychotherapy in a Representative German Sample: Randomized Controlled Web-Based Study
<p>ABSTRACT</p> <p>Background: In health-related, Web-based information search, people should select information in line with expert (vs nonexpert) information, independent of their prior attitudes and consequent confirmation bias.</p> <p>Objective: This study aimed to investigate confirmation bias in mental health–related information search, particularly (1) if high confidence worsens confirmation bias, (2) if social tags eliminate the influence of prior attitudes, and (3) if people successfully distinguish high and low source credibility.</p> <p>Methods: In total, 520 participants of a representative sample of the German Web-based population were recruited via a panel company. Among them, 48.1% (250/520) participants completed the fully automated study. Participants provided <em>prior attitudes</em> about antidepressants and psychotherapy. We manipulated (1) <em>confidence</em> in prior attitudes when participants searched for blog posts about the treatment of depression, (2) <em>tag popularity</em> —either psychotherapy or antidepressant tags were more popular, and (3) <em>source credibility</em> with banners indicating high or low expertise of the tagging community. We measured <em>tag</em> and <em>blog post</em> selection, and <em>treatment</em><em>efficacy ratings</em> after navigation.</p> <p>Results: Tag popularity predicted the proportion of selected antidepressant tags (beta=.44, SE 0.11; <em>P</em><.001) and blog posts (beta=.46, SE 0.11; <em>P</em><.001). When confidence was low (−1 SD), participants selected more blog posts consistent with prior attitudes (beta=−.26, SE 0.05; <em>P</em><.001). Moreover, when confidence was low (−1 SD) and source credibility was high (+1 SD), the efficacy ratings of attitude-consistent treatments increased (beta=.34, SE 0.13; <em>P</em>=.01).</p> <p>Conclusions: We found correlational support for defense motivation account underlying confirmation bias in the mental health–related search context. That is, participants tended to select information that supported their prior attitudes, which is not in line with the current scientific evidence. Implications for presenting persuasive Web-based information are also discussed.</p> <p>Trial Registration: ClinicalTrials.gov NCT03899168; https://clinicaltrials.gov/ct2/show/NCT03899168 (Archived by WebCite at http://www.webcitation.org/77Nyot3Do)</p> <p>J Med Internet Res 2019;21(4):e11081</p> <p>doi:10.2196/11081</p>
Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information and Social Tags on Information Search and Evaluation
<p>ABSTRACT</p> <p>Background: The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective.</p> <p>Objective: The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts’ evaluations.</p> <p>Methods: A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts’ blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants’ treatment recommendation after information search.</p> <p>Results: Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; <em>t</em><sub>173</sub>=7.67, <em>P</em><.001, <em>d</em>=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (<em>F</em><sub>2,168</sub>=10.61, <em>P</em><.001, partial eta squared=0.112), blog post selection (<em>F</em><sub>2,168</sub>=6.55, <em>P</em>=.002, partial eta squared=0.072), and treatment efficacy ratings (<em>F</em><sub>2,168</sub>=8.48, <em>P</em><.001, partial eta squared=0.092), compared to bias-supporting tag clouds (n=56) and balanced tag clouds (n=57). Challenging (n=93) explicit expert information as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (<em>F</em><sub>1,168</sub>=4.32, <em>P</em>=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (<em>P</em>s>.33).</p> <p>Conclusions: We conclude that the psychotherapy bias is most effectively attenuated—and even eliminated—when popular tags implicitly point to blog posts that challenge the widespread view. Explicit expert information (in a blog entry) was less successful in reducing biased information search and evaluation. Since tag clouds have the potential to counter biased information processing, we recommend their insertion.</p>
Data from: Koe: Web-based software to classify acoustic units and analyse sequence structure in animal vocalisations
<p>1. Classifying acoustic units is often a key step in studying repertoires and sequence structure in animal communication. Manual classification by eye and ear remains the primary method, but new tools and techniques are urgently needed to expedite the process for large, diverse datasets.</p> <p>2. Here we introduce <i>Koe</i>, an application for classifying and analysing animal vocalisations. <i>Koe</i> offers bulk-labelling of units via interactive ordination plots and unit tables, as well as visualisation and playback, segmentation, measurement, data filtering/exporting and new tools for analysing repertoire and sequence structure—in an integrated environment.</p> <p>3. We demonstrate <i>Koe</i> with a real-world case study of New Zealand bellbird <i>Anthornis melanura</i> songs from an archipelago metapopulation. Having classified 21,500 units in <i>Koe</i>, we compare repertoires and sequence structure between sites and sexes.</p> <p>4. <i>Koe</i> is web-based (koe.io.ac.nz) and easy to use, making it ideal for collaboration, education and citizen science. By enabling large-scale, high-resolution classification and analysis of animal vocalisations, <i>Koe</i> expands the possibilities for bioacoustics research.</p>
Example ScRNAseq Dataset 1 for Learning Web-based Tools
<p>This is one of the three example ScRNAseq datasets used to follow the guided example analyses within "A Guide to Single-Cell RNA Sequencing Analysis Using Web-based Tools for Non-Bioinformaticians" in the FEBS Journal. This dataset can be downloaded and imported into a variety of web-based tools and used as a learning device to gain more familiarity with the tools. As described in the paper, this dataset represents the untreated control. </p>
Example ScRNAseq Dataset 2 for Learning Web-based Tools
<p>This is one of the three example ScRNAseq datasets used to follow the guided example analyses within "A Guide to Single-Cell RNA Sequencing Analysis Using Web-based Tools for Non-Bioinformaticians" in the FEBS Journal. This dataset can be downloaded and imported into a variety of web-based tools and used as a learning device to gain more familiarity with the tools. As described in the paper, this dataset represents the negative control (carrier only). </p>
Enhancing Survivorship Care Planning for Patients With Localized Prostate Cancer Using A Couple-focused Web-based Tailored Symptom Self-management Program
ClinicalTrials.gov study NCT04350788. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Koe: Web-based software to classify acoustic units and analyse sequence structure in animal vocalisations
Open the record for dataset details and reuse information.
A web-based tool for automatically linking clinical trials to their publications - example calculation
Open the record for dataset details and reuse information.
Hypernym-LIBre: A free Web-based Corpus for Hypernym Detection
<p>The task of finding hypernyms from large text corpora is a fundamental problem in NLP. It provides a basis for the main-stream natural language problems in AI. In our paper, we introduce a free new web-based corpus for hypernym detection and we show that using this corpus we achieve similar results to the state-of-the-art pattern-based methods achieved by a well known corpus that is not freely available. The dataset provided here is the one we use in our paper and we provide it with an open license so others can apply different methods and techniques for hypernym detection.</p> <p> </p> <p>The dataset is a combination of UMBC corpus and the Wikipedia corpus. Its dependency parsed and POS-tagged versions are available at this DOI: 10.5281/zenodo.3689303</p> <p>Contents:</p> <p>Hypernym-LIBre.zip 11.3GB compresssed, 32GB uncompressed raw text</p> <p>288 files of ~110 MB each</p> <p> </p> <p>10.5281/zenodo.3689303</p> <p>PoS and dep annotated</p> <p>~15GB compressed, 80GB uncompressed, 442 files of ~180MB each</p> <p> </p> <pre>10.5281/zenodo.3695237</pre> <p>hyponym-hypernym pairs extracted from Hypernym-LIBre using Hearst patterns</p>
Data from: Use of web-based species occurrence information systems by academics and government professionals
<p>Web-based information systems designed to increase access to species occurrence data for use in research and natural resource decision-making have become more prevalent over the past few decades. The effectiveness of these systems depends on their usability and extent of use by their intended audiences. We conducted an online survey of academics and government professionals in the United States to compare their species occurrence data needs and their perceptions and use of web-based species occurrence information systems. Our results indicate that although views and perceptions held by academics and government professionals about the importance, usefulness, and ease of use of these information systems tend to be similar, there were differences in their use of species occurrence data and web-based species occurrence information systems. The baseline information obtained in this study will help inform future directions for improvements in species occurrence information systems.</p>
Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA
<p>MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs has accelerated with the development of high-throughput small RNA sequencing (sRNA-Seq) techniques and bioinformatics tools. However, generating high-quality comprehensive miRNA annotations remains challenging, due to the intrinsic complexity of sRNA-Seq data and inherent limitations of existing miRNA predictions. Here, we present iwa-miRNA, a Galaxy-based framework that can facilitate miRNA annotation in plant species by combining computational analysis and manual curation. iwa-miRNA is specifically designed to generate a comprehensive list of miRNA candidates, bridging the gap between already annotated miRNAs provided by public miRNA databases and new predictions from sRNA-Seq datasets. It can also assist users to select promising miRNA candidates in an interactive mode through the automated and manual steps, contributing to the accessibility and reproducibility of genome-wide miRNA annotation. iwa-miRNA is user-friendly and can be easily deployed as a web application for researchers without programming experience. With flexible, interactive, and easy-to-use features, iwa-miRNA is a valuable tool for annotation of miRNAs in plant species with reference genomes. We illustrated the application of iwa-miRNA for miRNA annotation of plant species with varying complexity. The sources codes and web server of iwa-miRNA is freely accessible at: <a href="http://iwa-miRNA.omicstudio.cloud">http://iwa-miRNA.omicstudio.cloud</a>/.</p>
A review of the status of web-based African Plant-Pollinator Interaction data
<p>A protocol was developed to collect and mine data from various web-based sources such as journals, web pages, handbooks, manuals and any other source that is web accessible and has information sought. The intention was to collect as much as possible all data with plant-pollinator interaction from studies carried out in Kenya and other parts of Africa. To assure technical support and homogeinity of thoughts, the activity was carried out in a write-shop set up whereby a team of data miners were brought together for 5 days to collect the data. They were trained on the meaning of plant pollinator interactions, key words that should look for, data coverage area, specific sites that are useful and the reporting. Further, monitoring and review of the data collection was continously done, to ensure the right data was collected appropriately. Various search engines were used to collect the data. The data was then prepared in a Globi data base to enhance its use base on the FAIR data principles. The results show that little data exists in Africa on plant-pollinator interaction based on the FAIR data principles. It further shows that Africa need to adopt FAIR principles to enhance utilization of generated data by scientists and expand the benefits of such data in Africa.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.