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189 results for “conceptualization”
Dataset of Measurement and conceptualization of maternal PTSD following childbirth: Psychometric properties of the City Birth Trauma Scale – French version (City BiTS-F)
<p>The City Birth Trauma Scale (City BiTS-F) was developed to assess posttraumatic stress disorder following childbirth (PTSD-FC), based on the PTSD criteria of the DSM-5. Recent studies investigating the latent factor structure of PTSD-FC symptoms in women reported mixed results. Given that no validated French questionnaire exists to measure PTSD-FC symptoms, this study first aimed to validate the French version of the CBTS (City BiTS-F). Second, it aims to establish the latent factor structure of PTSD-FC.</p> <p>This dataset contains data on the mental health (i.e., PTSD-CB, depression, anxiety) of 541 mothers who gave birth during the last 12 months. Sociodemegraphic data such as maternal age, marital status, educational level, parity, gravidity, weeks of gestation, type of delivery, history of traumatic childbirth, or history of traumatic event is available. </p> <p>This dataset is related to: Sandoz, V., Hingray, C., Stuijfzand, S., Lacroix, A., El Hage, W., & Horsch, A. (2022). Measurement and conceptualization of maternal PTSD following childbirth: Psychometric properties of the City Birth Trauma Scale—French Version (City BiTS-F). <em>Psychological Trauma: Theory, Research, Practice, and Policy, 14</em>(4), 696–704. <a href="https://psycnet.apa.org/doi/10.1037/tra0001068">https://doi.org/10.1037/tra0001068</a></p>
Data and code for: A conceptual model-based sediment connectivity assessment for patchy agricultural catchments
<p>Authors: Pedro V G Batista, Peter Fiener, Simon Scheper, Christine Alewell</p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>Abstract</p> <p>The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass buffer strips). Understanding the interactions between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. In specific, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the WaTEM/SEDEM model using high resolution spatial data (2 m x 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km<sup>2</sup>) of the Swiss Plateau. We used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade, which allowed us to investigate the uncertainty in the model structure. Furthermore, we compared model simulations of hillslope sediment yields from five sub-catchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. The sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increases sediment connectivity from hillslopes to surface waters in agricultural landscapes. This further highlights the importance of considering linear landscape features and model structural uncertainty in soil erosion and sediment connectivity research.</p> <p> </p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>Metainformation</p> <p>This dataset includes:</p> <p>1 - The input data used for running the WaTEM/SEDEM model in the Baldegg catchment.</p> <p>2 - The discharge and sediment concentration data used for producing the sediment rating curves for the tributaries of the Lake Baldegg.</p> <p>3 - The model and sediment rating curve output data.</p> <p>4 - The R scripts for running the WaTEM/SEDEM model in the Baldegg catchment, the code for producing the sediment rating curves, and the code for summarising and analysing the model output data.</p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>The sediment concentration and water discharge data were supplied by Robert Lovas, from the Department of Environment and Energy of the Canton of Lucerne.</p> <p>The model input data were adapted from freely available ©swisstopo geodata products:</p> <p>Swisstopo. SwissALTI3D. Das hoch aufgelöste Terrainmodell der Schweiz, 2014.</p> <p>Swisstopo. Swiss Map Vector 25 Beta, Das digitale Landschaftsmodell der Schweiz. 2018.</p> <p>Swisstopo. SwissTLM3D. Das grossmassstäbliche Topografische Landschaftsmodell der Schweiz, 2020.</p> <p>----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>For further information we refer to our preprint: https://doi.org/10.5194/hess-2021-231</p> <p> </p> <p> </p>
Conceptual Model of Neuroblastoma
<p>The following is the Neuroblastoma Conceptual Model (CMN) resulting from the study of the domain and collaborative meetings with clinical experts at Hospital <em>Hospital Universitari y Politècnic de La Fe</em>. Based on a previous CMN [1], the analysis of each of the classes has been carried out, structured in views and extended to adapt it to the new knowledge of the domain.</p>
Taxonomy, distribution and classification of ecosystem-types, integrating the recent IUCN function-based typology and local conceptualizations
<p>1. Introduction:</p> <p>This dataset is a work in progress. It compiles data gathered on ecosystem-types and their distribution based on a series of field studies led by the author, in Seychelles and West and Central Africa (Senterre 2014, Senterre & Wagner 2014, Senterre 2016, Senterre et al. 2017, 2019, 2020, 2021a, 2022). The aims of this dataset are:</p> <p>a. To share in an explicit and transparent way data on proposed taxonomies of ecosystems, i.e. conceptualizations of ecosystem-types, including explicit ecosystem names and management of synonymies.</p> <p>b. To develop ecosystem red listing based on transparent and falsifiable distribution raw data, combining distribution modeling (maps) and in situ observation of individual stand occurrences.</p> <p>c. To illustrate in detail how to deal with ecosystem data following the approach described in Senterre et al. (2021b) (i.e. "ecosystemology" approach).</p> <p>d. To integrate the above approach with the newly developed function-based typology of ecosystems (Keith et al. 2022), therefore contributing to bridging the persistent gap between the global and the local scales in ecosystem descriptions and classifications.</p> <p> </p> <p>2. Context and versions:</p> <p>This dataset was initially planned for publication on GBIF (Global Biodiversity Information Facility), as part of a project developed for the review of Key Biodiversity Areas in Seychelles: "Mainstreaming recent species and ecosystem distribution data into Key Biodiversity Areas assessments in Seychelles" (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>).</p> <p>In the first version of the GBIF dataset (<a href="https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf">https://www.gbif.org/dataset/f513fe98-b1c3-45ee-8e14-7f2a5b7890bf</a>), we proposed an analysis of the potential 'core' and 'extension' files available in GBIF for a publication of ecosystem-type names (and synonymies) and their corresponding occurrences recorded from field observations. This is an original analysis of taxonomic principles managed entirely at the scale of local observable objects, and their history of identifications or interpretations.</p> <p>Toward the end of the above-mentioned GBIF project, considering the limitations and gaps currently present in GBIF, it was decided to restrict the GBIF dataset to a simple 'metadata' entry and to publish the complete version of this dataset in Zenodo. This allows to include all tables needed, as well as all required fields without having to accommodate them within the limited GBIF structure (see metadata description on GBIF for more details). The fields of the tables published here are described in the GBIF metadata entry and in the ecosystemology paper (Senterre et al. 2021b).</p> <p> </p> <p>3. New development on typology aspects:</p> <p>In addition, considering that the new IUCN global typology of ecosystems is now published (Keith et al. 2022), we have reviewed in detail the possibility of integration of ecosystems conceptualized using our ecosystemology approach within the new IUCN typology. The result of this analysis is being considered for a publication, and this Zenodo dataset would then be published in full (i.e. including all typology aspects) as supplementary materials. In the meantime, I would be happy to discuss any of these aspects with whoever is interested.</p> <p> </p> <p>4. Access to ecosystem data for conservation actors:</p> <p>Finally, the actual data (published here) on ecosystem-types, their names, synonymies, classification, distribution, and red list status are compiled into a format that we designed to be useful to conservation actors in the form of interactive webpages (produced with R as shiny apps). This development is based on very limited resources, and the author is still quite new to R, so any help or feedback on ways to improve the scripts would be very much welcomed.</p> <p>The interactive page is available here (currently filtered to Seychelles' data only, although the dataset contains data beyond the Seychelles): https://shiny.bio.gov.sc/bioeco/</p> <p>The R scripts are available on Github: https://github.com/bsenterre/ecosystemology</p> <p> </p> <p>5. Tables contained in this dataset:</p> <p>a. Ecosystem taxonomy tables:</p> <p>ecoSpecies: Contains the list of all ecosystem-type names with their unique identifier.</p> <p>ecoOccurrences: Contains the list of individual stand occurrences, including ecosystem characters as standardized in Senterre et al. (2021b; i.e. virtual ecosystem specimen).</p> <p>ecoSpeciesProfiles: Contains basic metadata on ecosystem-types, such as their Red List evaluations.</p> <p>ecoIdentifications: Contains all the different interpretations/identifications (referring to the table ecoSpecies or to higher levels of classification, see below) made on the stands observed in the ecoOccurrences table.</p> <p> </p> <p>b. Ecosystem typology tables (TO BE ADDED LATER):</p> <p>IUCNL3: This is just a transcription, as is, of the IUCN global typology version 2.1.</p> <p>IUCNL3BIOCrossover: This table defines and comments correspondences between BIOL2 (the level 2 of the typology used by us) and the IUCN typology L3 (level 3).</p> <p>BIOL2: This is a variation based on the IUCN typology, here our level 2.</p> <p>BIOL3: This is a variation based on the IUCN typology, here our level 3.</p> <p>BIOL4: This is a variation based on the IUCN typology, here our level 4.</p> <p>ecoGenus: This is a general type of stand (thus excluding any regional ecosystem connotation), defined at a local scale and never combined with any geographic connotation (see ecosystemology paper: Senterre et al. 2021b).</p> <p>ecoFamily: This is a generalized version of the ecoGenus (i.e. still excluding any regional, sub-regional or geographic aspect).</p> <p>ecoOrder: This is a further generalized version of the ecoGenus (see also Senterre et al. 2020).</p> <p>lifeZone: This is a basic and incomplete list of life zones as defined following the Holdridge (1967) approach, with some additional elements proposed in Senterre et al. (2021b).</p> <p> </p> <p>6. Literature cited:</p> <p>Holdridge, L. R. 1967. Life zone ecology. Tropical Science Center, San Jose, Costa Rica.</p> <p>Keith, D. A., J. R. Ferrer-Paris, E. Nicholson, M. J. Bishop, B. A. Polidoro, E. Ramirez-Llodra, M. G. Tozer, J. L. Nel, R. Mac Nally, E. J. Gregr, K. E. Watermeyer, F. Essl, D. Faber-Langendoen, J. Franklin, C. E. R. Lehmann, A. Etter, D. J. Roux, J. S. Stark, J. A. Rowland, N. A. Brummitt, U. C. Fernandez-Arcaya, I. M. Suthers, S. K. Wiser, I. Donohue, L. J. Jackson, R. T. Pennington, T. M. Iliffe, V. Gerovasileiou, P. Giller, B. J. Robson, N. Pettorelli, A. Andrade, A. Lindgaard, T. Tahvanainen, A. Terauds, M. A. Chadwick, N. J. Murray, J. Moat, P. Pliscoff, I. Zager, and R. T. Kingsford. 2022. A function-based typology for Earth’s ecosystems. . Nature 610:513–518. doi:10.1038/s41586-022-05318-4.</p> <p>Senterre, B. 2014. Mapping habitat-types within the Hummingbird site at Dugbe (Liberia, West Africa). Consultancy Report, Missouri Botanical Garden. P. 56. https://doi.org/10.13140/RG.2.2.32628.48003.</p> <p>Senterre, B. 2016. Habitat-type ground-truthing and assessment of ecosystem conservation value in the Bel Air Alufer mining site (Guinea, West Africa), with recommendations for improving the draft map of land cover types. Consultancy Report, Missouri Botanical Garden, A study conducted for Alufer Mining Limited. P. 54.</p> <p>Senterre, B., E. Bidault, and T. Stévart. 2019. Identification et évaluation des écosystèmes menacés du Mont Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 106. https://doi.org/10.13140/RG.2.2.13242.93129.</p> <p>Senterre, B., E. Bidault, T. Stévart, and P. P. Lowry II. 2020. Assessment of Key Biodiversity Areas in the Lofa-Gola-Mano & Nimba complexes (West Africa) using ecosystem criteria. Final Report, Missouri Botanical Garden. P. 146. 10.13140/RG.2.2.17934.89924.</p> <p>Senterre, B., E. Bidault, T. Stévart, M. Wagner, and P. Lowry. 2017. Mapping habitat-types in south-east Kouilou (Republic of Congo). Consultancy Report, Missouri Botanical Garden (MBG), Africa and Madagascar Department, St. Louis, Missouri, USA. P. 163.</p> <p>Senterre, B., R. M. Bristol, G. Gendron, and E. Henriette. 2021a. Fine-tuning conservation priorities in Seychelles at the landscape scale, using global KBA guidelines with both species and ecosystem criteria. Consultancy Report, United Nations Development Programme, GOS/UNDP/GEF Programme Coordination Unit, Victoria, Seychelles.</p> <p>Senterre, B., P. P. Lowry II, E. Bidault, and T. Stévart. 2021b. Ecosystemology: a new approach toward a taxonomy of ecosystems. . Ecological Complexity 47:100945. doi:https://doi.org/10.1016/j.ecocom.2021.100945.</p> <p>Senterre, B., A.-H. Paradis, E. Bidault, T. Stévart, and P. P. Lowry II. 2022. Qualité et distribution des savanes montagnardes du Nimba. Rapport de consultance, Missouri Botanical Garden (MBG), Africa and Madagascar Department. P. 73. http://dx.doi.org/10.13140/RG.2.2.13433.34401.</p> <p>Senterre, B., and M. Wagner. 2014. Mapping Seychelles habitat-types on Mahé, Praslin, Silhouette, La Digue and Curieuse. Consultancy Report, Government of Seychelles, United Nations Development Programme, Victoria, Seychelles. P. 119. https://doi.org/10.13140/RG.2.1.4558.6009.</p>
Modeling CH4 and CO2 cycling using porewater stable isotopes in a thermokarst bog in Interior Alaska: Results from three conceptual reaction networks
Quantifying rates of microbial carbon transformation in peatlands is essential for gaining mechanistic understanding of the factors that influence methane emissions from these systems, and for predicting how emissions will respond to climate change and other disturbances. In this study, we used porewater stable isotopes collected from both the edge and center of a thermokarst bog in Interior Alaska to estimate in situ microbial reaction rates. We expected that near the edge of the thaw feature, actively thawing permafrost and greater abundance of sedges would increase carbon, oxygen and nutrient availability, enabling faster microbial rates relative to the center of the thaw feature. (full abstract available in supplemental file 610_NeumannPorewaterExtendedMetadataText.pdf)
The Emergency Conceptual Framework Big Picture
<p>The Emergency System Conceptual Framework Big Picture gives an insight to better manage and plan for different emergencies (Accidents, Incidents, Crisis, Disasters, Catastrophes). </p>
Participatory Conceptual Diagrams to research small-scale farmers´ information sharing for adapting to climate change in Mozambique
<p>Data collected from focus groups discussions with local communities of 4 distrcits of Mozambique in November 2019. The data are a series of conceptual maps describing a) the farming practices improvements most needed to adapt to climate change, and b) the most useful information for enabling the selected improvements, the most effective information sharing sources - e.g. institutional actors, members of the community, technical support, etc. - and means of communication - e.g. radio, mobile phone, word-of-mouth, etc. For the second purpose, connections were drawn by the members of the community between information sources and the actions needed for climate change adaptation. Participants also assigned a weight to the connections, selecting between: strong, medium or a weak connection.</p> <p>Notes about the discussions and opinions expressed by participants, written down by the research team, are also included.</p> <p>Together with the data, PDF files describing metadata and detailed methodology followed are included.</p>
Conceptual blending
<p>Conceptual blending model as described by Gilles Fauconnier and Mark Turner in various publications. The actual image does not appear in the publications, but is based on them.</p>
Supplementary material for "Exploring Conceptual Data Modeling Processes: Insights from Clustering and Visualizing Modeling Sequences"
<p>This material supplements the following conference publication:</p> <p>Winkler, Rosenthal, Strecker (2024). "Exploring Conceptual Data Modeling Processes: Insights from Clustering and Visualizing Modeling Sequences". Modellierung 2024.</p>
Dataset for paper titled: Conceptual preferences can be transmitted via selective social information use between competing wild bird species
<p><a name="_Hlk66629591"></a><span>Concept learning is considered a high-level adaptive ability. Thus far, it has been studied in laboratory via asocial trial and error learning. Yet, social information use is common among animals but it remains unknown whether concept learning by observing others occurs. We tested whether pied flycatchers (</span><em><span>Ficedula hypoleuca</span></em><span>) form conceptual relationships from the apparent choices of nest-site characteristics (geometric symbol attached to the nest box) of great tits (</span><em><span>Parus major</span></em><span>). Each wild flycatcher female (n = 124) observed one tit pair that exhibited an apparent preference for either a large or a small symbol and was then allowed to choose between two nest boxes with a large and a small symbol, but the symbol shape was different to that on the tit nest. Older flycatcher females were more likely to copy the symbol size preference of tits than yearling flycatcher females when there was a high number of visible eggs or a few partially visible eggs in the tit nest. However, this depended on the phenotype; copying switched to rejection as a function of increasing body size. Possibly the quality of and overlap in resource use with the tits affected flycatchers' decisions. Hence, our results suggest that conceptual preferences can be horizontally transmitted across co-existing animals, which may increase the performance of individuals that utilize concept learning abilities in their decision-making.</span></p>
Measuring embodied conceptualizations of pitch insinging performances: insights from an OpenPose study
<p>People conceptualize auditory pitch as vertical space: low and high pitch correspond to low and high space respectively. The strength of this cross-modal correspondence, however, seems to vary across different cultural contexts and a debate on the different factors underlying this variation is currently taking place. According to one hypothesis, pitch mappings are semantically mediated. For instance, the use of conventional metaphors such as ‘falling’ or ‘rising’ melodies strengthens a pitch-height mapping to the detriment of other possible mappings (e.g. pitch as bright/dark color or small/big size). Hence, entrenched pitch terms shape specific conceptualizations. The deterministic role of language is called into question by the hypothesis that different pitch mappings share a less constraining conceptual basis. As such, conceptual primitives may be concretized <em>ad hoc</em> into specific domains so that more local variation is possible<em>.</em> This claim is supported, for instance, by the finding that musicians use language-congruent (conventional) and language-incongruent (<em>ad hoc</em>) mappings interchangeably. The present paper substantiates this observation by investigating the head movements of musically trained and untrained speakers of Dutch in a melody reproduction task, as embodied instantiations of a vertical conceptualization of pitch. The OpenPose algorithm was used to track the movement trajectories in detail. The results show that untrained participants systematically made language-congruent movements, while trained participants showed more diverse behaviors, including language-incongruent movements. The difference between the two groups could not be attributed to the level of accuracy in the singing performances. In sum, this study argues for a joint consideration of more entrenched (e.g. linguistic metaphors) and more context-dependent (e.g. musical training and task) factors in accounting for variability in pitch representations.</p>
Data from: Can extreme climatic events induce shifts in adaptive potential? A conceptual framework and empirical test with Anolis lizards
<p>Multivariate adaptation to climatic shifts may be limited by trait integration that causes genetic variation to be low in the direction of selection. However, strong episodes of selection induced by extreme climatic pressures may facilitate future population-wide responses if selection reduces trait integration and increases adaptive potential (i.e., evolvability). We explain this counter-intuitive framework for extreme climatic events in which directional selection leads to increased evolvability and exemplify its use in a case study. We tested this hypothesis in two populations of the lizard <em>Anolis scriptus</em> that experienced hurricane-induced selection on limb traits. We surveyed populations immediately before and after the hurricane as well as the offspring of post-hurricane survivors, allowing us to estimate both selection and response to selection on key functional traits: forelimb length, hindlimb length, and toepad area. Direct selection was parallel in both islands and strong in several limb traits. Even though overall limb integration did not change after the hurricane, both populations showed a non-significant tendency toward increased evolvability after the hurricane despite the direction of selection not being aligned with the axis of most variance (i.e., body size). The population with comparably lower between-limb integration showed a less constrained response to selection. Hurricane-induced selection, not aligned with the pattern of high trait correlations, likely conflicts with selection occurring during normal ecological conditions that favor functional coordination between limb traits, and would likely need to be very strong and more persistent to elicit a greater change in trait integration and evolvability. Future tests of this hypothesis should use G-matrices in a variety of wild organisms experiencing selection due to extreme climatic events. </p>
Figure 10. Conceptual diagram illustrating vector quantization codeword formation-Development an Automatic Speech to Facial Animation Conversion for Improve Deaf Lives
<p>After the conversion process converts the analogue speech signal into a series words,<br> then converting recognized word to facial animation based on VRML.</p>
Mapa conceptual de la guerra cognitiva
<p>Mapa mental integrado de variables y categorías teórico-conceptuales del fenómeno de la guerra cognitiva, tomando como caso de estudio la República Bolivariana de Venezuela.</p>
A systematic meta-analysis of the role of perceptual and conceptual novelty in guiding infant looking behaviour
<p>These are the data, codebooks, and scripts required to reproduce the results of the paper Kunin, L., Piccolo, S., Saxe, R., & Liu, S. (under revision). A systematic meta-analysis of the role of perceptual and conceptual novelty in guiding infant looking behaviour.</p> <p>A previous version of the data and code can be found at https://zenodo.org/records/11084599.</p> <p> </p>
Fig 3 in Conceptual Application Of Dytiscus Latissimus Linnaeus, 1758 (Dytiscidae, Coleoptera) Gathering Methods In Natural Habitat
Fig 3. The result of uncontrolled use of fishing Fig 4. First success. Alive D.latissimus males tackle by fish. Handful of dead D.latissimus and C. lateralimarginalis
Fig.1. Funnel trap for gathering living RESULTS AND DISCUSSION D.latissimus a in Conceptual Application Of Dytiscus Latissimus Linnaeus, 1758 (Dytiscidae, Coleoptera) Gathering Methods In Natural Habitat
Fig.1. Funnel trap for gathering living RESULTS AND DISCUSSION D.latissimus a result of the individual (from Jan G.M. Cuppen and other): As many years application of the material gathering methods was 1 – float; 2- rubber; 3 – aeration net; a possibility to catch on regular and predictable 4 – entrance Ø 30 mm. basis a required number of animals for our laboratory research. itself. This can be identified from locating specific cuts on it. (Vahrusevs 2009) The key to a successful egg collection is a search of the plants used by beetles during their Below is an example from field notes of catching reproduction period, as well as the correct beetles during the autumn season: locating of clutches. Such plants in our reservoir "The research on the reservoir was done during under study are Carex acuta, Carex rostrata, 11.10.2009 - 28.10.2009. Caltha palustris. One has to identify suitable plants in the locations of beetles' clutches The weather conditions were favourable. It was (usually located on the sunny side along the quite warm and windless all this time in order to coast of a water reservoir). The person gathering work comfortably. Water temperature was +7-8 ŗ the material has to grasp with fingers the C. We worked as usual on the proven location. underwater part of the identified plant stem Coordinates in Google Earth (latitude 55 ° 52'33 reaching almost to its base, and slowly palpate it.95 "C; longitude 26 ° 35'18.78" H). by letting it through the fingers in the upwards direction. The upwards direction is imperative, We prepared the traps in advance (they had to as stems of many sedge plants have microscopic be repaired and mended, and modernized a little. thorns which are rooting upwards. If this method (Fig.2.). is not followed, an injury of a palm can occur. A stem of the plant which has protruding bumps We took along 21 trap to the water reservoir. The on it guarantees the presence of a clutch. A stem bait was pieces of beef heart. The traps were in its normal condition is usually smooth and placed along the coastline. The first "throw" was often flat. Such plants as Caltha palustris which kept in the water for almost a week with regular have fleshy stem are to be studied in addition check ups made every day or every second day. visually as eggs can be located inside the stem Traps were installed partly dipped under water.
Data from: Strategies of resource sharing in clonal plants: A conceptual model and an example of contrasting strategies in two closely related species
<p>These experimental data were collected to quantify amount of C and N translocated between mother and daughter ramets of two stoloniferous species. Data includes concentrations of 13-C and 15-N in plants samples originating from pulse-chase labelling, absolute amounts of the labels present, as well as dry mass of the samples. Details are described in the relevant paper.</p> <p> </p>
Conceptual Assessment Questions with Experts - OntoTurnover
<p><strong>Objective: </strong>To describe the questions and alternatives used in the conceptual evaluation with experts carried out in the OntoTurnover engineering process.</p>
Conceptualization of public data ecosystems
<p>This dataset contains data collected during a study <a href="https://www.sciencedirect.com/science/article/pii/S0740624X23000989"><strong><em>"Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems"</em></strong></a> conducted by <em>Martin Lnenicka (University of Hradec Králové, Czech Republic), Anastasija Nikiforova (University of Tartu, Estonia), Mariusz Luterek (University of Warsaw, Warsaw, Poland), Petar Milic (University of Pristina - Kosovska Mitrovica, Serbia), Daniel Rudmark (Swedish National Road and Transport Research Institute, Sweden), Sebastian Neumaier (St. Pölten University of Applied Sciences, Austria), Karlo Kević (University of Zagreb, Croatia), Anneke Zuiderwijk (Delft University of Technology, Delft, the Netherlands), Manuel Pedro Rodríguez Bolívar (University of Granada, Granada, Spain).</em></p> <p>As there is a lack of understanding of the elements that constitute different types of value-adding public data ecosystems and how these elements form and shape the development of these ecosystems over time, which can lead to misguided efforts to develop future public data ecosystems, the aim of the study is: (1) to explore how public data ecosystems have developed over time and (2) to identify the value-adding elements and formative characteristics of public data ecosystems. Using an exploratory retrospective analysis and a deductive approach, we systematically review 148 studies published between 1994 and 2023. Based on the results, this study presents a typology of public data ecosystems and develops a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems, and develops a conceptual model of the evolutionary generation of public data ecosystems represented by six generations called Evolutionary Model of Public Data Ecosystems (EMPDE). Finally, three avenues for a future research agenda are proposed.</p> <p>This dataset is being made public both to act as supplementary data for "<em>Understanding the development of public data ecosystems: from a conceptual model to a six-generation model of the evolution of public data ecosystems </em>", Telematics and Informatics*, and its Systematic Literature Review component that informs the study. </p> <p>***Description of the data in this data set***</p> <p>PublicDataEcosystem_SLR.docx provides the structure of the protocol</p> <p>PDEtypes.png provides a typology of public data ecosystems</p> <p>PDE_conceptual_model.png provides a conceptual model of elements and formative characteristics that contribute most to value-adding public data ecosystems</p> <p>PublicDataEcosystem_SLR.xlsx, Spreadsheet#1 provides the list of results after the search over three indexing databases and filtering out irrelevant studies</p> <p>Spreadsheets #2 provides the protocol structure.</p> <p>Spreadsheets #3 provides the filled protocol for relevant studies.</p> <p>The information on each selected study - presented in PublicDataEcosystem_SLR.xlsx - was collected in four categories:<br>(1) descriptive information,<br>(2) approach- and research design- related information,<br>(3) quality-related information,<br>(4) HVD determination-related information</p> <p>Descriptive Information</p> <ul> <li>Article number</li> <li>A study number, corresponding to the study number assigned in an Excel worksheet</li> <li>Complete reference</li> <li>The complete source information to refer to the study (in APA style), including the author(s) of the study, the year in which it was published, the study's title and other source information.</li> <li>Year of publication</li> <li>The year in which the study was published.</li> <li>Journal article / conference paper / book chapter</li> <li>The type of the paper, i.e., journal article, conference paper, or book chapter.</li> <li> Journal / conference / book</li> <li> Journal article, conference, where the paper is published.</li> <li> DOI / Website</li> <li> A link to the website where the study can be found.</li> <li>Number of words</li> <li>A number of words of the study.</li> <li>Number of citations in Scopus and WoS</li> <li>The number of citations of the paper in Scopus and WoS digital libraries.</li> <li>Availability in Open Access</li> <li>Availability of a study in the Open Access or Free / Full Access.</li> <li>Keywords</li> <li>Keywords of the paper as indicated by the authors (in the paper).</li> <li>Relevance for our study (high / medium / low)</li> <li>What is the relevance level of the paper for our study</li> </ul> <p>Approach- and research design-related information</p> <ul> <li>Approach- and research design-related information</li> <li>Objective / Aim / Goal / Purpose & Research Questions</li> <li>The research objective and established RQs.</li> <li>Research method (including unit of analysis)</li> <li>The methods used to collect data in the study, including the unit of analysis that refers to the country, organisation, or other specific unit that has been analysed such as the number of use-cases or policy documents, number and scope of the SLR etc.</li> <li>Study’s contributions</li> <li>The study’s contribution as defined by the authors</li> <li>Qualitative / quantitative / mixed method</li> <li>Whether the study uses a qualitative, quantitative, or mixed methods approach?</li> <li>Availability of the underlying research data</li> <li>Whether the paper has a reference to the public availability of the underlying research data e.g., transcriptions of interviews, collected data etc., or explains why these data are not openly shared?</li> <li>Period under investigation</li> <li>Period (or moment) in which the study was conducted (e.g., January 2021-March 2022)</li> <li>Use of theory / theoretical concepts / approaches? If yes, specify them</li> <li>Does the study mention any theory / theoretical concepts / approaches? If yes, what theory / concepts / approaches? If any theory is mentioned, how is theory used in the study? (e.g., mentioned to explain a certain phenomenon, used as a framework for analysis, tested theory, theory mentioned in the future research section).</li> </ul> <p>Quality-related information</p> <ul> <li>Quality concerns</li> <li>Whether there are any quality concerns (e.g., limited information about the research methods used)?</li> </ul> <p>Public Data Ecosystem-related information</p> <ul> <li>Public data ecosystem definition</li> <li>How is the public data ecosystem defined in the paper and any other equivalent term, mostly infrastructure. If an alternative term is used, how is the public data ecosystem called in the paper?</li> <li> Public data ecosystem evolution / development</li> <li>Does the paper define the evolution of the public data ecosystem? If yes, how is it defined and what factors affect it?</li> <li>What constitutes a public data ecosystem?</li> <li>What constitutes a public data ecosystem (components & relationships) - their "FORM / OUTPUT" presented in the paper (general description with more detailed answers to further additional questions).</li> <li>Components and relationships</li> <li>What components does the public data ecosystem consist of and what are the relationships between these components? Alternative names for components - element, construct, concept, item, helix, dimension etc. (detailed description).</li> <li>Stakeholders</li> <li>What stakeholders (e.g., governments, citizens, businesses, Non-Governmental Organisations (NGOs) etc.) does the public data ecosystem involve?</li> <li>Actors and their roles</li> <li>What actors does the public data ecosystem involve? What are their roles?</li> <li>Data (data types, data dynamism, data categories etc.)</li> <li>What data do the public data ecosystem cover (is intended / designed for)? Refer to all data-related aspects, including but not limited to data types, data dynamism (static data, dynamic, real-time data, stream), prevailing data categories / domains / topics etc.</li> <li>Processes / activities / dimensions, data lifecycle phases</li> <li>What processes, activities, dimensions and data lifecycle phases (e.g., locate, acquire, download, reuse, transform, etc.) does the public data ecosystem involve or refer to?</li> <li>Level (if relevant)</li> <li>What is the level of the public data ecosystem covered in the paper? (e.g., city, municipal, regional, national (=country), supranational, international).</li> <li>Other elements or relationships (if any)</li> <li>What other elements or relationships does the public data ecosystem consist of?</li> <li>Additional comments</li> <li>Additional comments (e.g., what other topics affected the public data ecosystems and their elements, what is expected to affect the public data ecosystems in the future, what were important topics by which the period was characterised etc.).</li> <li>New papers</li> <li>Does the study refer to any other potentially relevant papers?</li> <li>Additional references to potentially relevant papers that were found in the analysed paper (snowballing).</li> </ul> <p>***Format of the file***<br>.xls, .csv (for the first spreadsheet only), .docx</p> <p>***Licenses or restrictions***<br>CC-BY</p> <p> </p> <p>For more info, see README.txt</p>
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