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55 results for “tourists”
Evidence of a Vulnerable Marine Ecosystem documented via tourist submarine off Cape Well-Met, Vega Island, Eastern Antarctic Peninsula (Subarea 48.1) - Multimedia
<p>Video evidence of a Vulnerable Marine Ecosystem (VME) was collected via submarine deployed by the tourist super-yacht MY Scenic Eclipse flagged with Malta. The dive was conducted on the 29th November 2019 within Subarea 48.1. The video of this resource supplements the dataset "Evidence of a Vulnerable Marine Ecosystem documented via tourist submarine off Cape Well-Met, Vega Island, Eastern Antarctic Peninsula (Subarea 48.1) - data'' available at <a href="https://ipt.biodiversity.aq/resource?r=cape-well-met_2019">https://ipt.biodiversity.aq/resource?r=cape-well-met_2019</a>.</p> <p>Method step description:</p> <ol> <li> <p>Video evidence of a Vulnerable Marine Ecosystem (VME) was collected via submarine deployed by the tourist super-yacht MY Scenic Eclipse flagged with Malta. Recordings begin at the greatest depth and continue as the submarine travels up the wall. Footage was taken with a GoPro Hero 7 Black mounted in the pilot window of a U-Boat Worx Cruise Sub 7-300<a href="https://www.uboatworx.com/model/cruisesub"> (https://www.uboatworx.com/model/cruisesub).</a> Four submarine dives were filmed.</p> </li> <li> <p>Prior to footage clean-up it was decided that the longest resulting video would be the one that would be analysed. Footage of each of these dives were provided in multiple files.</p> </li> <li> <p>Final Cut Pro X was first used to join the files into one video file per dive.</p> </li> <li> <p>The videos were then cropped to remove the edge of the pilot’s window frame and to adjust the colour balance.</p> </li> <li> <p>Clean-up then followed the same methodology as was used for analyzing the submarine footage for the successful nomination of four VMEs in WG-EMM-18/35 to remove unusable sequences. For the Cape Well-Met footage that meant the removal of any sequences where the submarine was too far from the wall, where the visibility was poor and when the submarine was paused.</p> </li> <li> <p>Footage from Dive C was the longest resulting video after the completion of this clean-up procedure, thus it became the footage that was analysed.</p> </li> </ol> <p>This project is funded by The Soap and The Sea, a Swiss organic and ocean-friendly soap enterprise that donates half of its profits to Ocean Conservation initiatives.</p>
DGU-AI-LAB/Korean-Tourist-Spot-Dataset: Korean Tourist Spot Dataset
<p>The KTS dataset has four modals (image, text, hashtag, likes) and consists of 10 classes related to Korean tourist spots. All data were extracted from Instagram and preprocessed.</p>
Historical GIS and Guidebooks: Czechoslovak Tourist Attractions
<p>The following dataset of geolocated travel guide toponyms was compiled in the process of a research project <em>Historical GIS and Guidebooks: A Scalable Reading of Czechoslovak Tourist Attractions </em>(Bechmann Pedersen & Johansson, forthcoming) in which we performed a scalable reading of three travel guides of the former Czechoslovak lands as they were cirka 1959. We used a specialized, open-sourced tool <a href="https://github.com/MatJohaDH/citadel">CITADEL</a> created for this project, which in itself relies on open-sourced data from GeoNames and WikiData.</p> <p> </p> <p> </p> <p>Our primary sources were the following three travel guides:</p> <ul> <li>Čedok/Nagel, 1959, <em>Czechoslovakia</em></li> <li>Čedok, 1928 <em>Guide to the Czechoslovak Republic</em></li> <li>Baedker, 1905 <em>Austria–Hungary including Dalmatia and Bosnia</em></li> </ul> <p>All files are tab separated values (.tsv) files with utf-8 encoding.</p> <ol> <li>Three lists of positions with associated toponyms</li> <li>Two lists of clusters</li> </ol> <p>There are three files of the first type:</p> <p>CITADEL_1905Baedeker_toponyms.tsv<br> CITADEL_1928Cedok_toponyms.tsv<br> CITADEL_1959Nagel_toponyms.tsv</p> Columns for toponym files <table><tbody><tr> <th>Column</th> <th>Explanation</th> </tr> </tbody><tbody> <tr> <td>Toponym_first_used</td> <td>First toponym recorded in the database that is linked to the position</td> </tr> <tr> <td>Toponym_added</td> <td>The toponym as spellled in the travel guide</td> </tr> <tr> <td>Source</td> <td>A shorthand used to identify the travel guide</td> </tr> <tr> <td>PositionID</td> <td>The unique identifier of a position, using the GeoNames or WikiData identifiers where applicable.</td> </tr> <tr> <td>Longitude</td> <td>-</td> </tr> <tr> <td>Latitude</td> <td>-</td> </tr> <tr> <td>Year</td> <td>The year of the travel guide</td> </tr> <tr> <td>Weight</td> <td>The weight reflects the number of entries the toponym has in the index. Nagel1928 does not use this convention, and the weight is instead based on the relative page count.</td> </tr> </tbody> </table> <p> </p> <p>There are two files of the second type:</p> <p>CITADEL_1905,1928,1959_4km_clusters.tsv<br> CITADEL_1928,1959_4km_clusters.tsv</p> Columns for the cluster files <table><tbody><tr> <th>Column</th> <th>Explanation</th> </tr> </tbody><tbody> <tr> <td>years</td> <td>The years represented in the cluster</td> </tr> <tr> <td>Latitude</td> <td>-</td> </tr> <tr> <td>Longitude</td> <td>-</td> </tr> <tr> <td>cnt_points</td> <td> <p>The number of points represented in the cluster</p> </td> </tr> <tr> <td>cnt_toponyms</td> <td>The number of toponyms represented in the cluster</td> </tr> <tr> <td>cnt_toponyms_<source></td> <td>The number of toponyms from <source> represented in the cluster</td> </tr> </tbody> </table>
Tourist Reviews of Sri Lankan Destinations Dataset
<p>Explore a comprehensive collection of tourist reviews for diverse travel destinations in Sri Lanka. This dataset offers valuable insights into traveler preferences and sentiments, enabling research in tourism, hospitality, and sentiment analysis. It includes location details, user profiles, and review attributes.</p>
GPS trajectories of tourists in Öregrund 2023 from INCULTUM Sweden Pilot
<p>This dataset is part of ongoing work being written about changes in tourists' behaviour in Öregrund.</p>
Storytelling and its influence on the tourist promotion of the national sanctuary of Huayllay, Pasco Region-2021
<p><strong>Background:</strong> The objective of the study article was to determine the influence of Storytelling in the tourist promotion of the National Sanctuary of Huayllay</p> <p><strong>Methods:</strong> For which a quantitative approach study was used, pre-experimental design with a single control group, the study population consisted of 19 visitors to which (Pre test-post test).</p> <p><strong>Results:</strong> The information collected was processed through the statistical program spss, and then the Eta analysis was performed to determine the degree of influence between the variables of study. The result obtained was 0.677/0.795, which indicates that storytelling does influence the tourism promotion of the place. The importance of the study consists in the investigation of a new commercial communication tool known as storytelling, which appeals to the emotional factor, and which already represents a successful model in different countries of the world, since it has reached an extraordinary importance in the decision-making process of potential tourists and has turned out to be an excellent alternative for the promotion of tourist destinations.</p> <p><strong>Conclusion:</strong> The study was able to demonstrate that Storytelling can be used as a tool for tourism promotion not only at the level of the locality of the area of the study site, but also at the national level.</p> <p><strong>Background:</strong> The objective of the study article was to determine the influence of Storytelling in the tourist promotion of the National Sanctuary of Huayllay</p> <p><strong>Methods:</strong> For which a quantitative approach study was used, pre-experimental design with a single control group, the study population consisted of 19 visitors to which (Pre test-post test).</p> <p><strong>Results:</strong> The information collected was processed through the statistical program spss, and then the Eta analysis was performed to determine the degree of influence between the variables of study. The result obtained was 0.677/0.795, which indicates that storytelling does influence the tourism promotion of the place. The importance of the study consists in the investigation of a new commercial communication tool known as storytelling, which appeals to the emotional factor, and which already represents a successful model in different countries of the world, since it has reached an extraordinary importance in the decision-making process of potential tourists and has turned out to be an excellent alternative for the promotion of tourist destinations.</p> <p><strong>Conclusion:</strong> The study was able to demonstrate that Storytelling can be used as a tool for tourism promotion not only at the level of the locality of the area of the study site, but also at the national level.</p>
Results of SPOT surveys for tourists, residents and entrepreneurs in the case studies - dataset
<p>This is a dataset of three surveys conducted within the scope of the SPOT project. The purpose of this dataset is to provide the results of the surveys for tourists, residents and entrepreneurs of the fifteen participating case studies. </p>
Exploring the generational influence on social media based tourist decision making in India
Open the record for dataset details and reuse information.
Tourists and Visitors Flows in Lombardy
<p><span>The dataset provides information about the aggregate yearly flow of individuals travelling across 120 municipalities located in Lombardy (Italy) with details on the origin and destination of the movement. The dataset refers to the calendar year 2022.</span></p> <p><span>The dataset also distinguishes among two different travelling profiles, namely visitors and tourists. In particular, visitors are defined as those individuals who make a visit outside of the municipality of usual residence for at least four hours without an overnight stay. On the other hand, Tourists are defined as those users with a night cell referring to a municipality that differs from the phone residence. Such definitions of these two travelling behaviour are consistent with those provided by official statistical offices.</span></p> <p><span>In particular, the dataset “db_tourists.csv” provides information on the number of tourists moving from the municipality specified in the column “Origin_id” to the municipality specified in the column “Destination_id”.</span></p> <p><span>The dataset “db_visitors.csv” provides information on the number of visitors moving from the municipality specified in the column “Origin_id” to the municipality specified in the column “Destination_id”.</span></p> <p><span>Municipalities are anonymized and indicated through an index ranging between 1 and 120. </span></p> <p><span>The mobile network data used in this paper have been made available to the authors by Polis, a public entity collaborating with the Lombardy region. These data are provided by a main telecommunication company in an anonymised and irreversibly aggregated form, in compliance with the privacy legislation, and the provisions of the EU GDPR, according to the Privacy by Design methodology.</span></p>
Рис. 2. Схема станΔартных промеров раковины Δвустворчатых моΛΛюсков по А. А. Зютину: L — ΔΛина раковины; H — тоΛщина раковины; D — ширина / выпукΛость Fig. 2. Scheme of bivalve mollusk shell standard measurements: L — shell length; H — shell thickness; D — width / convexity (according to A. A. Zyutin) in Morphometric characteristics of Black Sea mussels Mytilus galloprovincialis Lam. as biomarkers of the anthropogenic impact on the Black Sea coastal biocenoses in tourist destinations
Рис. 2. Схема станΔартных промеров раковины Δвустворчатых моΛΛюсков по А. А. Зютину: L — ΔΛина раковины; H — тоΛщина раковины; D — ширина / выпукΛость Fig. 2. Scheme of bivalve mollusk shell standard measurements: L — shell length; H — shell thickness; D — width / convexity (according to A. A. Zyutin)
Рис. 1. Схема распоΛожения станций отбора проб (сервис ЯнΔекс.Карты) Fig. 1. Location of the sampling stations (source: Yandex.Maps) in Morphometric characteristics of Black Sea mussels Mytilus galloprovincialis Lam. as biomarkers of the anthropogenic impact on the Black Sea coastal biocenoses in tourist destinations
Рис. 1. Схема распоΛожения станций отбора проб (сервис ЯнΔекс.Карты) Fig. 1. Location of the sampling stations (source: Yandex.Maps)
Рис. 3. Ливневый сток, прохоΔящий через территорию муниципаΛьного пΛяжа «Маяк» (фото авторов) Fig. 3. Stormwater runoff passing through the territory of "Mayak" municipal beach (photo by the authors) in Morphometric characteristics of Black Sea mussels Mytilus galloprovincialis Lam. as biomarkers of the anthropogenic impact on the Black Sea coastal biocenoses in tourist destinations
Рис. 3. Ливневый сток, прохоΔящий через территорию муниципаΛьного пΛяжа «Маяк» (фото авторов) Fig. 3. Stormwater runoff passing through the territory of "Mayak" municipal beach (photo by the authors)
Meganisi tourist guide (ICCS)
<p>Gathers data describing the data related to Maritime Transport and Inland Waterway Transport including the infrastructures.</p>
Dataset National Tourist Routes Norway
<p>The dataset provides information related to the 18 tourist routes ('Nasjonale Turistveger', https://www.nasjonaleturistveger.no) developed in Norway by the Norwegian Public Roads Administration ('Statens Vegvesen') since the early 1990s. The dataset includes information about the 18 routes, 130 attractions built along these routes, as well as municipality-level information on geographical, social and economic variables.</p> <p>The dataset was prepared for public use as part of the Horizon Europe ‘DemoTrans’ project (grant agreement nr. 101059288; Work Package Leader: Zuzana Murdoch). Neither the European Union nor the granting authority can be held responsible for the contents and use of the data. Excellent research assistance by Trym Simensen, Rasmus Skogland, Kevin Tran and Henrik Nicolajsen at various stages of the development of the dataset over the period 2020-2024 is gratefully acknowledged. </p>
Fig. 1 in Effects of tourist visitation and supplementary feeding on fish assemblage composition on a tropical reef in the Southwestern Atlantic
Fig. 1. Non-Metric Multi-Dimensional Scaling (MDS) plot of fish assemblages samples of the Picãozinho reef in each of the two studied situations. Dark triangles = PT (presence of tourists) and light triangles = AT (absence of tourists).
Engraved Tourist info panorama plaque
Bronze metal Engraved Tourist info panorama plaque board at a lookout tower marking surrounding mountains and points of interests Štepánka tower, 1892 @ Kořenov (CZ) photogrammetry scan (60x24MP), 3x8K textures + Normals from 2M tris Source: Objaverse 1.0 / Sketchfab
Tytus Chałubiński's tourist-type Shepherd's axe
ID no.: S/538/MT Museum: The Dr. Tytus Chałubiński Tatra Museum in Zakopane https://muzea.malopolska.pl/en/objects-list/1983 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
The network characteristics of classic red tourist attractions in Shaanxi province, China
<p>Tourism flow is a significant tourism phenomenon and a hot topic of tourism geography research. This study, based on the perspective of combining <span>'virtual' and 'reality'</span><span>,</span> takes 13 classic red tourism scenic areas in Shaanxi <span>p</span>rovince as examples. It constructs a multi-source data network attention evaluation index and adopts social network analysis method to explore the network attention and tourism flow of the study case, and further investigates the relationship between the two. Th<span>e</span> study shows that: (1) The case sites have formed a spatial layout <span>of the </span><span>'</span>dense in the north and sparse in the south'. Among them, the total number of attractions in <span>n</span>orthern Shaanxi is the largest and most are concentrated in Yan<span>'</span>an; the total number of attractions in <span>s</span>outhern Shaanxi is the smallest and mo<span>st</span> scattered. (2) The overall network attention of the case sites is low, and there is variability in network attention of different types of tourist attractions, among which network attention of the attractions in Yan<span>'</span>an City is high. (3) The network structure of tourism flow in the case <span>has</span> the spatial characteristics of low density, <span>'</span>one level and multicore<span>'</span> and significant small network groups. (4) There are correlations and differences between network attention and tourism flow in the sites <span>in question</span>. Based on the differences between them, the attractions are classified into four types: high-high, high-low, low-high and low-low. In response to the above findings, this study proposes the principle of <span>'</span>precision identification and classification<span>'</span>, and proposes targeted development strategies such as <span>c</span>reating high-quality regional tourist routes<span>,</span> promoting the digital development of <span>tourist attractions</span>, and innovating <span>the </span>ways to promote attractions.</p>
Survey of tourists in Öregrund 2023 from INCULTUM Sweden Pilot
<div>This dataset is part of ongoing work about changes in tourists' behaviour in Öregrund, collected using pen-and-paper questionnaires in the summer of 2023.</div>
GPS trajectories of tourists on Torsö and Brommö 2021 from INCULTUM Sweden Pilot
<div>This dataset is part of ongoing work about tourist behaviour changes on Torsö and Brommö. It was collected using GPS trackers. </div> <div> <div> <p> </p> </div> </div>
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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.