Automated Author ProfileTaibi, Davide
Taibi, Davide
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 25.5 (sum of 13 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This chapter adds to the chapter by Kantz and Baldry (this volume) by providing a second perspective on tourism marketing genres in the digital age: it explores the effects of AR and AI technologies for would-be tourists and for users in the field of Education by encouraging the development of structured pathways that potentially enrich and amplify the SG (serious game) genre. The proposed developments include, in particular, the integration of podcast and video corpora so as to anchor SG simulation in explorations of real places and reconstructions of their place in history. The desire to provide a better interplay between entertainment and knowledge about people and places is backed up by suggestions of how current authoring tools could be reworked to provide a single platform through which users, whether teachers, tourists, students or others, can access pre-existing structured pathways and/or easily add to them.
Authors
- Baldry, Anthony ;
- Taibi, Davide
This is the raw-data for the paper Motivations, Benefits and Issues for adopting Micro-Frontends: A Multivocal Literature Review
Authors
- Peltonen, Severi ;
- Mezzalira, Luca ;
- Taibi, Davide
Dataset for the paper "Shall I ask a new feature"
Authors
- Zheying Zhang ;
- Sievi-Korte, Outi ;
- Ulla-Talvikki Virta ;
- Hannu-Matti Jarvinen ;
- Taibi, Davide
Dataset for the paper "Shall I ask a new feature"
Authors
- Zheying Zhang ;
- Sievi-Korte, Outi ;
- Ulla-Talvikki Virta ;
- Hannu-Matti Jarvinen ;
- Taibi, Davide
This is the raw-data for the paper Motivations, Benefits and Issues for adopting Micro-Frontends: A Multivocal Literature Review
The files contains 6 tabs:
Raw Data List of sources extracted from the search engines, application of inclusion and exclusion criteria Quality assessment Application of the quality assessment criteria Selected Sources List of selected sources RQ1 - Motivations Analysis of the motivations and related coding from the selected sources RQ2 - Benefits Analysis of the benefits and related coding from the selected sources RQ3 - Issues Analysis of the issues and related coding from the selected sources
Authors
- Peltonen, Severi ;
- Mezzalira, Luca ;
- Taibi, Davide
This is the raw-data for the paper Motivations, Benefits and Issues for adopting Micro-Frontends: A Multivocal Literature Review
The files contains 6 tabs:
Raw Data List of sources extracted from the search engines, application of inclusion and exclusion criteria Quality assessment Application of the quality assessment criteria Selected Sources List of selected sources RQ1 - Motivations Analysis of the motivations and related coding from the selected sources RQ2 - Benefits Analysis of the benefits and related coding from the selected sources RQ3 - Issues Analysis of the issues and related coding from the selected sources
Authors
- Peltonen, Severi ;
- Mezzalira, Luca ;
- Taibi, Davide
This is the raw-data for the paper Motivations, Benefits and Issues for adopting Micro-Frontends: A Multivocal Literature Review
Authors
- Peltonen, Severi ;
- Mezzalira, Luca ;
- Taibi, Davide
Video corpora are one form of specialised corpora that can be used to promote the use of video-hosting sites, such as YouTube and Dailymotion, in domain specific university language learning courses. The article reports the experiences of a group of researchers, working in a variety of roles and from different perspectives, to promote the use of videos hosted on such sites in English for Medical Purposes (EMP) courses. The article describes how the MWSWEB platform modifies access to such sites in ways compatible with corpus-based exploration of domain-specific videos thereby encouraging university students to build their own video corpora under the guidance of their teachers.
Authors
- Baldry, Anthony ;
- Kantz, Deirdre ;
- Loiacono, Anna ;
- Marenzi, Ivana ;
- Taibi, Davide ;
- Tursi, Francesca
This paper outlines the strategies, rationale and potential uses motivating the construction of the House Corpus, a one-million-word corpus that can be accessed by authorised users through the MWSWeb site (Taibi et al. 2015a) at http://openmws.itd.cnr.it. Part 1 illustrates the tools and techniques used to index the corpus data – transcriptions of all 177 episodes in the House M.D. series (original US version). In particular, it describes the commercially available Elasticsearch (https://www.elastic.co), used as an indexing, annotational and search tool. Part 2 explains that this is a multimedia corpus allowing viewings of different types of scene. The 6000-plus scenes in the corpus have been annotated in terms of their typological features: Location type (e.g. patient's hospital room; medical lab etc.); Event type (handover; differential diagnosis; precipitating medical event; patient examination etc.) and Character Group type (doctor/doctor; doctor/patient; doctor/caregiver; patient/caregiver etc.). The project envisages the development of various retrieval interfaces, initially Words, Scenes and Dialogues. This will make it possible to carry out searches in terms of types of scene and their distribution across the corpus without necessarily involving any other form of searching. Part 3 suggests the value of multimedia corpora in encouraging students to advance their critical discourse analysis (CDA) skills. As an example, it shows how the corpus can illustrate the priority of (inter)textual over lexicogrammatical considerations when formulating tag questions in oral discourse. Finally, the Discussion section argues that a typology of scenes appears to be an essential prerequisite for the construction of other types of access to the corpus data in subsequent stages of the project.
Authors
- Taibi, Davide ;
- Marenzi, Ivana ;
- Ahmad, Qazi Asim Ijaz