Dataset description. Briefly describe the data captured for this project and its purpose. This should have sufficient detail that enables readers to quickly understand whether the project or dataset is of interest to them. Tags/Keywords – Terms to help users discover the project and its datasets; please include terms that would be used by technical and nontechnical users. For tags, refer to Mesh Terms, which are loaded annually from the US National Library of Medicine.
Dataset description. The processed dataset consists of 64 Sentinel-1 Wide Swath images acquired during the period spanning from 5th November 2014 to 18th March 2017 (see Table 2-1). Table 2-1 shows the acquisition dates of the images: it can be observed that the maximum time interval of consecutive images is 48 days. The super master image is the first image. The images in green correspond to the dataset used for the iteration 1 (images from 1 to 51). The images used in the second iteration starts in the image number 23. The main characteristics of the used images are summarized in Table 2-2. Figure 2-1 shows the footprint of the processed datasets consisting in 18 bursts divided in 3 swaths. To process the interferometric products, we have used the SRTM Digital Elevation Model provided by NASA, and the precise orbits. To derive the deformation map, we have generated a network of 398 and 481 interferograms corresponding to the first and the second iteration respectively. The maximum temporal baseline used is 156 days. This threshold has been derived by a statistical analysis of the decrease of the coherence with respect the temporal baseline.
Dataset description. There are not formal requirements for the dataset description formulated yet. In particular, the description will depend on the type of a dataset. However, it is recommended to publishers of dataset to provide following information: • The nature of the dataset (scope of data) • The scale of the dataset (amount of data) • To whom could the dataset be useful • Whether the dataset underpins a scientific publication (and which publications) • Information on the existence (or not) of similar datasets • Possibilities for integration with other datasets and reuse It is also possible that the description will have additional internal structure (XML).
Dataset description. The data set used to model mental health (MH) trajectories of HADS total scores over 7 measurement points (M0 to M18) comprised 474 patients who had no more than 1 missing value. Imputation, was implemented using the Multiple Imputation through Chained Equations (MICE) algorithm from the R package ‘MICE’ for 1, 14, 7, 12, 18, 17, and 19 observations, respectively for data at M0, M3, M6, M9, M12, M15, and M18. For modelling of global QoL trajectories across the 7 measurement points the available data set comprised 472 patients who had no more than 1 missing value. Imputation, was implemented for 9, 15, 8, 13, 21, 17, and 24 observations, respectively for data at M0, M3, M6, M9, M12, M15, and M18.
Dataset description. The research data of the project include design and simulation files of the circuits, design rules for fabrication process, measurement results, reports, project deliverables and publications from the project. Research material for the project include physical circuits and circuit boards and demonstrator units. The integrated circuits, circuit housings, demonstrator units will be designed with appropriate simulation software (e.g. Agilent ADS, Cadence, HFSS) and are saved as schematic files and layouts with specific file format of the software. The measurement results are saved in touchtone (.s2p), excel (.xlsx), Mathcad (.mcd) and Matlab (.mat) formats. The designs, measurements and measurement setups are also reported and documented in word processing programs and saved with .doc and .pdf formats. Estimated volume of data will be 20 GB.
Dataset description. The data, following anonymization, has been provided by Prof. Xxxx Xxx-Horenczyk, THE HEBREW UNIVERSITY OF JERUSALE, Israel, within the framework of the BOUNCE EU funded project. The study details and outcome have been previously described [Xxxxxx-Xxx et al. 2012, 2016, Xxx-Xxxxxxxxx et al 2015, 2016]. A short summary is provided here. Researchers Involved in Data Collection: Xxxx Xxx-Horenczyk PhD, Xxxxxxx Xxxxx PhD, Xxxxx Xxxxxx-Xxx, PhD, Xxxx Xxxxxxxx BA Xxxxx Xxxxxxxxxx MA, Xxxxxxxxx Xxxxxxx MD & Xxxxxxx Xxxxxxx MD Purpose: The purpose of the study was to evaluate the long-term effect of group intervention in female patients with early-stage breast cancer. The group intervention was intended to enhance emotion regulation and build resilience. The intervention and comparison group were self-selected based on participants’ willingness to take part in the intervention program (Xxxxxxxxx et al 2016).
Dataset description. The data following anonymization has been provided by Xx. Xxxxx Xxxxx, Champalimaud Breast Unit, Lisbon, Portugal within the framework of the BOUNCE EU funded project. A short summary is provided here. Researchers for data collection: Xxxxx Xxxxxxx, Xxxxxx Xxxxxxx, Xxxxxx Xxxxxxxx-Xxxx, Xxxxx Xxxxx, Xxxxxx Xxxxx, Xxxxx Xxxxxxx, Xxxxxxxx Xxxxxxxxxxxx Aim: This study has an observational retrospective design: it looks backwards to medical, functional, demographic, and psychometric data collected in CR/CCC databases and examines the correlation between biological and psychological factors. The collection of the data will regard all the breast cancer patients treated with curative intent until 2017. The dataset represents a very heterogenous population where data was retrospectively collected to be integrated in a larger dataset.
