Dataset Sample Clauses
Dataset. The Dataset will consist of all the files transferred by the Depositor and the metadata provided by the Depositor as described in Section 1. Metadata is understood to mean the contents of all fields that must be completed in the archival system at the time of deposit in order to describe the Dataset. The Depositor warrants that the Dataset corresponds to the metadata provided by the Depositor in the Data Deposit Form. The Depositor will provide the files in a preferred format, as defined on ISSDA’s File Format Policy at the time of deposit. In the event that a format is not defined as a preferred format, the Depositor will contact ISSDA before delivery. A different file format may only be supplied with the written consent of ISSDA. The Depositor will provide documentation with the Dataset that explains its creation, contents and any specific values (such as codes, characters and abbreviations), its structure (such as folder structures and relationships between files) and its actual use (such as that of software) to third parties (“Related Documentation”). The Depositor acknowledges that the Related Documentation described in Section 1 and shared by the Depositor shall be available to Researchers via ISSDA’s website without restriction. ISSDA will make the metadata associated with the Dataset freely available. The metadata associated with the Dataset will be included in ISSDA’s databases and publications and will be accessible to everyone. The Depositor will make the Dataset available to ISSDA in a manner and through a medium that ISSDA deems suitable. The Depositor has identified the Dataset as not containing personal data. The Depositor warrants that the metadata and file names shall not contain any personal data. Only bibliographical data which exclusively refer to personal data that are necessary for the accountability of the Dataset, such as its creator, rights holders and citations (hereinafter: “Bibliographical Data”) are allowed. It is explicitly forbidden to include directly or indirectly identifying personal data in the deposited Dataset, the metadata and file names. The Depositor represents and warrants that the Dataset does not contain any personal data (as defined by Article 4 of the General Data Protection Regulation 2016/679 (“GDPR”)). The licence If it transpires that the Dataset contains personal data as defined by Article 4 of the GDPR, It is agreed that the Depositor will remain the controller of the Dataset within the meaning of th...
Dataset. 4.1. The Dataset will consist of all the files transferred by the Depositor and the metadata provided by the Depositor. Metadata is understood to mean the contents of all fields that must be completed in the archival system at the time of deposit in order to describe the Dataset.
4.2. The Depositor declares that the Dataset corresponds to the metadata provided by the Depositor.
4.3. The Dataset shall be compiled with due observance of the Netherlands Code of Conduct for Research Integrity, the GDPR and other applicable laws and regulations.
4.4. The metadata and file names shall not contain any personal data within the meaning of the GDPR. Only Bibliographical Data are allowed. It is explicitly forbidden to include personal data that are part of the deposited data, such as - but not limited to - research subjects, in the metadata and file names.
4.5. The Depositor will provide the files in a preferred format, as defined on the Depositary's website at the time of deposit. In the event that a format is not defined as a preferred format, the Depositor will contact the Depositary before delivery. A different file format may only be supplied with the written consent of the Depositary.
4.6. The Depositor will provide documentation with the Dataset that explains its creation, contents and any specific values (such as codes, characters and abbreviations), its structure (such as folder structures and relationships between files) and its actual use (such as that of software) to third parties.
4.7. The Depositor will make the Dataset available to the Depositary in a manner and through a medium that the Depositary deems suitable.
Dataset. Information or data from a database Service primarily devoted to market sizing by market segment and country, derived from a single (a) market segment and (b) country.
Dataset. Any data you provide to the Project is subject to the license agreement indicated in the Project’s source repository for the Materials.
Dataset. Dataset description
Dataset. The database we used has been developed within the subalpine GIG. Samples were collected between 1997 and 2010 in the sublittoral zone of 19 Austrian, 25 German, 21 France and 28 Italian subalpine lakes. 10 of those lakes were sampled in 2 different years while 1 lake was sampled in 3 different years, each lake-year combination has been considered as an indipendent sample unit. Invertebrates were indentifyed to the lower taxonomic level possible, mostly to genus/species level. Data gathered in more than one sampling site were aggregated to lake-year level. We considered climatic and morphological environmental variables (table 1): precipitation, mean annual temperature, difference between temperature in July and in January, lake surface area, lake mean depth and catchment area. The climatic data were gathered from the Climatic Research Unit (CRU) model (New et al. 2002; xxxx://xxx.xxx.xxx.xx.xx/). Table 1: Environmental variables ranges. min max Mean annual Prec. (cm) 60.16 162.67 Mean annual Temp. (°C) 5.17 12.99 T(July)-T(January) (°C) 17.40 21.60 surface (km2) 0.04 79.90 mean depth (m) 3.20 53.21 catchment (km2) 1.01 4551.60
Dataset. This Agreement begins on the final date of execution by both Parties and continues until the earlier of (i) CDPH’s decision to stop providing the COVID-19 Dataset, or (ii) two (2) years. After two (2) years, this Agreement will expire without further action. If the Parties wish to extend the Agreement, they may do so by reviewing, updating, and reauthorizing this Agreement.
Dataset. The dataset used for the study reported in this section is the same used by Xxxxx et al. (2009b) to derive ITA08, consisting of Nr 553 strong motion recordings relevant to a total number NE=106 earthquakes with moment magnitude MW varying from 4.0 to 6.9 and recorded at epicentral distances up to about 100 km (see Figure 2.
Dataset. The used dataset contains information taken from 118 Instagram fashion influencer’s accounts representing 2703 lines of text. For each fashion influencer, the pseudo name, the link to his profile picture, his biography and the most recent 100 posts are provided. Each post consists of a link to the published picture, the textual caption of the post together with some basic metrics as the number of comments and likes. We extract the textual data from this dataset which revolves around 100 textual captions of fashion influencer’s posts and we apply the following NLP tools.
Dataset. For Chinese-English (ZH-EN) translation, our training data for the translation task consists of 1.25M Chinese-English sentence pairs extracted from LDC corpora1. The NIST02 testset is chosen as the development set, and the XXXX00, 0Xxx corpora include LDC2002E18, LDC2003E07,LDC2003E14, Hansards portion of LDC2004T07, LDC2004T08 and LDC2005T06. # Model NIST WMT 1 EDR (Tu et al., 2017) N/A N/A 33.73 34.15 N/A N/A 2 DB (Xxxxx et al., 2018) 38.02 40.83 X/X X/X X/X X/X 3 Transformer(Base) 45.57 46.40 46.11 44.92 45.75 27.28 4 +lossmse 46.71† 47.23† 47.12† 45.78† 46.71 28.11† 5 +lossmse + enhanced 46.94† 47.52† 47.43† 46.04† 46.98 28.38† 6 Transformer(Big) 46.73 47.36 47.15 46.82 47.01 28.36 7 +lossmse 47.43† 47.96 47.78 47.39 47.74 28.71 8 +lossmse + enhanced 47.68† 48.13† 47.96† 47.56† 47.83 28.92†