Data Set Sample Clauses

Data Set. The MLS Data Set is copyrighted information concerning real estate which has been compiled by and belongs to MLSSAZ.
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Data Set. The Data Requestor agrees to use and the Agency agrees to disclose the following Data Set, with the variables delineated in Exhibit “B”, to the Data Requestor for use by the Data Requestor in the performance of the Activities described above.
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Data Set. Covered Entity agrees to share the following data with Data User: [insert description, or include as an attachment] (the "Data Set"). Such Data Set shall not contain any of the following identifiers of the individual(s) who is(are) the subject(s) of the Protected Health Information, or of relatives, employers or household members of the individual(s): names; postal address information, other than town or city, state and zip code; telephone numbers; fax numbers; electronic mail addresses; social security numbers; medical record numbers; health plan beneficiary numbers; account numbers; certificate/license numbers; vehicle identifiers and serial numbers, including license plate numbers; device identifiers and serial numbers; Web Universal Resource Locators (URLs); Internet Protocol (IP) address numbers; biometric identifiers, including finger and voice prints; and full face photographic images and any comparable images.
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Data Set. In this paper, we present the development of a training data set for Dutch Named Entity Recognition (NER) in the archaeology domain. This data set was created as there is a dire need for semantic search within archaeology, in order to allow archaeologists to find structured information in collections of Dutch excavation reports, currently totalling around 60,000 (658 million words) and growing rapidly. To guide this search task, NER is needed. We created rigorous annotation guidelines in an iterative process, then instructed five archaeology students to annotate a number of documents. The resulting data set contains roughly 31k annotations between six entity types (artefact, time period, place, context, species & material). The Inter Annotator Agreement (IAA) is 0.95, and when we used this data for machine learning, we observed an increase in F1 score from 0.51 to 0.70 in comparison to a machine learning model trained on a data set created in prior work. This indicates that the data is of high quality, and can confidently be used to train NER classifiers.
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Data Set. 2.1 The Data Controller holds two different data sets on households receiving benefits.
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Data Set. ‌ We used the Twitter Stream API, which provides a random sample comprising 1% of all tweets created in the world on a day. In order to form our collection, we collected all mes- sages provided by the API between January and June 2014 together with the available meta-information published in JSON format via the Stream API. This process yielded a collection of 784 million tweets from which 262 million are in English. Subsequently, we automatically selected 113K tweets (from 262 million English) on 10 controversial topics ”Obama”, ”Xxxx”, ”Xxxx Xxxx”, ”Xxxxxx Xxxxxx”, ”Islam”, ”Lakers”, ”Youtube”, ”iPad”, ”An- droid” and ”Microsoft”. Furthermore, we ended up with 17k tweets after applying following steps of Twitter Pre-Filtering component along with other steps
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Data Set. But this task only looks at common, general-domain entities and is not compa- rable to our data set (Xxxxx Xxx Xxxx, 2002). In the archaeology domain, NER data sets exist in other languages (English and Swedish), created in the ARIADNE project (Vlachidis et al., 2017). To our knowledge, the only directly related data set that deals with both Dutch and archaeological texts is another data set created in the same ARIADNE project, as briefly described in the introduction. As we are going to show in this paper, the data set we have created is of better quality and much larger than the ARIADNE data.
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Data Set. 2.1. The Client shall provide Xxxx Xxxx with such necessary documents, data and assistance relating to the Client’s trade data as agreed between Xxxx Xxxx and the Client (the “Data Set”) in order to enable Xxxx Xxxx to provide the Services on the terms of the agreement.
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Data Set. The data set that was used in this master’s thesis consisted of data from 2009 to 2017. It is important to state that the decision was made to focus on two years, in particular 2012 and 2013, since an analysis for each year would have been excessive. These years are not chosen randomly, since research has shown that re-election purposes are a crucial incentive for pork barrel politics. Therefore, this master’s thesis will examine the two years before the Flemish elections of 2014. The research question and hypotheses will thus be examined for both years individually and in the end, a comparison can be made. This third section is structured as follows, first the used method will be explained and second, the variables that were used in the analyses will be explained.
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Related to Data Set

  • Data Services In lieu of any other rates or discounts, the Customer will receive a discount of 20% for the following Data Services: Access: Standard VBS2 Guide local loop charges for DS1 and DS-3 Access Service.

  • Data Security The Provider agrees to utilize administrative, physical, and technical safeguards designed to protect Student Data from unauthorized access, disclosure, acquisition, destruction, use, or modification. The Provider shall adhere to any applicable law relating to data security. The provider shall implement an adequate Cybersecurity Framework based on one of the nationally recognized standards set forth set forth in Exhibit “F”. Exclusions, variations, or exemptions to the identified Cybersecurity Framework must be detailed in an attachment to Exhibit “H”. Additionally, Provider may choose to further detail its security programs and measures that augment or are in addition to the Cybersecurity Framework in Exhibit “F”. Provider shall provide, in the Standard Schedule to the DPA, contact information of an employee who XXX may contact if there are any data security concerns or questions.

  • Data Segregation a. DSHS Data must be segregated or otherwise distinguishable from non-DSHS data. This is to ensure that when no longer needed by the Contractor, all DSHS Data can be identified for return or destruction. It also aids in determining whether DSHS Data has or may have been compromised in the event of a security breach. As such, one or more of the following methods will be used for data segregation.

  • Data Storage Where required by applicable law, Student Data shall be stored within the United States. Upon request of the LEA, Provider will provide a list of the locations where Student Data is stored.

  • Privacy and Data Security (a) The parties will keep confidential any information regarding the Company, Nationwide, the Variable Accounts, and Contract Owners received in connection with providing services and meeting their respective obligations hereunder, except: (a) as necessary to provide the services or otherwise meet their respective obligations under this Agreement; (b) as necessary to comply with applicable law; and (c) information regarding the Variable Accounts which is otherwise publicly available. The parties will maintain internal safekeeping procedures to safeguard and protect the confidentiality of the data transmitted to another party or its designees or agents in accordance with Section 248.11 of Regulation S-P (17 CFR 248.1–248.30) (“Reg S-P”) and any other applicable federal or state privacy laws and regulations, including without limitation 201 CFR 17.00 et seq. and applicable security breach notification regulations (collectively “Privacy Laws”). Each party shall use such data solely to effect the services contemplated herein, and none of the parties will directly, or indirectly through an affiliate, disclose any non-public personal information protected under Privacy Laws (“Non-public Personal Information”) received from another party to any person that is not an affiliate, designee, service provider, or agent of the receiving party and provided that any such information disclosed to an affiliate, designee, service provider, or agent will be under the same or substantially similar contractual limitations on use and non-disclosure and will comply with all legal requirements. The Company will not use information, including Non-public Personal Information, directly or indirectly provided to it by Nationwide or its designees or agents pursuant to this Agreement for the purpose of marketing to Contract Owners or any other similar purpose, except as may be agreed by the parties hereto. Except for confidential information consisting of Non-public Personal Information, which will be governed in all respects in accordance with the immediately preceding sentence, confidential information does not include information which (i) was publicly known and/or was in the possession of the party receiving confidential information (“Receiving Party”) from other sources prior to the Receiving Party’s receipt of confidential information from the party disclosing confidential information (“Disclosing Party”), or (ii) is or becomes publicly available other than as a result of a disclosure by the Receiving Party or its representatives, or (iii) is or becomes available to the Receiving Party on a non-confidential basis from a source (other than the Disclosing Party) which, to the best of the Receiving Party’s knowledge, is not prohibited from disclosing such information to the Receiving Party by a legal, contractual, or fiduciary obligation to the Disclosing Party, or (iv) describes the fees payable to Nationwide under this Agreement.

  • Data Security and Privacy Plan As more fully described herein, throughout the term of the Master Agreement, Vendor will have a Data Security and Privacy Plan in place to protect the confidentiality, privacy and security of the Protected Data it receives from the District. Vendor’s Plan for protecting the District’s Protected Data includes, but is not limited to, its agreement to comply with the terms of the District’s Bill of Rights for Data Security and Privacy, a copy of which is set forth below and has been signed by the Vendor. Additional components of Vendor’s Data Security and Privacy Plan for protection of the District’s Protected Data throughout the term of the Master Agreement are as follows:

  • Data Subjects The categories of Data Subjects who we may collect Personal Data about may include the following where they are a natural person: the Customer, the directors and ultimate beneficial owner(s) of the Customer, your customers, employees and contractors, payers and payees. You may share with Airwallex some or all of the following types of Personal Data regarding Data Subjects: • full name; • email address; • phone number and other contact information; • date of birth; • nationality; • public information about the data subject; • other relevant verification or due diligence documentation as required under these terms; and • any other data that is necessary or relevant to carry out the Agreed Purposes.

  • Data Access Services State Street agrees to make available to the Fund the Data Access Services subject to the terms and conditions of this Addendum and such data access operating standards and procedures as may be issued by State Street from time to time. The Fund shall be able to access the System to (i) originate electronic instructions to State Street in order to (a) effect the transfer or movement of cash or securities held under custody by State Street or (b) transmit accounting or other information (the transactions described in (i)(a) and (i)(b) above are referred to herein as “Client Originated Electronic Financial Instructions”), and (ii) access data for the purpose of reporting and analysis, which shall all be deemed to be Data Access Services for purposes of this Addendum.

  • REMOTE ACCESS SERVICES ADDENDUM The Custodian and each Fund agree to be bound by the terms of the Remote Access Services Addendum hereto.

  • Data Security and Privacy 12.1 SERVICE PROVIDER acknowledges the importance of Data Security and agrees to adhere to the Terms and Conditions of the Data Security Policy of IIMC.

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