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Open Data Policy

Overview

Open data is considered a subset of public information, classified according to the levels outlined in the Data Classification Policy. This type of data can be used, reused, and shared by any individual or entity without restrictions. In line with efforts to enhance knowledge and promote a culture of open data, a set of guidelines and procedures has been developed, derived from the National Data Governance Policies issued by the National Data Management Office.

Objectives

This policy aims to define and establish the requirements related to the publication of open data by applying the legislative requirements specified in the documents:

  • Data Management, Governance, and Protection of Personal Data Controls (Version 1.5 – January 2021)

  • National Data Governance Policies (Second Edition – May 26, 2021),
    both issued by the National Data Management Office.

Purpose of Open Data Policy:

  • Define the general rules, obligations, and mechanisms for measuring compliance.

  • Enable the effective utilization of published open data.

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    		 Principle  Description
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    		 The Principle of Availability: Publicly classified data is made accessible to everyone, as it qualifies as open data suitable for publication and access—unless its nature requires non-disclosure.
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    		 Open Format and Machine-Readability:
    • Open data is provided in a machine-readable format that allows for automated processing. It is stored using commonly used file formats.
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    		 Currency of Data:
    • The latest version of available open data sets is published regularly and made accessible to the public. University-collected data is released promptly upon completion, with priority given to time-sensitive data that loses value over time.
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    		 Comprehensiveness:
    • Open data must be comprehensive, reflect actual recorded data, and include as many publishable details as possible—without violating related laws and regulations. Metadata should accompany the data to clarify and explain the raw content, including interpretations and formulas used to derive or calculate the data.
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    		 Non-Discrimination:
    • Open data must be accessible to everyone equally, without requiring registration. Anyone, whether an individual or an entity, can access the published open data at any time without identity verification or justification.
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    		 No Financial Charges:
    • Open data is made available to the public free of charge.
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    		 Data Licensing:
     
    • The university’s open data is subject to a license that defines the legal basis for its use, including applicable terms, obligations, and restrictions. Accessing open data is considered acceptance of the terms stated in the open data license.
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    		 Developing a Governance Model and Inclusivity:
    • Through the National Open Data Platform, open data enables public access and participation. It supports informed decision-making and enhances service delivery.
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    		 Comprehensive Development and Innovation:
    • The university promotes the reuse of open data by providing the necessary resources and expertise to achieve integration and support innovation.

  • Open Data Regulations and Specifications:

  • The field of open data consists of five regulations and specifications, which are a set of specific public information that is machine-readable, freely accessible to the public, and available without restrictions. This data is made available through a national open data platform, and any individual, public entity, or private organization can use or share it.

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  • Data Valuation for Determining Open Data Sets

  • The process of data valuation is conducted in several key stages to enable the publication of as much open data as possible. The stages are as follows:

  • Step 1: Identifying Public Data

  • Data must be classified according to the university's Data Classification Policy.

  • The benefits and potential applications of the public data in various fields such as health, education, social, inter-sectorial, etc., should be identified.

  • Step 2: Assessing the Benefit of the Data

  • The main factors that contribute to evaluating the value of data (Usefulness) must be studied. These factors include:

    • Completeness of data

    • Accuracy

    • Consistency

    • Timeliness

    • Restrictions on data usage

    • Exclusivity for the university

  • The risks associated with publishing the data as open data should be evaluated in terms of compliance with local regulations such as the Personal Data Protection Policy and the Cybercrimes Law.

  • Periodically ensure that open data users cannot analyze or access it in ways that would allow for the combination with other data to breach local regulations. This review should be carried out at least annually.

  • Lifecycle of Open Data:
    (Continue with details on the open data lifecycle, if available)

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