ISLAMABAD: Media Matters for Democracy has announced the first edition of the Pakistan Data Journalism Awards in order to encourage and promote data-driven journalism in Pakistan.
The Pakistan Data Journalism Awards aim to encourage data-driven news reporting and investigative journalism in Pakistan.
The awards will celebrate investigations and data-driven stories produced and published by Pakistani journalists and news organisations that showed the truth to power, enhanced government accountability, and promoted the public interest.
The awards contest is funded through Media Matters for Democracy’s Media for Transparency initiative, which delivers data-driven training courses and workshops for local journalists and promotes the use of public records for news reporting on government accountability and transparency.
1) The awards contest is open to all local journalists working for print, broadcast, and digital publications. Teams of journalists, news organisations, freelancers, citizen journalists, and contributors to news publications can also submit entries to the contest.
2) The contest is only open to works published or broadcast between 1 January 2018 and 31 January 2019.
3) There are no submission fees.
4) An entry to the contest could be a single news report or a series of news reports.
5) An individual or organisation can submit multiple entries in a single category (except the portfolio category, for which each participating journalist can only submit once).
6) An individual or organisation can submit entries to more than one category.
7) Any instance of plagiarism will lead to immediate disqualification.
8) Submission of unpublished works will not be accepted.
9) For works in languages other than English and Urdu, please provide a translation of the published story or translated transcript of the broadcast report.
10) Some categories are divided by types of media. If you incorrectly submit a piece (for example, a newspaper article) to a category designed for a different type of media (for example, broadcast), we will automatically assign it to the appropriate category.