
KIFU_OS_newsfeed_data_2022_08.csv
KIFU_OS_newsfeed_data_2022_08.xlsx
KIFU_OS_newsfeed_stat_anal_2022_08.sav

The open science newsfeed of KIFÜ was launched for the test phase in April 2021, and the live, daily-weekly updates were started later on. The newsfeed originally was published under https://kifu.gov.hu/ni4os/hirek. During Summer 2022, the major redesigning of KIFÜ's web-page concluded in a new site under https://kifu.gov.hu/ni4os-hirek/. All earlier posts have been migrated to the new platform, and earlier URLs have been redirected to the new sites.
The analysis covers 133 posts that were published in the open science newsfeed of KIFÜ between 5 May 2021 and 7 April 2022. We collected the number of individual views of each item, filtering out multiple viewings by the same users. Then we have categorized the posts according to different aspects such as type, topic focus (international or local focus) and open science field. During the analysis, the distribution of items by category can be considered as a representation of the communication goals, while the number of views is a representation of the needs of the target group. Considering the shortcoming that the target group could only choose from what was presented in the newsfeed. Analyses were carried out through simple descriptive statistics and examining possible significant differences among variables by using the software SPSS 21.0.

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ni4os_hungary_event_registrants.xlsx

Attendee list of the Hungarian Open Science Forum events.
All sheets refer to one of the events, which took place on 28/5/2021, 24/9/2021, 19/1/2022, and 28/4/2022.
For the analysis, all data of registrants who had not attended the meeting have been removed from the dataset. Thanks to the registration form, we are able to analyse the attendee affiliations and professions. For this three groups were formed: researchers, librarians (meaning all library staff, including IT specialists, data stewards, etc.), organisers (all KIFÜ and DEENK staff). Where ‘profession’ field was left blank during registration, affiliation and e-mail fields helped to coin the most fit group for the attendee type.
All name, e-mail, and affiliation fields have been removed from the dataset.
