The use of cloud for generated statistics data file storage in statistics tasks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23510%2F22%3A43966240" target="_blank" >RIV/49777513:23510/22:43966240 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.divai.sk/assets/divai2022.pdf" target="_blank" >https://www.divai.sk/assets/divai2022.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

The use of cloud for generated statistics data file storage in statistics tasks

Popis výsledku v původním jazyce

The paper builds on previous work that dealt with the automatic generator of parameterized tasks and tests. In these works, the author focused mainly on the issue of automatic generation of parameterized tasks in the field of data science. A key problem in creating tasks of this type is the generation of source data and especially their storage and subsequent access in various systems and formats. This contribution is an innovation of previously used procedures and an extension of the possibilities of working with synthetic data files. The innovative data storage system uses cloud storage for its work and thus simplifies the work of the generator user when generating tasks that also contain the statistics data stored in the data file. No knowledge of cloud technologies is required to generate these tasks. In this solution we can work with the statistics tasks containing data files not only in format of selected LMS (for example LMS Moodle), but we can work with these tasks published in PDF format, where the data is represented by a link to the cloud storage. The contribution is more technical and contains the procedures and codes needed to work with cloud storage in both directions – data storage and data retrieval. These procedures also include instructions that allow you to create and use cloud storage. An integral part of the solution is also the design of the administration system of stored data and their periodic cleaning.

Název v anglickém jazyce

The use of cloud for generated statistics data file storage in statistics tasks

Popis výsledku anglicky

The paper builds on previous work that dealt with the automatic generator of parameterized tasks and tests. In these works, the author focused mainly on the issue of automatic generation of parameterized tasks in the field of data science. A key problem in creating tasks of this type is the generation of source data and especially their storage and subsequent access in various systems and formats. This contribution is an innovation of previously used procedures and an extension of the possibilities of working with synthetic data files. The innovative data storage system uses cloud storage for its work and thus simplifies the work of the generator user when generating tasks that also contain the statistics data stored in the data file. No knowledge of cloud technologies is required to generate these tasks. In this solution we can work with the statistics tasks containing data files not only in format of selected LMS (for example LMS Moodle), but we can work with these tasks published in PDF format, where the data is represented by a link to the cloud storage. The contribution is more technical and contains the procedures and codes needed to work with cloud storage in both directions – data storage and data retrieval. These procedures also include instructions that allow you to create and use cloud storage. An integral part of the solution is also the design of the administration system of stored data and their periodic cleaning.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

DIVAI 2022 - 14th International Scientific Conference on Distance Learning in Applied Informatics

ISBN

978-80-7676-410-1

ISSN

2464-7470

e-ISSN

2464-7489

Počet stran výsledku

11

Strana od-do

373-383

Název nakladatele

Wolters Kluwer

Místo vydání

Prague

Místo konání akce

Štúrovo

Datum konání akce

2. 5. 2022

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—