ASWI - Pokročilé softwarové inženýrství » ASWI 2021 » OpenData vlastní téma (KIV) - Tři Mušketýři

h1. Data sources

h2. ZČU opne data

All ZČU data can be downloaded in formats xml, csv and json.

As discussed in further chapters there are certain complications with data sources not providing sufficient data granuality or amount. However there is a possibility that the data will in future contain more suitable datasets, and such should be at least acknowledged to some degree. However this is more of a topic for [[Prediction models]], where it will be further discussed.

Table with faculties and room prefixes belonging to those faculties

|_. Faculty |_. Prefix |

| Fakulta strojní | UV, UU, UK, UL, UP, UF |

| Fakulta ekonomická | UV, UU, UK, UL, UP, UF |

| Fakulta elektrotechnická | EU, EK, EL, EP, ES, ET, EH, EZ |

| Fakulta designu a umění | LS |

| Fakulta filozofická | JJ, RJ, RS, SP, SD, ST, SO |

| Fakulta pedagogická | CH, VC, KL | 

| Fakulta ekonomická Cheb | CD |

| Fakulta zdravotních studií | HJ |

| Fakulta aplikovaných věd | UN, UC,US |

| Fakulta právnická | PC, PS |

h3. Historical weather data

Link to data: http://opendata.zcu.cz/Energeticky-dispecink.html

Data contains:

* datum_a_cas - date and time, time at which the values were measured with hour accuracy

* teplota - average temperature in given time slot (°C)

* vitr - average wind speed in given time slot (m/s)

* dest - value signifying rain (1) and no rain (0)

* svetelnost - average value of luminance (k lux)

For further processing luminance will be translated to the terms "sunny", "overcast" and "cloudy". In the 2019 data are values between 0 and 83.2k lux.

Lux values can be understood using the following table:

|_. Conditions |_. Value (lux) |

| Sunlight | 107527 |

| Full Daylight	| 10752 |

| Overcast Day	| 1075 |

| Very Dark Day	| 107 |

| Twilight	| 10.8 |

| Deep Twilight	| 1.08 |

| Full Moon	| 0.108 |

| Quarter Moon	| 0.0108 |

| Starlight	| 0.0011 |

| Overcast Night | 0.0001|

Source: https://www.engineeringtoolbox.com/light-level-rooms-d_708.html

However, upon comparing values in data with archived weather predictions it seems more like the following table would be appropriate:

|_. Conditions |_. Value (k lux) |

| Direct sungligt | >60 |

| Sunny | 40-60 |

| Overcast | 20-40 |

| Cloudy | 10-20 |

| Night | 0 |

Used weather archive: https://www.in-pocasi.cz/archiv/archiv.php?historie=2019-12-01&region=9

h3. JIS data

Link to data: http://opendata.zcu.cz/Snimace-JIS.html

Data contains:

* datum_a_cas - timestamp of JIS authentication (accuracy in milliseconds)

* pocet_logu - number of authentized users in given time

* popis_objektu - description of object according to standard ZČU tagging

On the linked page there is written that " ... Data about dorms, the entry to laboratories and other spaces with restricted access, informations about university canteen, checkouts in univeristy library, access to copy machines etc can be interesting for students ...". However not all of these places can be found in said data. In data from 2019 are present only 47 places, and most of them are dorms, parking lots and buffets.

There is a possibility that in the future the number of logged places will increase, however it is also possible that the data was affected by GDPR and more detailed data now won't be provided for the public anymore.

Possible solution is to assign provided spaces to buildings.

_table of which is which / how it will be assigned_

h3. WebAuth data

Link to data: http://opendata.zcu.cz/Autentizacni-system.html

Data contains:

* datum - date of access

* budova - building tag

* hodina_zacatek - start of lecture

* hodina_konec - end of lecture

* pocet_prihlaseni - number of successfull sign-ins to given computer in given lecture

* stroj_hostname - name of specific computer

* typ_objektu - type of object (classroom, laboratory, lecture room, other)

* ucebna_nazev - specific name of room

* vyucovaci_hodina - number of lecture (according to the timetable)

On the linked page there is written that " Pomocí přihlašování přes orion login a password lze také sledovat i přihlašování na stroje ZČU a s tím související využití počítačových učeben. " however it seems quesstionable if really all computer logins are in this data. Since it contains only 106 different rooms for all of ZČU in data from  the year 2019, which seems suspicious especially since some rooms that we know that they are equipped with computers and are being used (at least sometimes) are not present.

So, it would be possible to again assign those rooms to the appropriate buldings and go off the assumption that a similar set of students will be attending lessons in the same building (which is often the case at least with KIV lectures).

h3. Occupancy data

Link to data: http://opendata.zcu.cz/Obsazeni-mistnosti.html

Data contains:

* rok_platnosti - rok platnosti

* budova - zkratka budovy (viz výše)

* ucebna_nazev - název konkrétní učeny

* typ_objektu - učebna/laboratoř/posluchárna/jiné

* kapacita_objektu - maximální kapacita výukové místnosti

* obsazeni - počat zapsaných studentů na výukovou akci v dané učebně v daném čase

* predmet - zkratka rozvrhové akce

* typ_akce - seminář/přednáška/cvičení

* vyucovaci_hodina - vyučovací hodina (dle rozvrhu)

* hodina_zacatek

* hodina_konec

* semestr - rozdělení dle LS(letního) a ZS(zimního) semestru

* tyden - S(sudý), L(lichý), K(každý),J(jiný)

* tyden_v_roce- týden/rok

* datum - konkrétní datum

h2. Weather data

Link to data: http://wttr.in/Plzen,czechia?format=j1

Data contains:

json file

Data processing: