README.md

@@ -19,9 +19,41 @@ In diesem GitLab Repo finden Sie:
 - Requirements (`requirements.txt`): Beschreibt die pip-Umgebung, nicht relevant für die Ausarbeitung
 - Matplotlib Style (`FST.mplstyle`): Einstellung für Matplotlib nach der FST-Institut-Vorschrift
 
+### Numpy Quick Start Quide
+`numpy.ndarray` ist eine sehr effiziente Datenstruktur im Python-Package `numpy`, die von Datenwissenschaftlern jeden Tag gebraucht wird. Einige Beispiele werden hier gezeigt.
+
+Initializierung von `numpy.ndarray`:
+```python
+import numpy as np
+
+a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
+```
+Anders als `list` müssen die Elemente im `ndarray` von gleichen Typen (zum Beispiel `float64`) sein. Und das Array muss wie eine Matrix in der Mathematik aussehen. Das heißt, die Anzahl der Elemente bei jeder Spalte bzw. Zeile gleich ist.
+
+`numpy.ndarray` erleichert die mathematische Berechnung:
+```python
+# Assuming that each element in "a" is the radius of a circle,
+# the area of each circle can be calculated in this way.
+area = np.pi * a ** 2
+# Print the array.
+print(area)
+# Print a element in the array.
+print(area[0, 3])
+```
+Es ist möglich, Statistik des Arrays durch Build-in Funktionen von `numpy` zu brechen.
+```python
+a_mean = a.mean()
+print(a_mean)
+# Calculate the average of each column.
+a_mean_first_dimension = a.mean(0)
+print(a_mean_first_dimension)
+```
+
 ### Links
 Mehr Infomationen über die Datenstruktur sind in der [README.md](https://git.rwth-aachen.de/fst-tuda/public/lehre/calorimetry_home/-/blob/main/README.md) des Küchentischversuches zu finden.
 
+[NumPy: the absolute basics for beginners](https://numpy.org/doc/stable/user/absolute_beginners.html)
+
 [h5py Quick Start Guide](https://docs.h5py.org/en/stable/quick.html)
 
 [NumPy Fundamentals](https://numpy.org/doc/stable/user/basics.html)

ausarbeitung_laborversuch_v2.ipynb

-%% Cell type:markdown id: tags:
-
-# Kalorimetrie Laborversuch
-
-Author: XXXXX
-
-Datum: XXXXX
-
-Gruppe: XXXXX
-
-%% Cell type:markdown id: tags:
-
-## Forschungsfrage
-
-Formulieren Sie eine oder mehrere Forschungsfragen zu diesem Versuch.
-
-%% Cell type:markdown id: tags:
-
-
-%% Cell type:markdown id: tags:
-
-## Versuchsaufbau und Durchführung
-
-Beschreiben Sie den Versuchsaufbau und die Versuchsdurchführung. Nutzen Sie hier Ihr eigenes Bild.
-
-%% Cell type:markdown id: tags:
-
-<img src="figures/kalorimetrie_pruefstand.jpg" width="800">
-
-%% Cell type:markdown id: tags:
-
-## Versuchsauswertung
-
-%% Cell type:code id: tags:
-
-``` python
-import numpy as np
-from matplotlib import pyplot as plt
-import h5py as h5
-# If you plan to write functions in another module,
-# you can use importlib.reload(module) to reload the module
-# at the beginning of each cell in order to make the latest
-# changes take effect without restart the kernel.
-import importlib
-
-from functions import m_json
-
-# Use FST-Style, if you don't like it, you can safely delete this line.
-plt.style.use("FST.mplstyle")
-```
-
-%% Cell type:markdown id: tags:
-
-### Kalorimeterkonstante
-
-Hinweis: Nutzen Sie die Funktionen *get_ids_from_setup* und *get_json_entry* um auf Metadaten zuzugreifen.
-
-Sie sollten Ihr Programm zwischen TODO und DONE implementieren, und versuchen die Anweisung zu verfolgen. Das ist aber nicht erforderlich.
-
-%% Cell type:markdown id: tags:
-
-#### (i) Messdaten einlesen
-
-Messdaten werden in das Notebook eingelesen.
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Define the path to hdf5 file, which containing experiment data for constant.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read all experimental data and associated metadata from HDF5 files for data processing.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (ii) Mittelwert und Standardabweichung für Plots bestimmen
-
-Die Mittelwerte und Standardabweichungen der Messungen werden in der nächsten Sektion geplottet.
-
-Nachdem die Mittelwerte und Standardabweichungen berechnet wurden, können Daten jeder Wärmequelle jeweils in einem numpy.ndarray gespeichert werden.
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculate the average value and standard deviation of sensors.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iii) Daten ploten
-
-Im Kalorimeter befinden sich mehrere Sensoren, deren Mittelwerte sowie Standardabweichungen der Messung an jeden Zeitpunkt bestimmt wurden. Die Messdaten bzw. ihre Mittelwerte müssen auf ein Scatter Plot eingetragen werden. Die Standardabweichungen der Sensoren sind als Errorbar im Plot zu sehen.
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Use the temperature and time data for plotting
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iv) Metadaten auslesen
-
-Die notwendigen Daten bzw. Metadaten für die Berechnung der Wärmekapazität wird ausgelesen.
-
-%% Cell type:code id: tags:
-
-``` python
-# Heat capacity of Water has been given
-water_heat_capa = 4.18
-
-# TODO: Read mass of the water from the metadata of the experiment.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Reading heater related data from hdf5 file, please use the same datafile_path_const variable for the HDF5 path.
-# Hint: Note whether the data is stored as an array or a scalar in the hdf5 dataset.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (v) Anfangs- und Endwert der Temperatur
-Die Anfangs- und Endwert der Temperatur im Kloriemeter sind notwendig, um die Wärmekapazität zu bestimmen.
-
-Eine Möglichkeit wäre, durch das Maxium bzw. Minium und einen Schwellenwert ist ein Teil der Daten zu entnehmen.
-
-Daraus sind Mittelwerte zu berechnen. Die entsprechenden Mittelwerte können als Anfangs- und Endtemperatur verwendet werden.
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculation of temperature data necessary to determine the specific heat capacity
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (vi) Kalorimeterkonstante bestimmen
-$$
-C = \frac{UI\Delta t}{(T_2 - T_1)}
-$$
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculate heat capacity of the calorimeter
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (Vii) Ergebnis
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Print result
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-### spezifische Wärmekapazität: erste Probe
-
-%% Cell type:markdown id: tags:
-
-#### (i) Messdaten einlesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Define the path to hdf5 file, which containing experiment data for constant.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read all experimental data and associated metadata from HDF5 files for data processing.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (ii) Mittelwert und Standardabweichung für Plots bestimmen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculate the average value and standard deviation of sensors.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iii) Daten ploten
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Use the temperature and time data for plotting.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iv) Metadaten auslesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read mass of the sample from the metadata of the experiment.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (v) Anfangs- und Endwert der Temperatur
-Die Mischungstemperatur und Anfangstemperatur des Kalorimeters sind für die Berechnung relevant.
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculation of temperature data necessary to determine the specific heat capacity
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Determine the initial temperature of the sample.
-# Since the temperature of the water bath is stable, the initial temperature
-# of the sample can be taken as the average of the 10 data after the start of the measurement.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (vi) spezifische Wärmekapazität bestimmen
-$$
-c_p = \frac{C(T_M-T_1)}{m_p(T_2-T_M)}
-$$
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calulate specific heat capacity of the sample.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (Vii) Ergebnis
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Print result
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-### spezifische Wärmekapazität: zweite Probe
-
-%% Cell type:markdown id: tags:
-
-#### (i) Messdaten einlesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Define the path to hdf5 file, which containing experiment data for constant.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read all experimental data and associated metadata from HDF5 files for data processing.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: In order to be able to process data from sensors with the same position,
-# it is first necessary to obtain the index of the sensors with different positions in the list.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (ii) Mittelwert und Standardabweichung für Plots bestimmen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculate the average value and standard deviation of sensors.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iii) Daten ploten
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Use the temperature and time data for plotting.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iv) Metadaten auslesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read mass of the sample from the metadata of the experiment.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (v) Anfangs- und Endwert der Temperatur
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculation of temperature data necessary to determine the specific heat capacity
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Determine the initial temperature of the sample.
-# Since the temperature of the water bath is stable, the initial temperature
-# of the sample can be taken as the average of the 10 data after the start of the measurement.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (vi) spezifische Wärmekapazität bestimmen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calulate specific heat capacity of the sample.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (Vii) Ergebnis
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Print Result
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-### spezifische Wärmekapazität: dritte Probe
-
-%% Cell type:markdown id: tags:
-
-#### (i) Messdaten einlesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Define the path to hdf5 file, which containing experiment data for constant.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read all experimental data and associated metadata from HDF5 files for data processing.
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: In order to be able to process data from sensors with the same position,
-# it is first necessary to obtain the index of the sensors with different positions in the list.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (ii) Mittelwert und Standardabweichung für Plots bestimmen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculate the average value and standard deviation of sensors.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iii) Daten ploten
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Use the temperature and time data for plotting.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (iv) Metadaten auslesen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Read mass of the sample from the metadata of the experiment.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (v) Anfangs- und Endwert der Temperatur
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calculation of temperature data necessary to determine the specific heat capacity
-
-
-# DONE #
-```
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Determine the initial temperature of the sample.
-# Since the temperature of the water bath is stable, the initial temperature
-# of the sample can be taken as the average of the 10 data after the start of the measurement.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (vi) spezifische Wärmekapazität bestimmen
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Calulate specific heat capacity of the sample.
-
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-#### (Vii) Ergebnis
-
-%% Cell type:code id: tags:
-
-``` python
-# TODO: Print result
-
-# DONE #
-```
-
-%% Cell type:markdown id: tags:
-
-## Genutzte Daten und Metadaten
-
-Geben Sie an welche Daten Sie verwenden und wie diese aufgebaut sind. Erklären Sie weiterhin in wenigen Sätzen das genutzte Metadaten-Konzept, sodass eine andere Person Ihre genutzten Daten versteht.
-
-%% Cell type:markdown id: tags:
-
-
-%% Cell type:markdown id: tags:
-
-## Analyse
-Analysieren Sie Ihre Ergebnisse aus wissenschaflticher Sicht. Berücksichtigen Sie dabei Ihre oben genannte Forschungsfrage. Wie wirkt sich die mit der Probe aus dem Heißwasserbad transportierte Wassermenge auf das Ergebnis aus? Welche weiteren Fehlerquellen gibt es?
-
-%% Cell type:markdown id: tags:
-
-
-%% Cell type:markdown id: tags:
-
-## Fazit
-Ziehe Sie ein persönliches Fazit zum Versuch.
-
-%% Cell type:markdown id: tags:
-

data/Heat_Capacity/actor_immersionHeater_1ee21744-0355-6023-94b4-d5c041dd32cd.json

+{
+	"JSON": {
+		"ID": "1ee21744-0355-6023-94b4-d5c041dd32cd",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"actor": {
+		"type": "immersion heater",
+		"manufacturer": "Zhuodingsen",
+		"power_supply": {
+			"voltage": 12,
+			"type": "DC voltage",
+			"source": {
+				"type": "adjustable laboratory power supply",
+				"model": "DPPS-32-20",
+				"manufacturer": "VOLTCRAFT",
+				"power": "640 Watt",
+				"technology": "clocked power supply",
+				"voltage": "1...32 V",
+				"current": "0...20 A",
+				"residual ripple": "<5 mV"
+			}
+		}
+	}
+}

data/Heat_Capacity/calorimeter_1ee5ec0c-0b57-68cd-9d39-c9b7e9b18753.json

+{
+	"JSON": {
+		"ID": "1ee5ec0c-0b57-68cd-9d39-c9b7e9b18753",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"calorimeter": {
+		"type": "heat flow calorimeter",
+		"manufacturer": "Fluidsystemtechnik",
+		"container": {
+			"type": "beaker",
+			"volume": {
+				"value": 600,
+				"unit": "milliliter"
+			}
+		},
+		"medium": {
+			"type": "water",
+			"mass": {
+				"value": 400,
+				"unit": "gramm",
+				"accuracy": {
+					"value": 0,
+					"type": "absolute",
+					"unit": "gramm"
+				}
+			}
+		}
+	}
+}

data/Heat_Capacity/group_1ee5ec0a-1830-63f5-ac3e-6f8ce4468546.json

+{
+	"JSON": {
+		"ID": "1ee5ec0a-1830-63f5-ac3e-6f8ce4468546",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"group": {
+		"number": "Laborversuch_Group37",
+		"author": [
+			"Diogo Fernandes Costa",
+			"Zidane Bürmann",
+			"Santiago Ramirez Saldana"
+		],
+		"experiment": "calorimetry",
+		"testrig_number": "1"
+	}
+}

data/Heat_Capacity/instrument_raspPi_1ee5ec0d-e77c-68b7-90f7-2e33485ff91c.json

+{
+	"JSON": {
+		"ID": "1ee5ec0d-e77c-68b7-90f7-2e33485ff91c",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"instrument": {
+		"name": "raspberry_pi",
+		"type": "single_board_computer",
+		"manufacturer": "Raspberry Pi Foundation",
+		"model": "Raspberry Pi 4 Model B Rev. 1.5",
+		"serial": "10000000dbd18662",
+		"operating_system": "Raspberry Pi OS",
+		"comment": "to get model and serial number put this code in the terminal: cat /proc/cpuinfo"
+	}
+}

data/Heat_Capacity/sensor_tempCalorimeter1_1ee5ec00-4a00-68a1-bb1e-873c2dd4dbde.json

+{
+	"JSON": {
+		"ID": "1ee5ec00-4a00-68a1-bb1e-873c2dd4dbde",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3c01f0956007",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}

data/Heat_Capacity/sensor_tempCalorimeter2_1ee5ec03-7e64-6071-8ca3-98dbab0a7719.json

+{
+	"JSON": {
+		"ID": "1ee5ec03-7e64-6071-8ca3-98dbab0a7719",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3cf9e3818fb8",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}

data/Heat_Capacity/sensor_tempCalorimeter3_1ee5ec04-30cd-678f-a64b-0ce7544ef5e8.json

+{
+	"JSON": {
+		"ID": "1ee5ec04-30cd-678f-a64b-0ce7544ef5e8",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3c01f095b066",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}

data/Heat_Capacity/sensor_tempEnvironment_1ee5ec04-c845-69e2-853a-25c11543466f.json

+{
+	"JSON": {
+		"ID": "1ee5ec04-c845-69e2-853a-25c11543466f",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3c01f095d465",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}

data/Heat_Capacity/setup_constant.json

+{
+	"JSON": {
+		"ID": "1ee5ec1a-e3f7-66be-b5a8-ad82b1e18627",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+    "comment": "this setup is used to measure the calorimeter constant by bringing in a known amount of energy, while measuring the temperature",
+	"setup": {
+		"1ee5ec0a-1830-63f5-ac3e-6f8ce4468546": {
+            "type": "group_info",
+			"name": "group_info",
+            "comment": ""
+        },
+		"1ee5ec0d-e77c-68b7-90f7-2e33485ff91c": {
+            "type": "instrument",
+			"name": "raspberry_pi",
+            "comment": ""
+        },
+        "1ee5ec0c-0b57-68cd-9d39-c9b7e9b18753": {
+            "type": "calorimeter",
+			"name": "calorimeter",
+            "comment": ""
+        },
+		"1ee21744-0355-6023-94b4-d5c041dd32cd": {
+            "type": "actor",
+			"name": "immersion_heater",
+            "comment": "this heater is used to warm up the water in the calorimeter for measuring the calorimeter constant"
+        },
+		"1ee5ec00-4a00-68a1-bb1e-873c2dd4dbde": {
+            "type": "sensor",
+			"name": "temperature_calorimeter_1",
+            "comment": ""
+        },
+		"1ee5ec03-7e64-6071-8ca3-98dbab0a7719": {
+            "type": "sensor",
+			"name": "temperature_calorimeter_2",
+            "comment": ""
+        },
+		"1ee5ec04-30cd-678f-a64b-0ce7544ef5e8": {
+            "type": "sensor",
+			"name": "temperature_calorimeter_3",
+            "comment": ""
+        },
+		"1ee5ec04-c845-69e2-853a-25c11543466f": {
+            "type": "sensor",
+			"name": "temperature_environment",
+            "comment": ""
+        }
+	}
+}
\ No newline at end of file

data/PDC003/actor_sousvide_1ee21750-5282-63bc-86e9-b4de622ee43e.json

+{
+	"JSON": {
+		"ID": "1ee21750-5282-63bc-86e9-b4de622ee43e",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"actor": {
+		"type": "Sous Vide cooker",
+		"model": "DE310B",
+		"manufacturer": "KitchenBoss",
+		"power_supply": {
+			"voltage": "230 V",
+			"type": "AC voltage",
+			"power": "1100 W"
+		},
+		"temperature_range": {
+			"min": 40,
+			"max": 90,
+			"unit": "degree Celsius"
+		},
+		"circulation": "available"
+	}
+}
\ No newline at end of file

data/PDC003/calorimeter_1ee5ec0c-0b57-68cd-9d39-c9b7e9b18753.json

+{
+	"JSON": {
+		"ID": "1ee5ec0c-0b57-68cd-9d39-c9b7e9b18753",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"calorimeter": {
+		"type": "heat flow calorimeter",
+		"manufacturer": "Fluidsystemtechnik",
+		"container": {
+			"type": "beaker",
+			"volume": {
+				"value": 600,
+				"unit": "milliliter"
+			}
+		},
+		"medium": {
+			"type": "water",
+			"mass": {
+				"value": 400,
+				"unit": "gramm",
+				"accuracy": {
+					"value": 0,
+					"type": "absolute",
+					"unit": "gramm"
+				}
+			}
+		}
+	}
+}

data/PDC003/group_1ee5ec0a-1830-63f5-ac3e-6f8ce4468546.json

+{
+	"JSON": {
+		"ID": "1ee5ec0a-1830-63f5-ac3e-6f8ce4468546",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"group": {
+		"number": "Laborversuch_Group37",
+		"author": [
+			"Diogo Fernandes Costa",
+			"Zidane Bürmann",
+			"Santiago Ramirez Saldana"
+		],
+		"experiment": "calorimetry",
+		"testrig_number": "1"
+	}
+}

data/PDC003/instrument_raspPi_1ee5ec0d-e77c-68b7-90f7-2e33485ff91c.json

+{
+	"JSON": {
+		"ID": "1ee5ec0d-e77c-68b7-90f7-2e33485ff91c",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"instrument": {
+		"name": "raspberry_pi",
+		"type": "single_board_computer",
+		"manufacturer": "Raspberry Pi Foundation",
+		"model": "Raspberry Pi 4 Model B Rev. 1.5",
+		"serial": "10000000dbd18662",
+		"operating_system": "Raspberry Pi OS",
+		"comment": "to get model and serial number put this code in the terminal: cat /proc/cpuinfo"
+	}
+}

data/PDC003/sensor_tempCalorimeter1_1ee5ec00-4a00-68a1-bb1e-873c2dd4dbde.json

+{
+	"JSON": {
+		"ID": "1ee5ec00-4a00-68a1-bb1e-873c2dd4dbde",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3c01f0956007",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}

data/PDC003/sensor_tempCalorimeter2_1ee5ec03-7e64-6071-8ca3-98dbab0a7719.json

+{
+	"JSON": {
+		"ID": "1ee5ec03-7e64-6071-8ca3-98dbab0a7719",
+		"label": "",
+		"comment": "UUID6 is used"
+	},
+	"sensor": {
+		"name": "Temperature_Sensor",
+		"type": "DS18B20",
+		"manufacturer": "keyestudio",
+		"serial": "3cf9e3818fb8",
+		"comment": "",
+		"range": {
+			"min": -55,
+			"max": 125,
+			"units": "degree_celsius"
+		},
+		"accuracy": {
+			"value": 0.5,
+			"type": "absolute",
+			"unit": "degree_celsius"
+		}
+	}
+}