Dataset: B-GOOD WP1 Tier 1 Data 2020

1. For some columns it is possible to guess the meaning based on the context (e.g. columns Battery voltage (V) (bv), Weight (kg) (weightkg), T 0 (°C) (t0), T 1 (°C) (t1)). However, for most columns it is unclear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data. Alternatively, all sensor outzputs that are not considered necessary could be removed.
2. It is unclear in which unit the receives signal strength is given: dBm or RSSI.
3. There are weight and temperature measurements that are unrealistically low or high. The data should be checked for outlayers. If the issue can be resolved it should be resolved. If it cannot be resolved it should be documented in the dataset report and mentioned in the description of the table.

1. For many columns it is possible to guess the meaning based on the context. However, for some columns (Data size (timestamps), Data length (days), Data size imported (timestamps), Data length imported (days), LoRa transmission ratio (x interval), Data completeness (%), filter (startyear)). Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.
2. In column ID decimal numbers are used as record identifiers. If there are no well-founded reasons to do so it is recommended to use integers, a common practice in relational databases. Otherwise, there is a risk of an error when the data is reused.
3. In column B-Good mini apiary the attributes "Switserland" and "GB" are used. If there are no well-founded reasons to do so it is recommended to use the English name of these countries (Switzerland, Great Britain), like for the majority of the attributes.
4. In column Hive_id multiple values have been used, separated by a {+} sign. In relational databases this practice is possible but requests additional operations and may lead to errors. If there are no well-founded reasons to do so it is recommended to save multiple versions of such records with the respective identifiers.

1. Although the meaning of many columns can be guessed in context, the meaning of many columns (in particular of the columns Created at, Deleted at) is not entirely clear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.
2. In columns Address, Postal code and City question marks are used. If there are no well-founded reasons to do so it is recommended to either use a more meaningful attribute (e.g. 'unknown') or to declare it as missing value by assigning the value NULL or a blank.

1. Although the meaning of many columns can be guessed in context, the meaning of many columns (in particular of the columns Color (HEX), Queen fertilized, Brood layers, Honey layers, Frames total, Created at, Deleted at) is not entirely clear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.

1. Although the meaning of many columns can be guessed in context, the meaning of many columns (in particular of the columns Test type, Test date, Test result, Test lab name, Created at, Deleted at) is not entirely clear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.

1. Although the meaning of many columns can be guessed in context, the meaning of many columns (in particular of the columns boot_count, measurement_transmission_ratio, ble_pin, next_downlink_message, last_downlink_result, Created at, Deleted at) is not entirely clear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.

1. Although the meaning of many columns can be guessed in context, the meaning of many columns (in particular of the columns offset, multiplier, input_measurement, output_measurement, Created at, Deleted at) is not entirely clear. Since it was decided to include this data in the data set, it should be explained in order to allow reuse of the data.

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