The data was published by Schäfer MO (FLI) on the B-GOOD Bee Health Data Portal as part of the B-GOOD project (grant agreement 817622), funded under the EU Horizon 2020 Research and Innovation Programme. It contains results from the analysis of pathogens (Deformed Wing Virus A, DWV A; Deformed Wing Virus B, DWV B; Acute Bee Paralysis Virus, ABPV; Chronic Bee Paralysis Virus CBPV; Black Queen Cell Virus BQCV; Sackbrood Virus, SBV; Paenibacillus larvae; Melissococcus plutonius; Nosema apis; Nosema ceranae; Malpighamoeba mellificae; Varroa destructor) in bee samples collected in spring, summer and autumn of 2020, 2021 and 2022 in different locations.

The objectives of the B-GOOD project were: (1) Facilitate decision making for beekeepers and other stakeholders by establishing ready-to-use tools for operationalising the HSI; (2) Test, standardise and validate methods for measuring and reporting selected indicators affecting bee health; (3) Explore the various socio-economic and ecological factors beyond bee health; (4) Foster an EU community to collect and share knowledge related to honey bees and their environment; (5) Engender a lasting learning and innovation system (LIS); (6) Minimise the impact of biotic and abiotic stressors.

The datset contains two tables. One contains the results from the pilot studies (1029 records, 333,43 kB), one the results from the field studies (769 records, 233,42 kB).

Currently, the data integrated from the B-GOOD Bee Health Data Portal contains major issues and does not comply with the FAIR Guiding Principles for scientific data management and stewardship applied on the EU Pollinator Hub. More descriptive information about the context, quality and condition, or characteristics of the data (e.g. protocols, measurement devices used, units of the captured data, or any other details about the study) must be provided. More metadata in the form of accurate and relevant attributes (*e.g. *metadata that describes the scope of the data has been described, any particularities or limitations about the data that other users should be aware of, specification of the date of generation/collection of the data, the lab conditions, who prepared the data, the parameter settings, the name and version of the software used, specification of whether it is raw or processed data, explanation of all variable names are explained if they are not self-explanatory) must be provided. It requires major revisions by the data provider.

The data was published by Schäfer MO (FLI) on the B-GOOD Bee Health Data Portal as part of the B-GOOD project (grant agreement 817622), funded under the EU Horizon 2020 Research and Innovation Programme. The dataset contains results from the analysis of pathogens (Deformed Wing Virus A, DWV A; Deformed Wing Virus B, DWV B; Acute Bee Paralysis Virus, ABPV; Chronic Bee Paralysis Virus CBPV; Black Queen Cell Virus BQCV; Sackbrood Virus, SBV; Paenibacillus larvae; Melissococcus plutonius; Nosema apis; Nosema ceranae; Malpighamoeba mellificae; Varroa destructor) in bee samples collected in spring, summer and autumn of 2020, 2021 and 2022 in different locations.

The objectives of the B-GOOD project were: (1) Facilitate decision making for beekeepers and other stakeholders by establishing ready-to-use tools for operationalising the HSI; (2) Test, standardise and validate methods for measuring and reporting selected indicators affecting bee health; (3) Explore the various socio-economic and ecological factors beyond bee health; (4) Foster an EU community to collect and share knowledge related to honey bees and their environment; (5) Engender a lasting learning and innovation system (LIS); (6) Minimise the impact of biotic and abiotic stressors.

All raw data files were downloaded from the B-GOOD Bee Health Data Portal on 2024-07-04.

List of raw data and metadata files obtained from the data provider.

1. File b-good-pilot-a-results-2020-for-beep-v2.xlsx accesed on 2024-10-01 14:19:29, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
2. File b-good-pilot-a-results-2020-for-inrae-v2.xlsx accessed on 2024-10-01 14:21:11, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
3. File b-good-pilot-a-results-2020-for-mlu-v2.xlsx accessed on 2024-10-01 14:21:31, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
4. File b-good-pilot-a-results-2020-for-tntu-v2.xlsx accessed on 2024-10-01 14:22:01, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
5. File b-good-pilot-a-results-2020-for-ubern-v2.xlsx accessed on 2024-10-01 14:26:57, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
6. File b-good-pilot-a-results-2020-for-ucluj-v2.xlsx accessed on 2024-10-01 14:27:11, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
7. File b-good-pilot-a-results-2020-for-ucoi-v2.xlsx accessed on 2024-10-01 14:27:55, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
8. File b-good-pilot-a-results-2020-for-ugent-v2.xlsx accessed on 2024-10-01 14:28:07, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
9. File b-good-pilot-a-results-2020-for-wr-v2.xlsx accessed on 2024-10-01 14:28:19, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
10. File b-good-pilot-b-results-2020-for-wr-v3.xlsx accessed on 2024-10-01 14:28:33, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
11. File b-good-tier-1-results-2021-for-beep-v3.xlsx accessed on 2024-10-01 17:47:21, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
12. File b-good-tier-1-results-2021-for-inrae-v2.xlsx accessed on 2024-10-01 17:47:36, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
13. File b-good-tier-1-results-2021-for-mlu-v2.xlsx accessed on 2024-10-01 17:47:50, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
14. File b-good-tier-1-results-2021-for-tntu-v2.xlsx accessed on 2024-10-01 17:48:04, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
15. File b-good-tier-1-results-2021-for-ubern-v2.xlsx accessed on 2024-10-01 17:48:22, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
16. File b-good-tier-1-results-2021-for-ucluj-v2.xlsx accessed on 2024-10-01 17:48:34, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
17. File b-good-tier-1-results-2021-for-ucoi-v3.xlsx accessed on 2024-10-01 17:48:51, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
18. File b-good-tier-1-results-2021-for-ugent-v2.xlsx accessed on 2024-10-01 17:49:05, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
19. File b-good-tier1-results-2021-for-wr-v2.xlsx accessed on 2024-10-01 17:49:18, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
20. File b-good-pilot-b-results-2021-for-wr-v2.xlsx accessed on 2024-10-01 17:49:36, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
21. File b-good-tier-1-results-2022-for-beep.xlsx accessed on 2024-10-01 18:16:24, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
22. File b-good-tier-1-results-2022-for-inrae.xlsx accessed on 2024-10-01 18:16:44, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
23. File b-good-tier-1-results-2022-for-mlu.xlsx accessed on 2024-10-01 18:16:57, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
24. File b-good-tier-1-results-2022-for-tntu.xlsx accessed on 2024-10-01 18:17:10, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
25. File b-good-tier-1-results-2022-for-ubern.xlsx accessed on 2024-10-01 18:17:22, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
26. File b-good-tier-1-results-2022-for-ucluj.xlsx accessed on 2024-10-01 18:17:34, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
27. File b-good-tier-1-results-2022-for-ucoi.xlsx accessed on 2024-10-01 18:17:46, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
28. File b-good-tier-1-results-2022-for-ugent.xlsx accessed on 2024-10-01 18:18:09, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
29. File b-good-pilot-a-results-2022-for-wr.xlsx accessed on 2024-10-01 18:18:24, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
30. File b-good-pilot-b-results-2022-for-wr.xlsx accessed on 2024-10-01 18:18:41, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
31. File b-good-tier-2-results-2021-for-beep-v3.xlsx accessed on 2024-10-01 18:27:41, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
32. File b-good-tier-2-results-2021-for-bsour-v2.xlsx accessed on 2024-10-01 18:27:55, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
33. File b-good-tier-2-results-2021-for-mlu-v2.xlsx accessed on 2024-10-01 18:28:08, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
34. File b-good-tier-2-results-2021-for-sml-v2.xlsx accessed on 2024-10-01 18:28:22, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
35. File b-good-tier-2-results-2021-for-ubern-v3.xlsx accessed on 2024-10-01 18:28:34, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
36. File b-good-tier-2-results-2021-for-wr-v2.xlsx accessed on 2024-10-01 18:28:47, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
37. File b-good-tier-2-results-2022-for-beep-v2.xlsx accessed on 2024-10-01 18:22:14, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
38. File b-good-tier-2-results-2022-for-bsour.xlsx accessed on 2024-10-01 18:22:35, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
39. File b-good-tier-2-results-2022-for-mlu.xlsx accessed on 2024-10-01 18:22:47, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
40. File b-good-tier-2-results-2022-for-sml-v2.xlsx accessed on 2024-10-01 18:23:00, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
41. File b-good-tier-2-results-2022-for-ubern.xlsx accessed on 2024-10-01 18:23:15, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
42. File b-good-tier-2-results-2022-for-wr.xlsx accessed on 2024-10-01 18:23:29, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal
43. File b-good-tier-3-results-2022-for-beep.xlsx accessed on 2024-10-01 18:24:20, provided by Schäfer, MO (FLI) at B-GOOD Bee Health Data Portal

Metadata was obtained from the web pages of the single datasets (see above).

All files in the zip-archives were extracted using File Explorer (Microsoft Corporation, version 22H2). The data files were processed using MS Excel (Microsoft Corporation, version 2409).

For datasets B-GOOD Pilot A results 2020 for MLU V2, B-GOOD Pilot A results 2020 for TNTU V2, B-GOOD Pilot A results 2020 for UBERN V2, B-GOOD Pilot A results 2020 for UCLUJ V2, and B-GOOD Pilot B results 2020 for WR V3, two apparently identical raw data files (same name, size) were provided on the B-GOOD Bee Health Data Portal. These files were compared using the Get-FileHash command of the Microsoft.PowerShell.Utility module, which computes the hash value for each raw data file by using the SHA256 hash algorithm. Hash values were then compared with MS Excel using the EXACT function. All hash values were the same for each of the duplicate raw data files, therefore, one duplicate file per dataset was deleted.

Tier 1 Pilot A and B 2020. Even though this is not explicitly stated in the data description, the file of dataset B-GOOD Pilot A results 2020 for BEEP V2 (b-good-pilot-a-results-2020-for-beep-v2.xlsx) contains the data (180 records) form the following datasets, which were therefore not integrated in order to avoid duplicate records: B-GOOD Pilot A results 2020 for INRAe V2; B-GOOD Pilot A results 2020 for MLU V2; B-GOOD Pilot A results 2020 for TNTU V2; B-GOOD Pilot A results 2020 for UBERN V2; B-GOOD Pilot A results 2020 for UCLUJ V2; B-GOOD Pilot A results 2020 for UCOI V2; B-GOOD Pilot A results 2020 for UGENT V2; B-GOOD Pilot A results 2020 for WR V2.

The following issues were found and resolved:

• In column N. spores
  • file b-good-pilot-a-results-2020-for-beep-v2.xlsx contains {<25000} while file b-good-pilot-a-results-2020-for-ucluj-v2.xlsx contains {0} for Sample ID {AHJTRZLZ}. {< 25000} has been used, as b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.
  • file b-good-pilot-a-results-2020-for-beep-v2.xlsx contains {<25000} while file b-good-pilot-a-results-2020-for-inrae-v2.xlsx contains {0} for Sample ID {MUDAXHCG}. {< 25000} has been used, as b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.
  • file b-good-pilot-a-results-2020-for-beep-v2.xlsx contains {<25000} while file b-good-pilot-a-results-2020-for-inrae-v2.xlsx contains {0} for Sample ID {RRMUZUBR}. {< 25000} has been used, as b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.
  • file b-good-pilot-a-results-2020-for-beep-v2.xlsx contains {<25000} while file b-good-pilot-a-results-2020-for-inrae-v2.xlsx contains {0} for Sample ID {SKLRARCR}. {< 25000} has been used, as b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.
  • file b-good-pilot-a-results-2020-for-beep-v2.xlsx contains {<25000} while file b-good-pilot-a-results-2020-for-inrae-v2.xlsx contains {0} for Sample ID {XLFGKPJZ}. {< 25000} has been used, as b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.

Tier 1 Pilot A and B 2021. Even though this is not explicitly stated in the data description, the file of dataset Tier1 Pilot A results 2021 for BEEP (b-good-tier-1-results-2021-for-beep-v3.xlsx) contains the data (186 records) form the following datasets, which were therefore not integrated in order to avoid duplicate records: Tier1 Pilot A results 2021 for INRAe; Tier1 Pilot A results 2021 for MLU; Tier1 Pilot A results 2021 for TNTU; Tier1 Pilot A results 2021 for UBERN; Tier1 Pilot A results 2021 for UCLUJ; Tier1 Pilot A results 2021 for UCOI; Tier1 Pilot A results 2021 for UGENT; Tier1 Pilot A results 2021 for WR.

Tier 1 Pilot A and B 2022. Even though this is not explicitly stated in the data description, the file of dataset Tier1 Pilot A results 2022 for BEEP (b-good-tier-1-results-2022-for-beep.xlsx) contains the data 186 records) form the following datasets, which were therefore not integrated in order to avoid duplicate records: Tier1 Pilot A results 2022 for INRAe; Tier1 Pilot A results 2022 for MLU; Tier1 Pilot A results 2022 for TNTU; Tier1 Pilot A results 2022 for UBERN; Tier1 Pilot A results 2022 for UCLUJ; Tier1 Pilot A results 2022 for UCOI; Tier 1 Pilot A results 2022 for UGENT; Tier1 Pilot A results 2022 for WR.

The following issues were found and resolved:

• Records with sample ID {XMMDKSCT; RGYMGYTM; GFGTGBKY} contained in file b-good-tier-1-results-2022-for-ucluj.xlsx (3 records), but not in file b-good-tier-1-results-2022-for-beep.xlsx were not integrated into the dataset, as file b-good-pilot-a-results-2020-for-beep-v2.xlsx is assumed to be the single source of truth.

Tier 2 Field study 2021. Even though this is not explicitly stated in the data description, the file of dataset Tier2 Field study results 2021 for BEEP (b-good-tier-2-results-2021-for-beep-v3.xlsx) contains the data (311 records) form the following datasets, which were therefore not integrated in order to avoid duplicate records: Tier2 Field study results 2021 for BSOUR; Tier2 Field study results 2021 for MLU; Tier2 Field study results 2021 for SML; Tier2 Field study results 2021 for UBERN; Tier2 Field study results 2021 for WR.

Tier 2 Field study A 2022. Even though this is not explicitly stated in the data description, the file of dataset Tier2 Field study A results 2022 for BEEP (b-good-tier-2-results-2022-for-beep-v2.xlsx) contains the data (300 records) form the following datasets, which were therefore not integrated in order to avoid duplicate records: Tier2 Field study A results 2022 for BSOUR; Tier2 Field study A results 2022 for MLU; Tier 2 Field study A results 2022 for SML; Tier 2 Field study A results 2022 for UBERN; Tier 2 Field study A results 2022 for WR.

Data from all pilot studies and data from all field studies was transferred into one single table (pilot studies, field studies) in order to facilitate automated evaluation and visualisation of the data. Six columns were added to the beginning and one column to the end (RecordNotes) of each table, which contained the following metadata, as provided in the metadata section of each dataset on the B-GOOD Bee Health Data Portal:

• name of the dataset (column dataset)
• tier level of the study (column StudyTierLevel)
• name of the study (column StudyName)
• year of the study (column year)
• name of the organisation that provided that data file (column organisation)
• attribute contained in some data files, starting with the letter V followed by a number (either 2 or 3) presumably indicating the version number (column V)
• pool of comments added to fields in individual records (RecordNotes)

Data was then exported to the respective preparatory files and uploaded to the EU Pollinator Hub according to SOP-017 (Dataset integration.

No data validation was performed.

No data analysis was performed.

Data from the tier 1 pilot A and B studies performed in 2020, 2021 and 2022.

1. In column partner {UGent} was changed to the more commonly used acronym {UGENT} in 22 records in order to avoid potential problems with automated data analysis.
2. Column sample ID was renamed SampleID to avoid blank spaces in table headers, which might cause problems in some database systems.
3. Column DWV A was renamed DWVA to avoid blank spaces in table headers, which might cause problems in some database systems.
4. Column Cat. relating to column DWVA was renamed DWVA_Cat to assure an assignment of unique names to column headers.
5. Column DWVA_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
6. Column DWV B was renamed DWVB to avoid blank spaces in table headers, which might cause problems in some database systems.
7. Column Cat. relating to column DWVB was renamed DWVB_Cat to assure an assignment of unique names to column headers.
8. Column DWVB_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
9. Column Cat. relating to column ABPV was renamed ABPV_Cat to assure an assignment of unique names to column headers.
10. Column ABPV_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
11. Column Cat. relating to column CBPV was renamed CBPV_Cat to assure an assignment of unique names to column headers.
12. Column CBPV_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
13. Column Cat. relating to column BQCV was renamed BQCV_Cat to assure an assignment of unique names to column headers.
14. Column BQCV_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
15. Column Cat. relating to column SBV was renamed SBV_Cat to assure an assignment of unique names to column headers.
16. Column SBV_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
17. Column Cat. relating to column EFB was renamed EFB_Cat to assure an assignment of unique names to column headers.
18. Column EFB_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
19. Column Cat. relating to column AFB was renamed AFB_Cat to assure an assignment of unique names to column headers.
20. Column AFB_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
21. Column N. apis was renamed NosemaApis to avoid blank spaces in table headers, which might cause problems in some database systems.
22. Column NosemaApis_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
23. Column N. ceranae was renamed NosemaCeranae to avoid blank spaces in table headers, which might cause problems in some database systems.
24. Column NosemaCeranae_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
25. Column > 100 bees was renamed VarroaBees to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
26. Column Varroa/100 bees was renamed VarroaInfestation to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
27. Column Varroa_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
28. Column *AFB (cfu)*was renamed AFBcfu to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
29. Column AFBcfu_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
30. Column N. spores was renamed NosemaSpores to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
31. Column NosemaSpores_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
32. Column CT < 36,00 was renamed Malpighamoeba_CT to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
33. Column Malpighamoeba_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in therelated column can be added.

1. All occurrences of the character {-} in column DWVA_Cat were replaced by {N} (612 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
2. In records, which contained the string {negative} in column DWVA, column DWVA_Notes was replaced by {negative} (634 records) and {negative} in column DWVA was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
3. All occurrences of the character {-} in column DWVB_Cat were replaced by {N} (21 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
4. In records, which contained the string {negative} in column DWVB, column DWVB_Notes was replaced by {negative} (21 records) and the {negative} in column DWVB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
5. All occurrences of the character {-} in column ABPV_Cat were replaced by {N} (169 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
6. In records, which contained the string {negative} in column ABPV, column ABPV_Notes was replaced by {negative} (168 records) and the {negative} in column ABPV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
7. In records, which contain blank values in column ABPV, column ABPV_Notes was replaced by {not available} (265 records) and the blanks in column ABPV and column ABPV_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
8. All occurrences of the character {-} and one occurrence of a blank value in column CBPV_Cat were replaced by {N} (227 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
9. In records, which contain blank values in column CBPV, column CBPV_Notes was replaced by {not available} (265 records) and the blanks in column CBPV and column CBPV_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers or categories.
10. In records, which contained the string {negative} in column CBPV, column CBPV_Notes was replaced by {negative} (227 records) and the {negative} in column CBPV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
11. In records, which contain the value {>40} in column CBPV (1 record), column CBPV_Notes was replaced by {>40} and the {>40} in column CBPV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
12. All occurrences of the character {-} in column SBV_Cat were replaced by {N} (2 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
13. In records, which contained the string {negative} in column SBV, column SBV_Notes was replaced by {negative} (2 records) and the {negative} in column SBV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
14. All occurrences of the character {-} in column EFB_Cat were replaced by {N} (239 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
15. In records, which contain blank values in column EFB, column EFB_Notes was replaced by {not available} (485 records) and the blanks in column EFB and column EFB_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
16. In records, which contained the string {negative} in column EFB, column EFB_Notes was replaced by {negative} (261 records) and the {negative} in column EFB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
17. In records, which contained the string {negative} in column AFB, column AFB_Notes was replaced by {negative} (253 records) and the {negative} in column AFB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
18. All occurrences of the character {-} in column AFB_Cat were replaced by {N} (232 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
19. In records, which contain blank values in column AFB, column AFB_Notes was replaced by {not available} (485 records) and the blanks in column AFB and column EFB_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
20. In records, which contain blank values in column NosemaApis, column NosemaApis_Notes was replaced by {not available} (262 records) and the blanks in column NosemaApis were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
21. In records, which contained the string {negative} in column NosemaApis, column NosemaApis_Notes was replaced by {negative} (506 records) and the {negative} in column NosemaApis was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
22. In records, which contain blank values in column NosemaCeranae, column NosemaCeranae_Notes was replaced by {not available} (262 records) and the blanks in column NosemaCeranaewere replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
23. In records, which contained the string {negative} in column NosemaCeranae, column NosemaCeranae_Notes was replaced by {negative} (253 records) and the {negative} in column NosemaCeranae was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
24. In records, which contain {ND} in column VarroaInfestation, column Varroa_Notes was replaced by {ND} (7 records) and {ND} in column VarroaInfestation was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
25. In records, which contain {ND} in column AFBcfu, column AFBcfu_Notes was replaced by {ND} (270 records) and {ND} in column AFBcfu was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
26. In records, which contain blank values in column AFBcfu, column AFBcfu_Notes was replaced by {not available} (485 records) and the blanks in column AFBcfu were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
27. In 1 record, in which column AFBcfu contained the special character {-}, where dataset = {B-GOOD Pilot A results 2020 for BEEP V2 } and SampleID = {UTYBTKUM}, column AFBcfu was replaced by {NULL} and column AFBcfu_Notes was replaced by {unknown} to avoid having special characters in a data column that is supposed to contain real numbers.
28. In records, which contain {ND} in column NosemaSpores, column NosemaSpores_Notes was replaced by {ND} (252 records) and {ND} in column NosemaSpores was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
29. In records, which contain blank values in column NosemaSpores, column NosemaSpores_Notes was replaced by {not available} (262 records) and the blanks in column NosemaSporeswere replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
30. In records, which contain {< 25000; <25000} in column NosemaSpores, column NosemaSpores_Notes was replaced by {<25000} (26 records) and {< 25000; <25000} in column NosemaSpores was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
31. In records, which contained the string {negative} in column Malpighamoeba, column Malpighamoeba_Notes was replaced by {negative} (225 records) and the {negative} in column Malpighamoeba was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
32. In records, which contained no values in column Malpighamoeba, column Malpighamoeba_Notes was replaced by {not available} (513 records) and the blanks in column Malpighamoeba were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.

1. Overall, the B-GOOD datasets ingested into this EUPH dataset lack sufficient metadata and there are a range of other issues that limit compliance with the FAIR principles.
2. In general, columns are not sufficiently well described (e.g. it is unclear, which information is contained in columns MalpighamoebaCT and Malpighamoeba_Notes related to column Malpighamoeba; it is unclear, if the definitions provided for the attributes L, M, H - number of genome copies per bee -, which are used to define the dilution of DNA plasmids, only refer to Viral pathogens or to all pathogens). The provider should provide all information necessary to allow reuse of the data within the dataset.
3. For some columns no units are provided (e.g. AFB cfu), for other columns, the unit in which data is expressed is not explicitly stated and can only be assumed based on exclusion. The provider should explicitly state the units in columns containing data in order to avoid misunderstandings.
4. Some of the attributes used in the dataset are not explained (e.g. ND). The provider should define the meaning of all attributes used in the dataset.
5. Data comes in Microsoft Excel files, which occasionally contain nested comments or uncommented annotations (e.g. different background colour of cells) in single cells, which makes storage in relational databases difficult and automated processing and analysis impossible.
6. The table structure does not facilitate data standardisation, as standardisation would require all values measured with the same method to be stored int one single column and transformed to the same unit.
7. The significance of the string {ND} is unclear:

• In columns DWV_Cat, EFB_Cat, AFB_Cat (22 records), where column dataset = {B-GOOD Pilot B results 2020 for WR V3} and SampleID = {BKCSYJMR; JKSXXKSC; LSPSHGZL; MDHLMFYT; NMYRPHNJ; YUXRGDZR; ANYXAYUZ; GNBMNLPM; HFXGDUAU; YPCTFUUU; LJSUAPFC; ZCUPCPFF; KNBULSMH; DUSFMRXB; JTYTGYDP; HXNGCDSH; KSNLKPRT; DRAZTCGC; LYZHDDGB; DXSPRLUC; CYPCTUGX; MJUYMLSH};
• In column VarroaBees and Varroa_Notes (7 records), where column dataset = {B-GOOD Pilot A results 2020 for BEEP V2} and SampleID = {CKTSXSMR; CYXUCRUN; FBYMAGCT; HCHPHKFL; RRBYHJBU; STZPSJHR; UAKMCLMN};
• In column VarroaBees and Varroa_Notes (7 records), where column dataset = {B-GOOD Pilot A results 2020 for BEEP V2} and SampleID = {CKTSXSMR; CYXUCRUN; FBYMAGCT; HCHPHKFL; RRBYHJBU; STZPSJHR; UAKMCLMN};
• In column NosemaSpores_Notes (252 records);

8. The significance of the special character {-} in column AFBcfu, where dataset = {B-GOOD Pilot A results 2020 for BEEP V2 } and SampleID = {UTYBTKUM}, is unclear. Column AFBcfu_Notes was replaced by {unknown} until the issue will be resolved.

Data from the tier 2 and tier 3 field studies A and B performed in 2021 and 2022.

1. Column sample ID was renamed SampleID to avoid blank spaces in table headers, which might cause problems in some database systems.
2. Column DWV A was renamed DWVA to avoid blank spaces in table headers, which might cause problems in some database systems.
3. Column Cat. relating to column DWVA was renamed DWVA_Cat to assure an assignment of unique names to column headers.
4. Column DWVA_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
5. Column DWV B was renamed DWVB to avoid blank spaces in table headers, which might cause problems in some database systems.
6. Column Cat. relating to column DWVB was renamed DWVB_Cat to assure an assignment of unique names to column headers.
7. Column DWVB_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
8. Column Cat. relating to column ABPV was renamed ABPV_Cat to assure an assignment of unique names to column headers.
9. Column ABPV_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
10. Column Cat. relating to column CBPV was renamed CBPV_Cat to assure an assignment of unique names to column headers.
11. Column CBPV_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
12. Column Cat. relating to column BQCV was renamed BQCV_Cat to assure an assignment of unique names to column headers.
13. Column BQCV_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
14. Column Cat. relating to column SBV was renamed SBV_Cat to assure an assignment of unique names to column headers.
15. Column SBV_Notes was created and replaced with {NULL} (769 records) to add a column in which notes on the data in the related column can be added.
16. Column Cat. relating to column EFB was renamed EFB_Cat to assure an assignment of unique names to column headers.
17. Column EFB_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
18. Column Cat. relating to column AFB was renamed AFB_Cat to assure an assignment of unique names to column headers.
19. Column AFB_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
20. Column N. apis was renamed NosemaApis to avoid blank spaces in table headers, which might cause problems in some database systems.
21. Column NosemaApis_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
22. Column N. ceranae was renamed NosemaCeranae to avoid blank spaces in table headers, which might cause problems in some database systems.
23. Column NosemaCeranae_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
24. Column > 100 bees was renamed VarroaBees to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
25. Column Varroa/100 bees was renamed VarroaInfestation to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
26. Column Varroa_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
27. Column *AFB (cfu)*was renamed AFBcfu to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
28. Column AFBcfu_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
29. Column N. spores was renamed NosemaSpores to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
30. Column NosemaSpores_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.
31. Column CT < 36,00 was renamed Malpighamoeba_CT to avoid blank spaces and special characters in table headers, which might cause problems in some database systems.
32. Column Malpighamoeba_Notes was created and replaced with {NULL} (1029 records) to add a column in which notes on the data in the related column can be added.

1. In 27 records obtained from the file of dataset Tier2 Field study A results 2022 for BEEP (b-good-tier-2-results-2022-for-beep-v2.xlsx) and 36 records obtained from the file of dataset Tier3 Field study B results 2022 for BEEP (b-good-tier-3-results-2022-for-beep.xlsx) the leading asterisk {*} was removed from the data in column SampleID and the comment referring to those SampleID ("these codes might be wrong, as they could not be uploaded onto the BEEP app, or there was no code at all"), supplemented by the explanatory text in square brackets ("[column SampleID]" ) was added to column RecordNotes of the same record. Removal of annotations to a datum is necessary to enable the records to be linked with records in other tables in relational databases.
2. In records, which contained the string {negative} in column DWVA, column DWVA_Notes was replaced by {negative} (728 records) and {negative} in column DWVA was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
3. All occurrences of the character {-} in column DWVA_Cat were replaced by {N} (727 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
4. In records, which contained the string {negative} in column DWVB, column DWVB_Notes was replaced by {negative} (26 records) and the {negative} in column DWVB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
5. All occurrences of the character {-} in column DWVB_Cat were replaced by {N} (26 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
6. All occurrences of the character {-} in column ABPV_Cat were replaced by {NULL} (409 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
7. In records, which contained the string {negative} in column ABPV, column ABPV_Notes was replaced by {negative} (410 records) and the {negative} in column ABPV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
8. In records, which contain blank values in column ABPV, column ABPV_Notes was replaced by {not available} (335 records) and the blanks in column ABPV and column ABPV_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers or categories.
9. All occurrences of the character {-} and one occurrence of a blank value in column CBPV_Cat were replaced by {N} (400 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
10. In records, which contained the string {negative} in column CBPV, column CBPV_Notes was replaced by {negative} (402 records) and the {negative} in column CBPV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
11. In records, which contain blank values in column CBPV, column CBPV_Notes was replaced by {not available} (335 records) and the blanks in column CBPV and column CBPV_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers or categories.
12. All occurrences of the character {-} and one occurrence of a blank value in column BQCV_Cat were replaced by {N} (2 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
13. In records, which contained the string {negative} in column BQCV, column BQCV_Notes was replaced by {negative} (2records) and the {negative} in column BQCV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
14. In records, which contained the string {negative} in column SBV, column SBV_Notes was replaced by {negative} (77 records) and the {negative} in column SBV was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
15. All occurrences of the character {-} in column SBV_Cat were replaced by {N} (77 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
16. All occurrences of the character {-} in column EFB_Cat were replaced by {N} (357 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
17. In records, which contained the string {negative} in column EFB, column EFB_Notes was replaced by {negative} (357 records) and the {negative} in column EFB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
18. In records, which contain blank values in column EFB, column EFB_Notes was replaced by {not available} (651 records) and the blanks in column EFB and column EFB_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
19. In records, which contain {ND} in column EFB, column EFB_Notes was replaced by {ND} (3 records) and {ND} blanks in column EFB as well as blank values in column EFB_Cat were replaced by {NULL} to avoid having string or blank values in a data column that is supposed to contain real numbers or categories.
20. All occurrences of the character {-} in column AFB_Cat were replaced by {NULL} (300 records), as the use of a mathematical operator as a datum could potentially cause problems with database queries under particular circumstances.
21. In records, which contained the string {negative} in column AFB, column AFB_Notes was replaced by {negative} (300 records) and the {negative} in column AFB was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
22. In records, which contain blank values in column AFB, column AFB_Notes was replaced by {not available} (696 records) and the blanks in column AFB and column EFB_Cat were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
23. In records, which contained the string {negative} in column NosemaApis, column NosemaApis_Notes was replaced by {negative} (687 records) and the {negative} in column NosemaApis was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
24. In records, which contain blank values in column NosemaApis, column NosemaApis_Notes was replaced by {not available} (333 records) and the blanks in column NosemaApis were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
25. In records, which contained the string {negative} in column NosemaCeranae, column NosemaCeranae_Notes was replaced by {negative} (435 records) and the {negative} in column NosemaCeranae was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.
26. In records, which contain blank values in column NosemaCeranae, column NosemaCeranae_Notes was replaced by {not available} (333 records) and the blanks in column NosemaCeranaewere replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
27. In records, which contain {ND} in columns VarroaBees and VarroaInfestation, column Varroa_Notes was replaced by {ND} (2 records) and {ND} in columns VarroaBees and VarroaInfestation was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers or categories.
28. In records, which contain {ND} in column AFBcfu (312 records), column AFBcfu_Notes was replaced by {ND} and {ND} in column AFBcfu was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
29. In records, which contain blank values in column AFBcfu, column AFBcfu_Notes was replaced by {not available} (696 records) and the blanks in column AFBcfu were replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
30. In records, which contain {ND} in column NosemaSpores, column NosemaSpores_Notes was replaced by {ND} (426 records) and {ND} in column NosemaSpores was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
31. In records, which contain blank values in column NosemaSpores, column NosemaSpores_Notes was replaced by {not available} (333 records) and the blanks in column NosemaSporeswere replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
32. In records, which contain {< 25000; <25000} in column NosemaSpores, column NosemaSpores_Notes was replaced by {<25000} (44 records) and {< 25000; <25000} in column NosemaSpores was replaced by {NULL} to avoid having blank values in a data column that is supposed to contain real numbers.
33. In records, which contained the string {negative} in column Malpighamoeba, column Malpighamoeba_Notes was replaced by {negative} (636 records) and the {negative} in column Malpighamoeba was replaced by {NULL} to avoid having text in a data column that is supposed to contain real numbers.

1. Overall, the B-GOOD datasets ingested into this EUPH dataset lack sufficient metadata and there are a range of other issues that limit compliance with the FAIR principles.
2. In general, columns are not sufficiently well described (e.g. it is unclear, which information is contained in columns MalpighamoebaCT and Malpighamoeba_Notes related to column Malpighamoeba; it is unclear, if the definitions provided for the attributes L, M, H - number of genome copies per bee -, which are used to define the dilution of DNA plasmids, only refer to Viral pathogens or to all pathogens). The provider should provide all information necessary to allow reuse of the data within the dataset.
3. For some columns no units are provided (e.g. AFB cfu), for other columns, the unit in which data is expressed is not explicitly stated and can only be assumed based on exclusion. The provider should explicitly state the units in columns containing data in order to avoid misunderstandings.
4. Some of the attributes used in the dataset are not explained (e.g. ND). The provider should define the meaning of all attributes used in the dataset.
5. Data comes in Microsoft Excel files, which occasionally contain nested comments or uncommented annotations (e.g. different background colour of cells) in single cells, which makes storage in relational databases difficult and automated processing and analysis impossible.
6. The table structure does not facilitate data standardisation, as standardisation would require all values measured with the same method to be stored int one single column and transformed to the same unit.
7. In column SampleID the values {GB_1; GB2; GB_3} are not unique. Each of them exists twice.
8. The significance of the string {ND} is unclear:

• In column EFB_Cat (3 records), where column dataset = {Tier2 Field study A results 2022 for BEEP} and SampleID = {CDYTBDHK; DTUDJNAG; RYAYUTUG};
• In column Varroa_Notes, where column dataset = {Varroa_Tier2 Field study results 2021 for WR} and SampleID = {ZUXHUFZP, BXCTGZBN CFO};
• In columns AFBcfu_Notes and NosemaSpores_Notes;