The following list contains all possible error types detected and reported by the STRUVAL service.
Error Code |
Message ID |
Description of Error |
Details of Error |
500 |
|
Internal server error. Validation service not available. |
The STRUVAL service is not able to process the inputs due to an internal server error. |
140 |
|
<Message from XML Parser> |
The SDMX-ML file is not a well-formed XML file. It may contain invalid characters, tags that are not closed or are closed out of order. Well formedness of an XML file can be checked using different tools, such as the advanced text editors or online. |
150 |
003 |
The dataset contains a series with a missing concept 0 |
The data file contains series with dimensions or attributes which are not defined in DSD. |
150 |
004 |
The DSD 0 used does not define a time dimension, required for the time series data. |
When building a time-series dataset, one must use a DSD that includes a time dimension. |
150 |
005 |
The dataset includes primary measure 0, not expected by the DSD. |
When building a time-series dataset, one must use a DSD that has a primary measure. |
150 |
904-1 |
Series key 0 is not defined in DSD (unexpected size). |
Dataset contains series keys with unexpected size. |
150 |
904-2 |
Series key 0 is not defined in DSD (incorrect codes). |
Dataset contains series keys which unexpected size. |
150 |
007 |
The dataset contains a concept 0 that is not defined in DSD. |
All concepts used in a dataset must be defined in a DSD. |
150 |
008 |
Attribute 0 defined as mandatory in DSD is missing from the dataset. |
The dataset contains a mandatory series level attribute which is not present in the data file. |
150 |
009 |
Series attribute 0 is not defined in DSD. |
The encountered attribute at the series level in data file does not exist in the DSD. |
150 |
010 |
Attribute 0 defined as mandatory in DSD is missing from the group. |
The dataset contains a mandatory group level attribute which is not present in the data file. |
150 |
011 |
Attribute 0 is assigned to the incorrect group. |
The encountered attribute at the dataset level in data file does not exist in DSD. |
150 |
012 |
Attribute 0 defined as mandatory in DSD is missing from the observation. |
The dataset contains a mandatory observation level attribute which is not present in the data file. |
150 |
013 |
Attribute 0 is not defined in DSD for observation. |
The encountered observation attribute is not defined in the DSD. |
150 |
014 |
Dataset group 0 is not defined in the DSD. |
Dataset contains group keys with unexpected size. |
150 |
015 |
Dataset group 0 is not defined in the DSD. |
Data Structure Definition does not define a Group. |
150 |
016 |
The mandatory concept 0 in DSD is currently missing from the group. |
The dataset contains a group missing mandatory concept(s) as defined in the DSD. |
150 |
017 |
Concept 0 is assigned to the incorrect group. |
The encountered group in the dataset contains a concept which is not defined in the DSD. |
150 |
018 |
XML error - The dataset contains an invalid node. |
Appears when an unexpected node exists in the dataset file. |
150 |
021 |
XML error - Unexpected text ''0'' found at node ''1'' |
Unexpected text is found as children of one SDMX node which does not contain text. SDMX node names are kept in an internal structure and has the names such as Header, Series, OBS or Group. This error message appears when the dataset contains children of these elements. |
150 |
022 |
XML error - Dataset header fails to reference a provision agreement, dataflow, or DSD. |
Dataset header fails to reference a provision agreement, a dataflow, or a DSD. |
150 |
023 |
XML error - Dataset does not contain a header. |
Dataset does not contain a header. |
150 |
024 |
XML error - Dataset structure reference incomplete. |
The message appears if the referenced structure is incomplete, i.e. the agencyId, ID or maintainable ParentId are missing or empty. |
150 |
025 |
XML error - Invalid DSD reference. |
Dataset structure reference invalid, could not process reference, no RefNode or URN node found. |
150 |
026 |
Attribute 0 is not defined in DSD. |
An attribute at dataset level is present in data file but it is not defined in the DSD. |
150 |
027 |
Expected component 0 must be an attribute but is 1. |
Another component appears as a dataset attribute in data file. |
150 |
028 |
Attribute 0 incorrectly attached to 2 instead of to 1. |
The dataset has an attribute with different attachment level. |
150 |
029 |
0 ''1'' is reporting value ''2'' which is not a valid representation in referenced code list ''3''. |
An attribute at dataset, series or observation level has a value which is not valid in the referenced code list. |
150 |
030 |
0 1 is reporting invalid value 3 which is not of expected type 2. |
Appears when reported value of a concept is unexpected. |
150 |
031 |
Component 0 in group 1 not defined in DSD 2. |
The dataset contains groups which contains components that are not defined as group components in the DSD. |
150 |
032 |
Observation missing time dimension for time series data. |
Observation missing the time dimension for time series data. |
150 |
033 |
Observations not allowed for this dataset. |
Appears if there is a constraint on the dataset which does not allow observations. |
150 |
034 |
Observation time ''0'' is before the expected reporting period start date "1". |
Appears if there is a constraint which specify report start date and the observation time is before this date. |
150 |
035 |
Observation Time ''0'' is after the expected reporting period end date "1". |
Appears if there is a constraint which specify report end date and the observation time is after this date. |
150 |
036 |
Series not allowed in this dataset. |
Appears if there is a constraint on the dataset which does not allow series. |
150 |
037 |
Series key 0 not allowed. |
Appears if the dimension is not allowed in the key due to an existing constraint. |
150 |
038 |
Illegal Series key 0 contains invalid value "1" not defined in DSD for 2 3. |
Appears when the series key contains some value which is disallowed by constraints in DSD. |
150 |
039 |
Duplicate observation found: 0 |
Appears when more than one observation is found in one series. |
150 |
040 |
Data validation failed: 0 |
It appears when a custom validation rule does not pass. |
150 |
041 |
Cross-sectional component 0 is incorrectly attached to 2 instead of to 1. |
The cross-sectional component is attached to a wrong level. |
150 |
042 |
Invalid date format "0". |
Appears if the TIME_PERIOD attribute does not match the TIME_FORMAT. |
150 |
043 |
Structure type wrongly references 1 instead of 0. |
If the dataset header contains a URN reference to another artefact than expected. |
100 |
044 |
The dataset references dataflow "0" which could not be resolved. |
The structure file supplied to the STRUVAL service call does not contain a dataflow (identified by agency, name, and version) that is referenced from the dataset. |
100 |
045 |
The dataset references DSD "0" which could not be resolved. |
The structure file supplied to the STRUVAL service call does not contain a DSD (identified by agency, name, and version) that is referenced from the dataset. |
501 |
046 |
Component attribute 0 with parent 1 not supported. |
The XML attribute is in the wrong element. |
501 |
047 |
Cannot read dataset for structure of type: '0' |
If the dataset has a structure reference which is neither DSD nor Dataflow. |
501 |
048 |
The DSD 0 is missing a time dimension. |
DSDs that STRUVAL can process must contain a time dimension. |
501 |
049 |
Cannot validate the header of format 0. |
Appears when STRUVAL tries to validate a header but the given dataset file is not detected as one of the following formats: COMPACT_2_0, GENERIC_2_0, CROSS_SECTIONAL_2_0, UTILITY_2_0, GENERIC_2_1, GENERIC_2_1_XS,COMPACT_2_1 or COMPACT_2_1_XS. |
150 |
050 |
Property not found 0 |
Appears when the validation fails, because of missing input or structure file |
140 |
051 |
Configuration Error 0 |
Appears when Excel Data Reader was not configured correctly. |
140 |
052 |
Excel data reader error 0 |
Appears when Reading the excel file was not possible. |
140 |
053 |
Invalid Parameters detected 0 |
Appears when misconfiguration exists inside Parameter Sheet or Mapping Sheet. |
150 |
054 |
Error While Processing XML: 0 |
Appears when XML structure validation fails. |
Bibliography Chadwick, Dave Robert, et al. 2011. Manure management: Implications for greenhouse gas emissions. Online 2011. Cited: 03 03 2019. https:www.researchgate.netpublication235409271_Manure_management_Implications_for_greenhouse_gas_emissions. CLRTAP. 2014. Online 13 03 2014. Cited: 14 03 2018. http:www.clrtap-tfrn.orgsitesclrtap-tfrn.orgfilesdocumentsTFRN-9Framework%20code%20TFRN-9%20Mar%2014FC_ManApplic_13-03-14%20clean%20sent.pdf. EC. 2017. Online 22 02 2017. Cited: 08 12 2017. https:ec.europa.euagriculturedirect-supportiacs. EEA. 2016. Online 2016. Cited: 08 12 2017. http:www.unece.orgfileadminDAMenvlrtapPublicationsAmmonia_SR136_28-4_HR.pdf. ISSN 1977-8449. —. 2017. Online 2017. Cited: 19 12 2017. https:www.eea.europa.euthemesairnational-emission-ceilingsnational-emission-ceilings-directive. —. 2016. Online 2016. Cited: 19 12 2017. http:ec.europa.euenvironmentwaterwater-nitratesindex_en.html. —. 2017. Online 09 2017. Cited: 18 12 2017. https:www.eea.europa.eupublicationsemep-eea-guidebook-2016part-b-sectoral-guidance-chapters4-agriculture3-b-manure-management-2016at_downloadfile. EFGS & Eurostat. 2017. Online 2017. Cited: 20 12 2017. http:www.efgs.infowp-contentuploads201703GEOSTAT2ReportMain.pdf. FAO. 2015. http:www.fao.orgdocrep017ap862eap862e00.pdf. Online 2015. IPCC. 2006. Online 2006. Cited: 12 12 2017. http:www.ipcc-nggip.iges.or.jppublic2006glpdf4_Volume4V4_10_Ch10_Livestock.pdf. JRC. 2017. https:eippcb.jrc.ec.europa.eusitesdefaultfiles2019-11JRC107189_IRPP_Bref_2017_published.pdf. Online 2017. Cited: 20 09 2018. Jun, Paul, Gibbs, Michael and Gaffney, Kathryn. CH4 and N2O emissions from livestock manure. Online https:www.ipcc-nggip.iges.or.jppublicgpbgp4_2_CH4_and_N2O_Livestock_Manure.pdf. Lupis, S. G., Embertson, N. and Davis, J. G. 2012. Online 12 2012. Cited: 12 12 2017. http:extension.colostate.edutopic-areasagriculturebest-management-practices-for-reducing-ammonia-emissions-lagoon-covers-1-631b. MWPS. 2004. Online 2004. Cited: 12 12 2017. http:msue.anr.msu.eduuploadsfilesManureCharacteristicsMWPS-18_1.pdf. UNECE. 2015. Online 2015. Cited: 08 12 2017. http:www.unece.orgfileadminDAMenvlrtapPublicationsAmmonia_SR136_28-4_HR.pdf. Webb, J., et al. 2013. Chapter seven - An Assessment of the Variation of Manure Nitrogen Efficiency throughout Europe and an Appraisal of Means to Increase Manure-N Efficiency. Advances in Agronomy. s.l. : Elsevier, 2013, Vol. 119. other references [http:ramiran.uvlf.skdoc11RAMIRAN%20Glossary_2011.pdf
http://ramiran.uvlf.sk/doc11/RAMIRAN%20Glossary_2011.pdf] https:ec.europa.eueurostatstatistics-explainedindex.php?title=Glossary:Biomass https:ec.europa.eueurostatstatistics-explainedindex.php?title=Glossary:Biofuels h1.Index of figures Figure 1 – Farm structure data available by country and year since 19992000 Figure 2 – Extended frame case 1: the frame allows distinguishing between holdings producing for the market and holdings producing (mainly) for self-consumption Figure 3 – Extended frame case 2: the frame does not allow distinguishing between holdings producing for the market and holdings producing (mainly) for self-consumption Figure 4 – Delimitation and mapping of the areas facing natural and other specific constraints (November 2020) Figure 5 – Glasshouse Figure 6 – Greenhouse Figure 7 – Shade house Figure 8 – Walk in tunnel Figure 9 – Plastic house – high accessible cover, the plants are accessible without destroying the shelter Figure 10 – Low tunnel Figure 11 – Location of the holding Figure 12 – Legal personality of the holding and status of the holder and manager Figure 13 – Total farm area (FA) general hierarchy Figure 14 – Arable land hierarchy Figure 15 – Cereals hierarchy Figure 16 – Dry pulses and protein crops hierarchy Figure 17 – Root crops hierarchy Figure 18 - Industrial crops hierarchy Figure 19 – Plants harvested green hierarchy Figure 20 – Fresh vegetables hierarchy (extract, full hierarchy can be found in Eurostat's glossary) Figure 21 – Permanent grassland hierarchy Figure 22 – Permanent crops' hierarchy Figure 23 – Fruits, berries and nuts hierarchy (extract, for full tree see Eurostat's website) Figure 24 – Citrus' hierarchy Figure 25 – Grapes' hierarchy Figure 26 – Olives' hierarchy Figure 27 – Mushrooms' hierarchy Figure 28 – UAA under glass hierarchy Figure 29 – UAA organic hierarchy Figure 30 – Bovine animals' hierarchy Figure 31 – Sheep and goats hierarchy Figure 32 – Pigs hierarchy Figure 33 – Poultry hierarchy Figure 34 – Rabbits hierarchy Figure 35 – Other livestock hierarchy Figure 36 – Duration of compulsory educationtraining and student's age-groups (201617) Figure 37 – Labour force categories Figure 38 – Farm work and other gainful activities in the agricultural holding Figure 39 – Other gainful activities in the agricultural holding: main vs. secondary Figure 40 – Pome and stone fruit hierarchy for the orchards module Figure 40 – Citrus' hierarchy for the orchards module Figure 41 – Olives' hierarchy for the orchards module Figure 41 – Grapes' hierarchy for the orchards module Figure 44 – Totals of continuous variables in eurobase Figure 45 – Count variables in eurobase Figure 56 – EDAMIS Web Portal front page Figure 57 – Validation Figure 58 – Validation process (GSBPM notation) Figure 59 – Schematic of the input hall (green highlights are items visible to NSI) Figure 60 – Retrieval of a report in EDAMIS Web Application Figure 61 – Retrieval of a report in EDAMIS Web Portal Figure 62 – Example error report header, with errors detected Figure 63 – Example error report header, with no errors detected Figure 64 – Grouping of errors Figure 65 – Example of error listing without filtering Figure 66 – Example of error listing with a measure filtered for confidentiality. The concept value and error description fields are removed Figure 67 – High level business process for reporting SDMX compliant reference metadata Figure 68 – Welcome screen of the ESS Metadata Handler Figure 69 – Agricultural holding density (number of farms per square Km of UAA) Figure 70 – If only one farm at a location, assign it to a random neighbouring cell within the same NUTS3; if still not possible, enlarge the area. Figure 71 – INSPIRE Grid Figure 72 – Standard Output Coefficient timetable Figure 73 – Navigation tree on Eurostat database showing the farm structure (ef) theme Figure 74 – Navigation tree on Eurostat database showing some of the farm structure tables Figure 75 – General aspect of a table on the data explorer Figure 76 – Example for solid bovine (for beef) manure Figure 77 – Example for liquid swine manure |