{"status":"OK","data":{"id":566773,"identifier":"8575OP","persistentUrl":"https://doi.org/10.34894/8575OP","protocol":"doi","authority":"10.34894","separator":"/","publisher":"DataverseNL","publicationDate":"2025-12-05","storageIdentifier":"surf://10.34894/8575OP","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"datasetType":"dataset","locks":[],"latestVersion":{"id":32015,"datasetId":566773,"datasetPersistentId":"doi:10.34894/8575OP","datasetType":"dataset","storageIdentifier":"surf://10.34894/8575OP","versionNumber":1,"internalVersionNumber":24,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","lastUpdateTime":"2025-12-05T12:46:07Z","releaseTime":"2025-12-05T12:46:07Z","createTime":"2025-11-27T15:48:23Z","publicationDate":"2025-12-05","citationDate":"2025-12-05","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9999,"termsOfUse":"This dataset is only available under strict conditions within the Microdata environment at CBS. Since this is a project-generated dataset made available for reuse via the CBS Data Storage, access to the following source CBS files has to be requested:\n\n(see full list under \"Data Source\"). Read more about the conditions to access and use the CBS data: www.cbs.nl/nl-nl/onze-diensten/maatwerk-en-microdata/microdata-zelf-onderzoek-doen","fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Compressed Population-scale Network Netherlands 2009-2023 in MLN format"},{"typeName":"otherId","multiple":true,"typeClass":"compound","value":[{"otherIdAgency":{"typeName":"otherIdAgency","multiple":false,"typeClass":"primitive","value":"CBS Project Number"},"otherIdValue":{"typeName":"otherIdValue","multiple":false,"typeClass":"primitive","value":"9629"}}]},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Bokányi, Eszter"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/027bh9e22","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"Leiden University","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0002-8625-1139"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Kazmina, Yuliia"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/04dkp9463","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"University of Amsterdam","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0002-1292-2497"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Heemskerk, Eelke M."},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/04dkp9463","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"University of Amsterdam","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0001-7356-5318"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Takes, Frank W."},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"https://ror.org/027bh9e22","expandedvalue":{"scheme":"http://www.grid.ac/ontology/","termName":"Leiden University","@type":"https://schema.org/Organization"}},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0001-5468-1030"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"PLANET-NL Team"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Bokányi, Eszter"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"Leiden University"}},{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"PLANET-NL Team"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"This record (and attached Documentation, see Files) describes the content and structure of “Compressed Population-scale Network Netherlands 2009-2023”, a project-generated file available via the CBS Microdata environment. The dataset consists of yearly node-aligned multilayer network (MLN) objects for the entire resident population of the Netherlands, where edges are based on the person networks published within Microdata by CBS (BURENNETWERKTAB, COLLEGANETWERKTAB, HUISHOUDENNETWERKTAB, FAMILIENETWERKTAB, KLASGENOTENNETWERKTAB), and some basic node information and layer decoding are also present alongside the edge information. \n
\nThe advantage of this data source is that compared to the original data, MLN objects are small in size, encode all different edge types (layers) between two people in the same location, and are memory-efficient if read with the corresponding mlnlib Python library. The mlnlib library also contains optimized procedures for further network analysis, sample selection and aggregation tasks, as well as exports into common network libraries or formats.\n
\nEach yearly network is directed and unweighted consisting of edges of 32 different types or layers belonging to 5 larger layer categories (called groups in the object) corresponding to the Microdata person network tables. The MLN objects follow the intermediate format required for fast loading by the mlnlib Python library (https://pypi.org/project/mlnlib), with each yearly network consisting of the following three files: \n\nThe mlnlib library which uses this as a native format can installed through ‘pip’ in a Python environment, as such, it can be requested when setting up a Microdata project.\n
\nPlease check \"Notes\" for the general description of the micro databases such as the definition of the population, methodological details and the quality and origin of the data. In \"Notes\", you can find a description of the format of the database and the list of all possible scores for the categorical variables and their significance."}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Multilayer network"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Population-scale network"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Social network"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Person network"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Adjacency matrix"}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Sociology"},"topicClassVocab":{"typeName":"topicClassVocab","multiple":false,"typeClass":"primitive","value":"ELSST"},"topicClassVocabURI":{"typeName":"topicClassVocabURI","multiple":false,"typeClass":"primitive","value":"https://elsst.cessda.eu/id/6/450c86d9-8224-4090-8b13-c430cbff3f28"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Family"},"topicClassVocab":{"typeName":"topicClassVocab","multiple":false,"typeClass":"primitive","value":"ELSST"},"topicClassVocabURI":{"typeName":"topicClassVocabURI","multiple":false,"typeClass":"primitive","value":"https://elsst.cessda.eu/id/6/37962809-512d-4f33-826f-15446df86392"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Interpersonal relations"},"topicClassVocab":{"typeName":"topicClassVocab","multiple":false,"typeClass":"primitive","value":"ELSST"},"topicClassVocabURI":{"typeName":"topicClassVocabURI","multiple":false,"typeClass":"primitive","value":"https://elsst.cessda.eu/id/6/de9bcc39-a017-4c61-b999-db9239b4d084"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Employment"},"topicClassVocab":{"typeName":"topicClassVocab","multiple":false,"typeClass":"primitive","value":"ELSST"},"topicClassVocabURI":{"typeName":"topicClassVocabURI","multiple":false,"typeClass":"primitive","value":"https://elsst.cessda.eu/id/6/aa0ddef6-51fa-4eee-bcb5-2b64c41a4818"}},{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Work"},"topicClassVocab":{"typeName":"topicClassVocab","multiple":false,"typeClass":"primitive","value":"ELSST"},"topicClassVocabURI":{"typeName":"topicClassVocabURI","multiple":false,"typeClass":"primitive","value":"https://elsst.cessda.eu/id/6/aa0ddef6-51fa-4eee-bcb5-2b64c41a4818"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Bokányi, E., Heemskerk, E. M., & Takes, F. W. (2023). The anatomy of a population-scale social network. Scientific Reports, 13(1), 9209."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"10.1038/s41598-023-36324-9"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1038/s41598-023-36324-9"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Bokányi, E., Kazmina, Y., & de Jong, R. (2023). POPNET MultiLayerNetwork Python Class (Version v2.0) [Computer software]. Zenodo."},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"10.5281/ZENODO.10838866"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.5281/ZENODO.10838866"}},{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"van der Laan, J. (2022). A Person Network of the Netherlands."},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://www.cbs.nl/-/media/_pdf/2022/20/person_network_netherlands.pdf"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"Description\n
\nThis dataset was constructed from the five CBS person network microdata layers with additional information on the underlying population for each calendar year 2009–2023. The construction uses the conversion toolchain from the repository https://github.com/planet-nl/compressed_population_scale_network_nl, which reads the original edge lists from the RA along with some node information, and produces per‑year MLN objects that are fast to load. The conversion aligns nodes across layers and years, encodes multilayer edges in a single sparse adjacency matrix using binary encoding for the layers, merges node attributes from multiple CBS sources into nodes.csv.gz, and produces analysis‑ready files per year (layers.csv, nodes.csv.gz, edges.npz).\n
\n
\nPerformance & footprint:\n\n
\nReproducibility:\n\n
\nDescription of the population\n
\nYear YYYY: all people alive and registered in the BRP with an active address on January 1 in year YYYY.
\nAll years: The network nodes are aligned based on the union of the yearly populations between 2009 and 2023, thus the full population of the dataset is anyone having an active address and alive on at least one of the January 1st dates of the years between 2009 and 2023. The total number of rows and columns in yearly edges.npz adjacency matrices correspond to the number of people in this unioned population.\n
\nStructure of database\n
\nEach year YYYY has a separate folder, and each year folder contains three files: layers.csv, nodes.csv.gz, and edges.npz."},{"typeName":"producer","multiple":true,"typeClass":"compound","value":[{"producerName":{"typeName":"producerName","multiple":false,"typeClass":"primitive","value":"Leiden University and University of Amsterdam through the PLANET-NL project"}}]},{"typeName":"distributor","multiple":true,"typeClass":"compound","value":[{"distributorName":{"typeName":"distributorName","multiple":false,"typeClass":"primitive","value":"Centraal Bureau voor Statistiek"},"distributorAbbreviation":{"typeName":"distributorAbbreviation","multiple":false,"typeClass":"primitive","value":"CBS"}}]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Bokányi, Eszter"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2025-11-27"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2009"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2023"}}]},{"typeName":"relatedMaterial","multiple":true,"typeClass":"primitive","value":["Python package: https://pypi.org/project/mlnlib/\n
\nSource for package: https://github.com/planet-nl/mlnlib\n
\nScripts generating the data: https://github.com/planet-nl/compressed_population_scale_network_nl"]},{"typeName":"dataSources","multiple":true,"typeClass":"primitive","value":["CBS microdata:\n"]},{"typeName":"accessToSources","multiple":false,"typeClass":"primitive","value":"This dataset is only available under strict conditions within the Microdata environment at CBS. Since this is a project-generated dataset made available for reuse via the CBS Data Storage, access to the following source CBS files has to be requested:\n\n(see full list under \"Data Source\"). Read more about the conditions to access and use the CBS data: www.cbs.nl/nl-nl/onze-diensten/maatwerk-en-microdata/microdata-zelf-onderzoek-doen"}]},"socialscience":{"displayName":"Social Science and Humanities Metadata","name":"socialscience","fields":[{"typeName":"universe","multiple":true,"typeClass":"primitive","value":["All people alive and registered in the BRP with an active address on January 1 in year YYYY
\nThe network nodes are aligned based on the union of the yearly populations between 2009 and 2023, thus the full population of the dataset is anyone having an active address and alive on at least one of the January 1st dates of the years between 2009 and 2023. The total number of rows and columns in yearly edges.npz adjacency matrices correspond to the number of people in this unioned population."]},{"typeName":"socialScienceNotes","multiple":false,"typeClass":"compound","value":{"socialScienceNotesType":{"typeName":"socialScienceNotesType","multiple":false,"typeClass":"primitive","value":"List of variables"},"socialScienceNotesText":{"typeName":"socialScienceNotesText","multiple":false,"typeClass":"primitive","value":"The following is a list of all the variables for the three files in a given year’s folder.\n
\nIn nodes.csv.gz files:\n\n
\nIn the layers.csv files:\n
    \n
  1. layer_id: int8 (0–#layers-1). Numeric index used for bit-encoding in edges.npz. The adjacency stores 1 << layer_id as the bit flag. Valid range 0–63.
    2. \n
  2. layer: int16 (3-digit key). Integer identifier of layer. RELATIE from BURENNETWERKTAB, COLLEGANETWERKTAB, HUISHOUDENNETWERKTAB, FAMILIENETWERKTAB, and KLASGENOTENNETWERKTAB.
    3. \n
  3. label: str. Short English human-readable label for layer.
    4. \n
  4. group: str {family, household, neighbor, work, school}. Human-readable label for the group of layers, based on which 5-layer network can be created with the MultiLayerNetwork.get_grouped_mln() method. In such a representation, all subtypes of one NETWERK file will be merged into the 5 main types.
    5. \n
  5. label_long: str. Group : label string descriptions of layer.
    6. \n
  6. binary: int64. An integer number equal to 2^layer_id which is used to encode the layers in the compressed sparse adjacency matrix edges.npz.
    7. \n
\nThe edges.npz file contains the directed unweighted multilayer adjacency matrix in a numpy compressed binary format, which can be loaded in general with the scipy.load_npz command as a scipy.sparse.csr_matrix class variable (loading handled internally if mlnlib library is used). The element i,j (where i and j correspond to the id field of the nodes.csv.gz file) in a given year’s adjacency matrix is an unsigned integer. If decomposed to binary representation, it contains a value 1 at location L if an edge exists in layer with layer_id= L between persons i and j in a given year. The layer to binary location and binary value mapping can be found in layers.csv. Mapping and fast querying for certain layer types using bitwise AND and OR operations is handled automatically by the mlnlib library."}}}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/8575OP"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"1.0"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:32051bca-8b91-42eb-a346-38054f0c68cf"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-92442d83-55ea-4c94-93c7-14f6304b3bca"}]}},"files":[{"description":"Description of dataset, dataset structure and variables.","label":"Documentation_Compressed Population-scale Network Netherlands 2009-2023 in MLN format.pdf","restricted":false,"version":1,"datasetVersionId":32015,"dataFile":{"id":571207,"persistentId":"","filename":"Documentation_Compressed Population-scale Network Netherlands 2009-2023 in MLN format.pdf","contentType":"application/pdf","friendlyType":"Adobe PDF","filesize":343273,"description":"Description of dataset, dataset structure and variables.","storageIdentifier":"surf://store:19aedca7285-a869216f51e4","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"83f5e932c51b3a2b9be24810f9aee19c4c2e69bf"},"tabularData":false,"creationDate":"2025-12-05","publicationDate":"2025-12-05","lastUpdateTime":"2025-12-05T12:46:07Z","fileAccessRequest":true}}]}}}