Begin with 1_ReadMe_Master.txt and 1_ReadMe_Master.do file. The .do file will run all other emails and replicate all major findings. June 6, 2022 STATA Version 16.1 Files include: 1. Draft Manuscript (.pdf) 2. Online Appendix (.pdf) 3. IRB Certificates (.pdf) 4. Original 2019 MBEI report (.pdf) 5. Original 2018 MBEI report (.pdf) 7 STATA .dta files (see Step III below) 8. STATA .do files to replicate analysis (See Step VI below) 9. Official MBEI 2020 Survey Codebook .xls 10. Official MBEI 2020 Observational Data Codebook .xls 11. Codebook generated in .do file #2 with variables used in replication JOP_MBEI_ReplicationData_Codebook.xls 12. Zipped folder of facilitation reports from each workshop. */

The ideological evolution of Western European social democratic parties has received considerable scholarly attention over the decades. The most widespread view concerns the alleged programmatic moderation and convergence with the mainstream right of this party family. However, recent empirical investigations based on electoral manifestos come to different conclusions, highlighting an increase over time in Western European social democratic parties' emphasis on traditional economic left goals, especially in recent years. Hence, this article analyses the evolution of the social democratic programmatic outlook with regard to traditional economic left issues. It does so by relying on Manifesto Project (MARPOR) data about such formations in 369 general elections across 20 Western European countries between 1944 and 2021, employing different indicators of economic left emphasis and time to ensure the robustness of the findings. The analysis shows how, at the aggregate level, social democracy increases its emphasis on traditional economic left issues over time, with the effect driven entirely by the recent post-Great Depression years. However, once disaggregating the results, a more differentiated picture emerges, pointing towards potential causes of concern in terms of measurement validity within the MARPOR data. The article discusses the substantive and, especially, methodological implications of its findings in detail.

Enquête naar de arbeidskrachten (EAK) Doel en korte beschrijving De steekproefenquête naar de arbeidskrachten is een enquête bij particuliere huishoudens, die gedurende het hele jaar wordt gehouden. Ze is gebaseerd op de antwoorden van ongeveer 110.000 personen (respondenten) van 15-89 jaar. Haar voornaamste doelstelling is de populatie van 15-89 jaar op te delen in drie groepen (nl. werkende personen, werklozen en niet-beroepsactieve personen), en over elk van deze categorieën beschrijvende en verklarende gegevens te verstrekken. Deze enquête wordt ook in de andere EU-lidstaten uitgevoerd en wordt gecoördineerd door de statistische dienst van de Europese Unie, EUROSTAT. In België wordt de EAK georganiseerd door Statbel (Algemene Directie Statistiek - Statistics Belgium). De bedoeling is informatie te vergaren die op Europees vlak vergelijkbaar is, o.m. inzake werkgelegenheids- en werkloosheidscijfers overeenkomstig de definities van het Internationaal Arbeidsbureau (IAB), en daarnaast gegevens te verzamelen en te verspreiden die elders niet verkregen kunnen worden. Voorbeelden hiervan zijn mobiliteit van de werknemers, motivatie voor deeltijds werken, de verschillende vormen van tijdelijke arbeid, beroep, onderwijsniveau van de bevolking op beroepsactieve leeftijd,… Populatie Leden van privé-huishoudens van 15-89 jaar Basis van de steekproef Demografische gegevens van het Rijksregister Dataverzamelingsmethode en eventuele steekproefomvang De informatie wordt voor de eerste bevraging verzameld via face to face interviews. Sinds 2017 volgen daarna nog drie kortere opvolgbevragingen die via het web of telefonisch gebeuren. Gezinnen die uitsluitend bestaan uit niet-beroepsactieve personen ouder dan 64 jaar mogen ook telefonisch worden bevraagd. Jaarlijks nemen in België ongeveer 34.000 unieke huishoudens deel aan deze enquête. Respons Gemiddeld bedraagt de respons in de eerste bevraging 68% en in de opvolgbevragingen tussen de 90% en 95%. Frequentie Driemaandelijks. Timing publicatie Resultaten beschikbaar +/- 3 maanden na de referentieperiode Formulieren Enquête naar de arbeidskrachten 2024 (PDF, 1 Mb) Definities De enquête is geharmoniseerd op Europees niveau. De definities over werkgelegenheid en werkloosheid die worden gehanteerd zijn die van het Internationaal Arbeidsbureau (IAB), waardoor een vergelijkbaarheid van de resultaten op internationaal vlak wordt gewaarborgd. Personen met een job (werkende personen) zijn personen die gedurende de referentieweek arbeid verrichtten ‘tegen betaling’ of met als doel ‘winst te maken’ ongeacht de duur (ook al was dit maar één uur), of die een job hadden maar tijdelijk afwezig waren. Men kan bijvoorbeeld tijdelijk afwezig zijn omwille van vakantie, ziekte, technische of economische redenen (tijdelijke werkloosheid),…. Ook de meewerkende familieleden worden tot de werkenden gerekend. Sinds 2021 worden personen die een ononderbroken periode van langer dan drie maanden tijdelijke werkloos zijn bij de werklozen of niet-beroepsactieven gerekend en niet meer bij de werkenden. Werklozen zijn alle personen die: (a) tijdens de referentieweek geen werk hadden, d.w.z. niet in loondienst of als zelfstandige werkten; (b) voor werk beschikbaar waren, d.w.z. voor werk in loondienst of als zelfstandige beschikbaar waren binnen twee weken na de referentieweek; (c) actief werk zochten, d.w.z. gedurende de laatste vier weken met inbegrip van de referentieweek gerichte stappen hadden ondernomen om werk in loondienst of als zelfstandige te zoeken, of die werk hadden gevonden en binnen ten hoogste drie maanden zouden beginnen te werken. Opgelet! De IAB‐werkloosheidscijfers staan los van een eventuele inschrijving bij VDAB, Actiris, FOREM of ADG, evenals van het ontvangen van een uitkering van de RVA, en zijn dus niet vergelijkbaar met de administratieve werkloosheidscijfers. De beroepsbevolking is samengesteld uit de werkloze en de werkende bevolking. Niet‐beroepsactieven zijn alle personen die niet beschouwd worden als personen met een betrekking of als werklozen. De werkgelegenheidsgraad geeft het percentage werkende personen in een bepaalde leeftijdsgroep weer. De werkgelegenheidsgraad in het kader van de Europa 2020‐strategie geeft het percentage werkende personen in de bevolking van 20 tot 64 jaar weer. De werkloosheidsgraad geeft het percentage werklozen in de beroepsbevolking (werkende personen + werklozen) binnen een bepaalde leeftijdsgroep weer. De activiteitsgraad geeft het percentage beroepsbevolking (werkende personen + werklozen) in de totale bevolking binnen een bepaalde leeftijdsgroep weer. Bovenstaande indicatoren (werkgelegenheidsgraad, werkloosheidsgraad en activiteitsgraad) zijn de belangrijkste indicatoren om de arbeidsmarktevolutie op internationaal niveau te vergelijken. Laaggeschoolden zijn die personen die maximaal een diploma hebben van het lager secundair onderwijs. Middengeschoolden zijn personen die een diploma behaald hebben van het hoger secundair onderwijs, maar geen diploma van het hoger onderwijs. Hooggeschoolden hebben een diploma van het hoger onderwijs. Metadata Werkgelegenheid, werkloosheid, arbeidsmarkt.pdf Enquête naar de arbeidskrachten (EAK).pdf Methodologie enquêtes Wijzigingen in de Enquête naar de arbeidskrachten (EAK) in 2021 EAK: De methodologische verbeteringen in de Enquête naar de Arbeidskrachten 2017 (PDF, 98 Kb) EAK: voorstelling van de enquête vanaf 2017 (PDF, 105.77 Kb) EAK: voorstelling van de enquête tot 2016 (PDF, 98.44 Kb) Nota naar aanleiding van publicatie gegevens T4 2024 & jaarresultaten 2024 (pdf) Wetgeving Koninklijk besluit 10 JANUARI 1999 betreffende een steekproefenquête naar de arbeidskrachten (PDF, 17.26 Kb) Koninklijk besluit tot wijziging van het koninklijk besluit van 10 januari 1999 betreffende een steekproefenquête naar de arbeidskrachten (PDF, 17.48 Kb)

Blast fishing has caused long-term damage to reefs and coastal livelihoods in Tanzania and across the globe for decades. In 2015, a Tanzanian government campaign against blasting was initiated; a subsequent reduction was observed. The aim of my study was to: (1) assess the current global status of blast fishing, (2) analyse causal factors underlying involvement in blast fishing and cessation of the activity in Tanzania; and (3) assess how Tanzania’s coastline communities and their fish stocks have been affected by the reduction of blast fishing. Primary data on economic indicators, marine resource management and fishery characteristics were collected in 2019 from 101 households and 234 fishers in 9 coastal districts in Tanzania. Data were collected using household and fisher surveys, which are stored in .pdf format. The data and metadata are stored in .xlsx format, alternative open access formats can be provided on request. The r code used to conduct the analysis is stored in .r format.

In this dataset we present core data of an integrative evaluation framework for assessing the environmental, social, and economic sustainability of urban agriculture. The multi-criteria analysis is conducted by an Analytic Hierarchy Process and a participatory approach. The data integrate the selection and weighting of sub-criteria based on two online surveys:

1) Survey 1: The selection of suitable sub-criteria for assessing the sustainability of urban agriculture was done by European scientific experts.

2) Survey 2: The weighting of the selected sub-criteria was done on the example of vertical farming and community supported agriculture. Therefore, we involved stakeholders representing key actors for the implementation of urban agriculture: city administrations and non-governmental organizations (NGOs) of ten German case study cities, practitioners and technical-scientific experts.

List of data and content

1) Survey_1 (*.zip):

• Survey_1_Criteria_Selection_English: Online survey in English (*.pdf)
• Survey_1_Information_Sub-criteria_English: Information about the sub-criteria provided in the survey (in English) (*.pdf)
• Survey_1_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)

2) Survey_2 (*.zip):

• Survey_2_AHP_City_Administrations_German: Online survey for city administrations in German (*.pdf)
• Survey_2_AHP_Practitioners_German: Online survey for practitioners and technical-scientific experts in German (*.pdf)
• Survey_2_AHP_NGOs_German: Online survey for NGOs in German (*.pdf)
• Survey_2_Information_Sub-Criteria_German: Information about the sub-criteria provided in the survey (in German) (*.pdf)
• Survey_2_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)
• rdata_CA_AHP_edible_Cities_2022-03-18_10-28: Results of the survey for city administrations (*.csv)
• rdata_NGO_AHP_edible_Cities_2022-03-18_10-40: Results of the survey for NGOs (*.csv)
• rdata_PE_AHP_edible_Cities_2022-03-18_10-41: Results of the survey for practitioners and technical-scientific experts (*.csv)
• rdata_all_AHP_edible_Cities_2022-03-18_09-53: Total results of the survey

Data acquisition and processing

The methods are described in this linked publication:

John, H., & Artmann, M. (2024). Introducing an integrative evaluation framework for assessing the sustainability of different types of urban agriculture. International Journal of Urban Sustainable Development, 16 (1), 35-52. doi: 10.1080/19463138.2024.2317795

The methodology of the performed analytic hierarchy process (AHP) is published in a separate repository on GitHub including a paper that systematically explains the AHP by means of code examples, starting with the raw data, through their adaptation to the software functions of the ahpsurvey R-package, and finally, execution of the AHP up to the visualization of the results.

Acknowledgments

The authors thank Mabel Killinger and Marie Herzig for their help in stakeholder identification as well as all experts and stakeholders for their participation in the two online surveys and their helpful comments. Data processing and analysis by means of an Analytic Hierarchy Process in R would not have been possible without the help of Björn Kasper.

Economic survey of Karnataka with important tables in csv format

This fileset contains half-yearly flow-of-funds data for the branch network of the Yokohama Specie Bank between 1893 and 1908. Data has been organized into matrices.This set is the 'simplified' one, i.e. shows totals of 'amounts transferred'; totals are in Japanese yen.These matrices have formed the basis for visualizations in social network analysis (SNA) software packages, as, for instance, UCINet, Pajek, Gephi, and the igraph-package in R.

The Digital Surficial Geologic-GIS Map of Gauley River National Recreation Area, West Virginia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (gari_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (gari_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (gari_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (gari_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gari_surficial_geology_metadata_faq.pdf). Please read the gari_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gari_surficial_geology_metadata.txt or gari_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:12,000 and United States National Map Accuracy Standards features are within (horizontally) 10.2 meters or 33.3 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The Unpublished Digital Surficial Geologic Map of Bluestone National Scenic River and Vicinity, West Virginia is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (blus_geology.gdb), a 10.1 ArcMap (.MXD) map document (blus_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (blue_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (blus_gis_readme.pdf). Please read the blus_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia University and West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (blus_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/blue/blus_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:12,000 and United States National Map Accuracy Standards features are within (horizontally) 6.1 meters or 20 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.2. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 17N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Bluestone National Scenic River.

description: The Unpublished Digital Bedrock Geologic Map of New River Gorge National River and Vicinity, West Virginia is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (neri_geology.gdb), a 10.1 ArcMap (.MXD) map document (neri_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (neri_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (neri_gis_readme.pdf). Please read the neri_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie OMeara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (neri_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/neri/neri_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 17N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of New River Gorge National River.; abstract: The Unpublished Digital Bedrock Geologic Map of New River Gorge National River and Vicinity, West Virginia is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (neri_geology.gdb), a 10.1 ArcMap (.MXD) map document (neri_geology.mxd), individual 10.1 layer (.LYR) files for each GIS data layer, an ancillary map information (.PDF) document (neri_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.TXT) and FAQ (.HTML) formats, and a GIS readme file (neri_gis_readme.pdf). Please read the neri_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie OMeara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (neri_metadata_faq.html; available at http://nrdata.nps.gov/geology/gri_data/gis/neri/neri_metadata_faq.html). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 17N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of New River Gorge National River.

Purpose and brief description The industrial production index makes it possible to monitor the evolution in volume of the value added at factor cost over a given reference period. Value added at basic prices can be calculated as follows: turnover (excluding VAT and other similar deductible taxes directly linked to turnover) plus capitalised production, plus other operating income, plus or minus the changes in stocks, minus the purchases of goods and services, minus other taxes on products which are linked to turnover but not deductible, and the subsidies received on the products. However, the data to produce this index are not available on a monthly basis. In practice, the adequate representative values to produce the indices are: gross production values (deflated); volumes; turnover (deflated); working hours; raw materials; energy... Reference year From January 2024, the indices are expressed with reference year 2021=100. Therefore, we have created a new downloadable file, expressing the full series with reference year 2021=100. The downloadable files with reference year 2015=100 remain available but will no longer be updated. These files end consequently in December 2023. Data collection method and sample size Prodcom is the monthly survey on industrial production. Cooperation among the EU countries seeks to improve the comparability of statistical data. The Statistical Office of the European Union has therefore taken the initiative to collect data on industrial production in all member states with the same product list, in the same sectors, etc. This initiative was named “Prodcom”: “PRODucts of the European COMmunity”. This survey is compulsory. The legal framework laid down in EC Regulation 3924/91, the Royal Decree of 28 January 1994, published in the Belgian Official Journal of 15 February 1994 and the Royal Decree of 20 February 2008, published in the Belgian Official Journal of 10 March 2008. The language of the form (part 1 and part 2) is determined by the place of business. The Royal Decree of 18 July 1966 applies here, published in the Belgian Official Journal on 2 August 1966, which coordinates the laws on the use of languages in administrative matters. A form must be completed for each local unit. The local unit is an enterprise or part thereof (e.g. workplace, factory, shop, office, mine or warehouse) located in a geographically defined place. At or from that place, economic activities are carried out for which - barring exceptions - one or more persons work (possibly part-time) on behalf of the same enterprise. Population The survey covers the activities of sections B and C of the Statistical Classification of Economic Activities in the European Community NACE Rev. 2 with the exception of sections 5, 6 and 19. In summary, two groups are concerned: any industrial enterprise or establishment employing 20 persons or more according to one of its quarterly NSSO declarations of the previous year or whose annual turnover in the previous year was at least 4,200,000 euros; any new industrial enterprise or establishment employing 20 persons or more according to one of its quarterly NSSO declarations for the current year or whose cumulative turnover in the course of the year amounted to at least 4,200,000 euros. This means that a declarant who has employed 20 persons at least once in a given year must answer in the following year (calendar year). Periodicity Monthly. Release calendar Results available 1 month + 10 days after the reference period. Metadata Prodcom manual.pdf Prodcom conversion table 2022.xlsx Industrial production (Prodcom).pdf Prodcom survey.pdf Data collection in shops and in private or public organisations (PPP).pdf Nomenclature The Prodcom list.xls

This fileset contains half-yearly flow-of-funds data for the branch network of the Yokohama Specie Bank between 1893 and 1908. Data has been organized into matrices, and annotated for currency (color codes), and has been appended with historically accurate exchange rates for the periods.This set is the 'original' one, including data for interest bills (which have been ranked under 'loans' in the original Midterm Reports 半季報告), and including calculation of the 'amounts transferred', yet without conversions.

The Digital Surficial Geologic-GIS Map of New River Gorge National Park and Preserve, West Virginia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (neri_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (neri_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (neri_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (neri_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (neri_surficial_geology_metadata_faq.pdf). Please read the neri_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (neri_surficial_geology_metadata.txt or neri_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:48,000 and United States National Map Accuracy Standards features are within (horizontally) 24.4 meters or 80 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The Digital Surficial Geologic-GIS Map of Bluestone National Scenic River and Vicinity, West Virginia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (blue_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (blue_surficial_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (blue_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (blue_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (blue_surficial_geology_metadata_faq.pdf). Please read the blue_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: West Virginia Geological and Economic Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (blue_surficial_geology_metadata.txt or blue_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:12,000 and United States National Map Accuracy Standards features are within (horizontally) 10.2 meters or 33.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).