This data reference standard provides a standard list of values to categorize data on person(s). The list reflects the classifications of gender and is designed to provide common data variables of the reported gender of person(s) or an individual’s personal and social gender identity. This data reference standard is to be read in conjunction with the Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices and the Disaggregated Data Action Plan. This list of values is intended to standardize the way gender classifications are described in datasets to enable data interoperability and improve data quality. The appendix lists a data reference table that includes one-digit codes for designating gender. Not included in this data reference standard is an additional two-digit code for further classification. This data reference standard will be reviewed as required by the data reference steward in consultation with the data reference standard custodian. For support or advice on the measurement of “gender of person” or related data variables, contact statcan.csds-cnsd.statcan@statcan.gc.ca

Data Stewardship vacancies collection to support FAIRsFAIR Data Stewardship Professional Competence Framework

This dataset is provided to validate and support the analysis of Data Stewardship competences. The dataset includes a collection of vacancies from the popular job search website indeed.com that responded to the search term "Data Steward".

Acknowledgment The research leading to these results has received funding from the Horizon2020 projects FAIRsFAIR (grant number 831558)

References FAIRsFAIR Project Deliverable D7.3 Data Stewardship Professional Competence Framework, Work in Progress. To be published Feb 2021 Yuri Demchenko, Lennart Stoy, Research Data Management and Data Stewardship Competences in University Curriculum, In Proc. Data Science Education (DSE), Special Session, EDUCON2021 – IEEE Global Engineering Education Conference, 21-23 April 2021, Vienna, Austria

This data reference standard is part of a suite that provides a standard list of values to categorize data on person(s). The list reflects the classifications of sex assigned at birth and is designed to provide common data variables of the reported sex at birth, typically assigned based on a person’s reproductive system and other physical characteristics. This data reference standard is to be used by exception and read in conjunction with Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices and the Disaggregated Data Action Plan. This list of values is intended to standardize the way sex assigned at birth classifications are coded in datasets to enable data interoperability and improve data quality. The numbering system is a one-digit code. The appendix lists a data reference table that includes the one-digit codes for designating sex assigned at birth. Not included in this data reference standard is the lived or current sex of person(s). This data reference standard will be reviewed as required by the data reference steward in consultation with the data reference standard custodian. For support or advice on the measurement of “sex at birth of person” or related data variables, contact statcan.csds-cnsd.statcan@statcan.gc.ca.

ABSTRACT:This dataset is used by the City as a log of datasets that have been published under the City’s open data policy, or are currently in the review process for potential publication. The dataset assists Dataset Managers, Data Architects and the Data Governance Working Group with monitoring updates, and may be useful to the public as a quick reference for the status of any datasets of interest. This dataset includes information gathered from the form developed by the Data Governance Working Group to consider datasets for publication. The dataset identifies roles for responsible parties, dates for significant actions, as well as the minimum refresh increment required for each approved dataset. It is a tabular dataset and is not associated with any geographical locations. The dataset is updated by the Chair or Co-Chair of the Data Governance Working Group following each meeting (typically monthly). DATA LAST UPDATED:December 5, 2018FIELD DESCRIPTIONS:DATANAME - Alias: Dataset Name - A descriptive name of the type of data contained within a dataset.REQUESTOR - Alias: Requestor - The party initiating the request for publication of a particular dataset.DEPARTMENT - Alias: Department - The City Department under which the dataset is maintained.DATACOORD - Alias: Data Coordinator - The individual designated by the Department to act as the liaison with the DG Working Group, Data Architect, Records Coordinator, Requestors and Dataset Managers on behalf of the Department on all matters related to the implementation of the Victorville Open Data Policy.DATAARCH - Alias: Data Architect - The individual assigned to oversee system integration between departmental data sources and the open data portal, facilitate availability of current and accurate published data, and review of datasets relative to technical/technology matters outlined in the Victorville Open Data Policy.DATAMNGER - Alias: Dataset Manager - The staff member within a department who is most familiar with a particular dataset will act as the primary data custodian and the point of contact for questions regarding the data within that dataset.DATEREQ - Alias: Request Date - The date the Open Data Review & Approval form was submitted to the chair or co-chair of the Data Governance Working Group.DATEAPPR - Alias: Approval Date - The date the Data Governance Working Group reviewed the Open Data Review & Approval form and approved the Data Architect and Dataset Manager to proceed with publication.ESTPUBDATE - Alias: Estimated Publication Date - The date by which the Data Governance Working Group anticipates the dataset will be published on the Open Data Portal.ORGPUBDATE - Alias: Original Publication Date - Original Publication Date.MINREFRESH - Alias: Minimum Refresh Increment - The minimum increment the Data Governance Working Group requires the dataset to be reviewed and refreshed.LASTREFRESH - Alias: Last Refresh Date - The date the dataset was last reviewed or updated (if applicable).NOTES - Alias: Notes - Miscellaneous information regarding the status of a dataset.

This feature class is part of the Cadastral National Spatial Data Infrastructure (NSDI) CADNSDI publication data set for rectangular and non-rectangular Public Land Survey System (PLSS) data set. The metadata description in the Cadastral Reference System Feature Data Set more fully describes the entire data set. This is a graphic representation of the data stewards for the Public Land Survey System (PLSS). For BLM data sets the the data steward is identifed at the township level or smaller area The Data Steward is agency that will be responsible for updates of the PLSS. In the shared environment of the Natioanl Spatial Data Infrastructure (NSDI) the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. Any questions about data content should be directed to the data steward.

Qualitative interviews with nine researchers at the Faculty of Technology, Policy and Management (TPM) at TU Delft were undertaken in order to get an understanding of data management needs at the faculty in advance of appointing a dedicated Data Steward. The purpose of this was to aid the recruitment of the Data Steward and to define the skills and experience of an ideal candidate, as well as help deciding on the work priority areas for the Data Steward. The results of this research can be also used as a point in time reference to monitor changes in data management practice at the faculty.

The main data management challenges identified were: handling personal sensitive research data; working with big data, managing and sharing commercially confidential information and software management issues. Despite the diversity of problems, some common issues were identified as well: need for improving daily data management practice, as well as the need for revising workflows for students’ research data. With the exception of one researcher, who was in opposition to the Data Stewardship project, all other researchers expressed their support for the project and welcomed the idea of having a dedicated Data Steward at the faculty.

Additionally, several follow up actions were already undertaken as a follow up of these interviews: the Data Stewardship Coordinator was invited to give two talks about Data Stewardship to two different groups of researchers; a member of the Research Data Support from the Library team was asked to deliver a training course for students; the Data Stewardship Coordinator was asked to discuss the best way of rolling our data management training for PhD students at TPM in coordination with the TPM Graduate School.

Given that the financial allocation for the Data Steward at TPM faculty is currently at 0,5 FTE for the first year and 1,0 FTE for the two subsequent years (until December 2020), it is recommended that the first year is spent on continuing and extending this research to better understand the needs of the faculty. It is suggested that at the same time, the Data Steward starts addressing the most urgent data management needs at TPM faculty, in particular the development of a data management policy, as well as the development of solutions and recommendations for working with personal sensitive research data.

The two subsequent years could be devoted to developing resources and solutions for the remaining problems and for critical evaluation of the project and its effect on data management practice at the faculty. This approach should provide the faculty with enough resources and information to decide on the best strategy for Data Stewardship beyond December 2020.

This data reference standard is part of a suite that provides a standard list of values to categorize data on person(s). The list reflects the classifications of sex assigned at birth and is designed to provide common data variables of the reported sex at birth, typically assigned based on a person’s reproductive system and other physical characteristics. This data reference standard is to be used by exception and read in conjunction with Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices and the Disaggregated Data Action Plan. This list of values is intended to standardize the way sex assigned at birth classifications are coded in datasets to enable data interoperability and improve data quality. The numbering system is a one-digit code. The appendix lists a data reference table that includes the one-digit codes for designating sex assigned at birth. Not included in this data reference standard is the lived or current sex of person(s). This data reference standard will be reviewed as required by the data reference steward in consultation with the data reference standard custodian. For support or advice on the measurement of “sex at birth of person” or related data variables, contact statcan.csds-cnsd.statcan@statcan.gc.ca.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward.

This feature class is part of the Cadastral National Spatial Data Infrastructure (NSDI) CADNSDI publication data set for rectangular and non-rectangular Public Land Survey System (PLSS) data set. The metadata description in the Cadastral Reference System Feature Data Set more fully describes the entire data set. This is a graphic representation of the data stewards for the Public Land Survey System (PLSS). For BLM data sets the the data steward is identifed at the township level or smaller area The Data Steward is agency that will be responsible for updates of the PLSS. In the shared environment of the Natioanl Spatial Data Infrastructure (NSDI) the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. Any questions about data content should be directed to the data steward.

This dataset consists of one spreadsheet, which shows the survival, number of polyps, size, Symbiodinium quantity and photosynthetic efficiency (Fv/Fm) of up to four-month-old Acropora millepora coral recruits while being exposed to three different climate scenarios resembling current climate conditions and conditions expected by mid and end of the century. Coral recruit resilience towards one-month-long light attenuation with five intensities was tested by exposing the recruits either one (experiment 1) or two months (experiment 2) following settlement. Additional tabs show temperature and pCO2 measured throughout the experiment. The experiment had 45 tanks made up from 15 climate (3) - light (5) combinations with 3-times replication. The temperature and pCO2 corresponding to the water going into the main lines feeding the 15 tanks in each climate combination were logged and are available in the dataset. The study was conducted at the National Sea Simulator.

The aim of this study was to 1) identify the survival of coral recruits under simultaneous exposure to climate stress (temperature and pCO2) and light attenuation and 2) identify survival mechanisms (i.e., number of polyps, Symbiodinium quantities, photosynthetic efficiency).

The climate scenarios (average of logged conditions) tested were: - Current: temperature: 28.46 deg C, pCO2: 428 ppm - Medium: temperature: 28.95 deg C, pCO2: 692 ppm - High: temperature: 29.56 deg C, pCO2: 985 ppm

The following light levels were tested for each of the climate scenarios : Maximum day time PAR: 3, 15, 31, 62, 124 (umol photons m-2 s-1) and matching Daily Light Integral of 0.1, 0.5, 1, 2, 4 (mol photons m-2 d-1).

This data will inform the development of water-quality management guidelines, a key aim of NESP project 5.2. The full research report can be found at:

Brunner CA, Ricardo GF, Uthicke S, Negri AP, Hoogenboom MO. 2022. Effects of climate change and light limitation on coral recruits. Marine Ecology Progress Series

Methods:

Coral recruits of Acropora millepora, a branching coral species abundant in shallow reefs on the Great Barrier Reef, were raised for 4 months in current and realistic medium and high climate scenarios (increased temperature and acidification), and were exposed to five environmentally relevant light attenuation levels typical of flood plumes and dredging operations. The one-month-long light attenuation events were simulated at different recruit ages: (1) one month following settlement, and (2) two months following settlement. After a four-week recovery phase, survival, polyp numbers, size, Symbiodinium quantities and the photosynthetic efficiency (Fv/Fm) were documented, and the data are presented here.

Specific details of the methodology may be found in: Brunner CA, Ricardo GF, Uthicke S, Negri AP, Hoogenboom MO. 2022. Effects of climate change and light limitation on coral recruits. Marine Ecology Progress Series

Limitations:

Note that the dataset only includes data for recruits that did not fuse with neighbouring recruits throughout the study. No data gathered where cells are empty. Mortality was observed even in the Current (control) climate treatment.

Format:

Excel Spreadsheet with 3 tables (Experiment: 16 columns x 12332 rows, Temperature: 5 columns x 26600 rows, pCO2: 5 rows x 14544 rows).

Data Dictionary:

• experiment: 1: one-month light attenuation one month after settlement, 2 one-month light attenuation two months after settlement
• climate: climate condition that each tank was subjected to: Current, Medium and High conditions.
• age_month: age in months following settlement climate = climate treatment based on manipulated temperature and pCO2, see "Temperatures" and "pCO2" tab for details
• light_PAR: light attenuation in photosynthetic active radiation (umol photons m-2 s-1) during the attenuation period. The PAR specified corresponds to the maximum light intensity during a day.
• light_DLI: light attenuation as Daily Light Integral (mol photons m-2 d-1) during the attenuation period. This corresponds to the total accumulated light received over the day. During the night light was 0. Between 6 am and 9 am light ramped up to the maximum value (light_PAR). It stayed at this level during the day and ramped down to zero from 3 pm to 6 pm.
• tank_ID: identification number of climate controllable aquarium
• disc_ID: identification number of discs where coral recruits settled on
• recruit_ID_on_disc: identification number of each recruit on each disc
• polyps_alive: number of alive polyps of each recruit, a dead recruit has 0 alive polyps. Polyps were counted so that we can could standardise the counts of Symbiodinium to Symbiodinium / polyp
• recruit_alive: 1: coral recruit is alive, 0: coral recruit is dead
• recruitarea_tota: total recruit size in mm² including dead and alive areas
• recruitarea_alive: alive recruit area in mm²
• recruitarea_bleached: bleached recruit area in mm²
• recruitarea_cca: recruit area in mm² overgrown with crustaceous corallin algae (CCA)
• symbionts_per_polyp: Symbiodinium cells per alive polyp
• FvFm: dark adapted photosynthetic efficiency

References:

Brunner CA, Ricardo GF, Uthicke S, Negri AP, Hoogenboom MO. 2022. Effects of climate change and light limitation on coral recruits. Marine Ecology Progress Series

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2019-2022-NESP-TWQ-5\5.2_Cumulative-impacts\data\2022-03-23-recruit-climate-light

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Graph and download economic data for Consumer Unit Characteristics: Percent Men Reference Persons by Housing Tenure: Home Owner (CXU980210LB1702M) from 1984 to 2023 about consumer unit, homeownership, males, percent, personal, housing, and USA.

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Additional file 2.. Complete challenge-solution matrix.

NOTE: This dataset is an older dataset that we have removed from the SGID and 'shelved' in ArcGIS Online. There may (or may not) be a newer vintage of this dataset in the SGID. This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward. Updated 10/15/2019

Graph and download economic data for Consumer Unit Characteristics: Age of Reference Person by Housing Tenure: Home Owner (CXU980020LB1702M) from 1984 to 2023 about consumer unit, age, homeownership, personal, housing, and USA.

This data reference standard provides a standard list of values to categorize data on person(s). The list reflects the classifications of gender and is designed to provide common data variables of the reported gender of person(s) or an individual’s personal and social gender identity. This data reference standard is to be read in conjunction with the Policy Direction to Modernize the Government of Canada’s Sex and Gender Information Practices and the Disaggregated Data Action Plan. This list of values is intended to standardize the way gender classifications are described in datasets to enable data interoperability and improve data quality. The appendix lists a data reference table that includes one-digit codes for designating gender. Not included in this data reference standard is an additional two-digit code for further classification. This data reference standard will be reviewed as required by the data reference steward in consultation with the data reference standard custodian. For support or advice on the measurement of “gender of person” or related data variables, contact statcan.csds-cnsd.statcan@statcan.gc.ca

Introduction This reference data provides a standard list of values for all Canadian provinces and territories. The list reflects Canada’s 13 major political units. There are many coding systems for Canadian provinces and territories. The data standard shows the relationships among the recommended code and other common codes. Purpose This list is intended to standardize the way Canadian provinces and territories are described in datasets to enable data interoperability and improve data quality. Not included in this standard are previous names, abbreviations and codes for provinces and territories. When changes occur in the future, version history will be maintained. Applicability Use of the codes within the “Alpha Code” column is recommended when sharing data within the federal government or publishing data to the Open Government Portal. This alpha code was chosen for three reasons: 1. it is comprehensible for users 2. it is closely aligned with the ISO 3166-2 code for subdivision and is identical to the Canada Post abbreviation 3. it has already been adopted by a number of federal departments The Alpha Code exactly matches the set of codes created and managed by Canada Post. If Canada Post changes its codes, the Government of Canada will review and separately approve any changes to this reference standard. If it is necessary to use a numerical code in a data system, then the numerical code created by Statistics Canada is included in the table. Roles and responsibilities Data Standard Stewards Statistics Canada Statistical Geomatics Centre, Analytical Studies, Methodology and Statistical Infrastructure Field Natural Resources Canada Geographical Names Board of Canada Secretariat Data Standard Custodian Treasury Board of Canada Secretariat Office of the Chief Information Officer, Data and Digital Policy Sector Recommended Review Period The reference data standard will be reviewed as required. The expected frequency of change is low.

Graph and download economic data for Consumer Unit Characteristics: Percent Women Reference Persons by Housing Tenure: Home Owner (CXU980220LB1702M) from 1984 to 2023 about consumer unit, homeownership, females, percent, personal, housing, and USA.