📍 Overview

The Drug Product Database (DPD) is the official registry of all pharmaceutical products that are authorized for sale in Canada. Maintained by Health Canada, this dataset provides comprehensive information on drugs that are currently approved, previously approved (but discontinued or withdrawn), or under specific regulatory conditions.

This dataset is a crucial resource for researchers, healthcare professionals, regulators, and data scientists working in public health, pharmacovigilance, healthcare analytics, and regulatory intelligence.

💊 About the Dataset

The Drug Product Database (DPD) contains details about:

• Active and previously authorized human and veterinary drug products sold in Canada
• Product names, dosage forms, routes of administration, and strengths
• Regulatory status, Drug Identification Number (DIN), and approval information
• Companies responsible for manufacturing and marketing
• Therapeutic classifications and pharmaceutical standards

Each record represents a single drug product as listed in Health Canada’s public DPD.

📂 Dataset Contents

📊 Example Use Cases

Here are some ideas for how you can use this dataset:

• 🩺 Drug trend analysis: Track how the number of authorized drug products changes over time.
• 🧪 Therapeutic class exploration: Explore the most common therapeutic categories or emerging treatment areas.
• 🧬 Active ingredient analysis: Identify commonly used active ingredients and their distribution across products.
• 🏥 Regulatory lifecycle studies: Study product approvals, discontinuations, and regulatory trends.
• 🤖 ML projects: Build models to predict drug approval likelihood, classify therapeutic categories, or cluster similar drugs.

📈 Potential Visualizations

• Top 10 companies by number of authorized drugs
• Distribution of dosage forms and routes of administration
• Time-series visualization of drug approvals per year
• Network graphs linking active ingredients to therapeutic classes
• Sankey diagrams of status transitions (e.g., Approved → Marketed → Discontinued)

🧠 Why This Dataset Matters

Drug regulation and market authorization are key aspects of public health. This dataset enables:

• Transparency in regulatory processes
• Data-driven insights into Canada’s pharmaceutical landscape
• Academic research on drug safety, market dynamics, and healthcare policy
• Industry intelligence for pharmaceutical R&a...

This dataset contains complete product information for all approved, marketed, canceled and dormant products for human, veterinary, disinfectant and radiopharmaceutical use in the Canadian Drug Product Database (DPD) as of September 1, 2017. Before drug products are authorized for sale in Canada, Health Canada reviews them to assess the safety, efficacy, and quality. Drug products include prescription and non-prescription pharmaceuticals, disinfectants and sanitizers with disinfectant claims.

The Canadian Drug Product Database (DPD) contains product specific information on drugs approved for use in Canada, and includes human pharmaceutical and biological drugs, veterinary drugs and disinfectant products. This information includes 'brand name', 'route of administration' and a Canadian 'Drug Identification Number' (DIN).

This dataset contains complete active ingredient information for all approved, marketed, canceled and dormant products for human, veterinary, disinfectant and radiopharmaceutical use in the Canadian Drug Product Database (DPD) as of September 1, 2017. Before drug products are authorized for sale, Health Canada reviews them to assess their safety, efficacy, and quality. Drug products include prescription and non-prescription pharmaceuticals, disinfectants and sanitizers with disinfectant claims.

The Drug Product Database (DPD) system captures information on Canadian human, veterinary and disinfectant products approved for use by Health Canada. To facilitate the use of the drug product data, multiple Drug Product files are available. Users can access the complete data set through the “Drug Product” file. Subsets of the data can be accessed in the “Drug Product By …” files. The data in these files are filtered based on the current drug product status. For example, only drug product data for Approved products will be found in the “Drug Product By Approved Status” file.

Please note that you cannot see the date fields on this page due to a technical issue. To see the Report Date and Date Closed, please access the via ArcGIS Online, or download the dataset from this page.This dataset reflects all citizen complaints received by the Detroit Police Department (DPD) and the Board of Police Commissioners from January 1, 2012 to the present. There is a 28-day delay between when a new complaint is filed and when it is posted to the Open Data Portal. The data are provided by the Office of the Chief Investigator (OCI), under the direction of the Board of Police Commissioners (BOPC). The OCI receives, investigates, and resolves complaints regarding non-criminal allegations of misconduct against the DPD and its personnel. Each case is allotted 90 days to complete an investigation. If OCI finds that a complaint is criminal in nature, it is transferred to DPD for further investigated.This dataset contains information about the nature of individual complaints, demographics for both the citizen filing the complaint and the officer against which the complaint is filed, and the resulting finding from the OCI investigation. In order to protect the privacy of both the officer and the citizen filing the complaint, no personally identifiable information is displayed. Each row in the dataset represents an allegation. A single complaint may have one or more allegations and is therefore represented by one or more rows. Allegations associated with the same complaint share same BPC Case Numbers and Citizen Complaint Report Numbers.Allegation Type Definitions:Arrest - Complaint associated with an improper or unjustified restraint of a person's liberty. Includes formal arrests and other types of detention.Demeanor - The bearing, gesture, language, or other action of a DPD staff member alleged to be offensive, of doubtful social propriety, or giving the appearance of conflict of interest, misuse of influence, or lack of jurisdiction or authority.Entry - Entry into a building or onto property improper and/or excessive force used against property to gain entry.Force - Use or threatened use of force against a person.Harassment - When an officer misuses their authority to threaten, intimidate, or coerce a person based on a factor such as race, attire, sex, or age.Procedure - Complaint regarding other actions in violation of DPD rules, regulations, procedures or policies, or the Law Enforcement Code of Ethics.Property - Complaint of property lost or damaged while in police custody or confiscated through police action.Search - Search of a person or a person's property was improper, violated established police procedure, or was unjustified.Service - Complaint regarding the lack, tardiness or inadequacy of police service.Findings Definitions:Unfounded - The investigation revealed no evidence to support that the incident complained of actually occurred.Sustained - A preponderance of the evidence shows that the alleged conduct did occur and the actions of the officer violated DPD policies, procedures, or training.Exonerated - A preponderance of the evidence shows that the alleged conduct did occur but did not violate DPD policies, procedures or training.Administrative Closure - Dispositions for complaints that: duplicates, referred to an outside agency, made against an officer or employee who is no longer employed by DPD, the alleged conduct does not violate the law or DPD policy, and lack sufficient detail of the officers involved or insufficient details within the complaint.No Charge - When evidence concludes that the allegation did not meet the threshold to dispense disciplinary action.Inconclusive - When there is insufficient evidence to decide whether the alleged misconduct occurred.Void - When the investigation is halted due to but not limited to a retracted complaint, duplicate submission, or a submission in error.Should you have questions about this dataset, you may contact the Office of the Chief Investigator at (313) 596-2499 or go to their website.A visualization of DPD Citizen Complaints is available from the open data Analytics Hub.

The Drug Product Database (DPD) system captures information on Canadian human, veterinary and disinfectant products approved for use by Health Canada. To facilitate the use of the drug product data, multiple Drug Product files are available. Users can access the complete data set through the “Drug Product” file. Subsets of the data can be accessed in the “Drug Product By …” files. The data in these files are filtered based on the current drug product status. For example, only drug product data for Approved products will be found in the “Drug Product By Approved Status” file.

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Before a drug is authorized for sale in Canada, it must be issued a DIN in accordance with the Food and Drug Regulations. Also in accordance with the Food and Drug Regulations, a manufacturer of a drug must annually, before October 1, notify Health Canada that the drug is still on the market and that all the information previously provided pertaining to the drug is correct. The Health Products and Food Branch (HPFB) commits to service delivery standard of 120 calendar days, from the receipt of annual notification, to update the Drug Product Database (DPD).

The Canadian Clinical Drug Dataset is a drug terminology and coding system designed to allow the interchange of standardized drug and medical device information between diverse digital health systems. Some use cases include electronic prescribing, electronic medical records, medication reconciliation and analytics. It also provides for the classification and identification of defined groups of medications (called special groupings), such as narcotic and controlled drugs. It has the capacity to be used by knowledge-based vendors, clinicians, researchers, statistical users, government agencies, healthcare organisations and consumers. The data source for the CCDD is the Drug Product Database (DPD) which contains information on drugs approved by Health Canada. However, the data is modeled differently following the CCDD Editorial Guidelines which take into consideration international terminology standards. For example, DPD uses the dosage form, “tablet (delayed-release)”, whereas CCDD uses the equivalent term “gastro-resistant tablet.” The Canadian Clinical Drug Data Set does not replace the Health Canada Drug Product Database (DPD) but is published in addition to it. The scope of health products included in CCDD is limited to those classified as human in DPD (veterinary, radiopharmaceutical and disinfectant products are out of scope). Some exclusions apply within the human class but are subject to periodic review: For a full list of exclusions, please see the Scope section in the CCDD Editorial Guidelines. In addition, a limited number of medical devices that are commonly prescribed and dispensed at a community pharmacy are included. This data set was developed in collaboration with Canada Health Infoway and is also available in their Terminology Gateway at https://tgateway.infoway-inforoute.ca/ccdd.html (Free login required)

This data represents calls for police services, which are separated by year due to file size, and updated annually. Historical data is available back to 2006. Available fields include:Event Number – Unique numerical identifier of the call for service.Case Number – If an incident report was written, this is the file number, which can be joined to the incidents and arrests datasets.Call Date – Date the call for service was generated.Call Time – Time the call for service was generated.Source – How the call was generated from the public, or self-initiated by an officer.Priority – The priority level of the call response, with ‘P’ being the highest, followed in order numerically.Nature – The description of the call for service.Address – The block number and street or intersection of the call for service.X – Mapping coordinate of the call for service, projected as NC State Plane (feet).Y – Mapping coordinate of the call for service, projected as NC State Plane (feet).District – The patrol district where the call for service was located.Beat – The patrol beat where the call for service was located, which is a sub-division of the district.Tract – The census tract where the incident occurred, based on 2010 census data.Disposition – How the call for service was closed.Cancelled – Whether the call for service was cancelled prior to officer arrival.

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.

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This data represents incident reports written to capture incidents of crime that are reported to law enforcement, based on the FBI’s UCR Program Data Collections for the National Incident-Based Reporting System (NIBRS). Historical data is available back to 10/1/2018, before which the agency was using the Summary Reporting System (SRS). While the data collected is similar, it is not comparable across reporting systems. Available fields include:Case Number – Unique numerical identifier of the incident, which can be joined to the calls for service and arrests datasets.Report Date – The date when the crime occurred, or when it was reported to police, if the date of occurrence is not known.Report Time – The time when the crime occurred, or when it was reported to police, if the time of occurrence is not known.Status – The status of the case at the time the dataset was last updated.Sequence – All offenses per incident are reported in NIBRS. This is the sequence by order of severity.ATT/COM – Designation of whether the crime was attempted or committed.UCR Code – The FBI’s alphanumeric identifier for the type of crime being reported.Address – The block number and street or intersection of the incident.X – Mapping coordinate of the incident, projected as NC State Plane (feet).Y – Mapping coordinate of the incident, projected as NC State Plane (feet).District – The patrol district where the incident occurred.Beat – The patrol beat where the incident occurred, which is a sub-division of the district.Premise – The type of location where the incident took place.Weapon – The primary weapon used in violent crimes.Tract – The census tract where the incident occurred, based on 2010 census data.This dataset is updated annually. However, other resources for incident data are available and updated nightly, including the DPD Crime dataset on the City and County of Durham Open Data Portal and Community Crime Map web site by LexisNexis.

This data represents arrests of adults made by law enforcement, based on the FBI’s UCR Program Data Collections for the National Incident-Based Reporting System (NIBRS). Historical data is available back to 10/1/2018, before which the agency was using the Summary Reporting System (SRS). While the data collected is similar, it is not comparable across reporting systems. Note: the age of adult criminal responsibility was raised from 16 to 18 years old on December 1, 2019. This dataset is updated annually. Available fields include:Arrest Number – Unique identifier of the arrest.Case Number – Unique numerical identifier of the case, which can be joined to the calls for service and incident datasets.Name ID – Unique numerical identifier of the person arrested.Race – The race of the person arrested.Ethnicity – The ethnicity of the person arrested.Sex – The gender of the person arrested.Age – The age of the person arrested.Arrest Date – The date of the arrest.Arrest Time – The time of the arrest.Arrest Type – The type of arrest. Criminal summons and citations are non-custodial.Sequence – This is the sequence by order of severity based on the FBI’s UCR hierarchy, not North Carolina General Statutes.UCR Code – The FBI’s alphanumeric identifier for the type of crime committed.Statute – The codified charge, usually by either the North Carolina General Statute or City Ordinance.Description – The description of the codified charge in the statute.F/M – Designation of whether the crime was a felony or misdemeanor.Counts – A multiplier of the number of counts for the same crime charged.Location of Arrest – The block number and street or intersection of the arrest.X – Mapping coordinate of the arrest, projected as NC State Plane (feet).Y – Mapping coordinate of the arrest, projected as NC State Plane (feet).District – The patrol district where the arrest occurred.Beat – The patrol beat where the arrest occurred, which is a sub-division of the district.Tract – The census tract where the incident occurred, based on 2010 census data.Individual arrest reports can be accessed and printed on the Durham Police Department’s Police to Citizen (P2C) web site, which are available back to 10/1/2018.

RMS Crime Incident data complies with Michigan Incident Crime Reporting (MICR) standards. More information about MICR standards is available via the MICR Website. The Manual and Arrest Charge Code Card may be especially helpful. There may be small differences between RMS Crime Incident data shared here and data shared through MICR given data presented here is updated here more frequently which results in a difference in a cadence of status updates. Additionally, this dataset includes crime incidents that following an investigation are coded with a case status of ‘Unfounded’. In most cases, this means that the incident occurred outside the jurisdiction of DPD or otherwise was reported in error. The State of Michigan, through the MICR program, reports data to the National Incident-Based Reporting System (NIBRS).

Yearly Datasets for RMS Crime Incidents have been added to the ODP. This is to improve the user's experience in handling the large file size of the records in the comprehensive dataset. You may download each year separately, which significantly reduces the size and records for each file. In addition to the past years, we have also included a year-to-date dataset. This captures all RMS Crime Incidents from January 1, 2025, to present.

Should you have questions about this dataset, you may contact the Commanding Officer of the Detroit Police Department's Crime Data Analytics at 313-596-2250 or CrimeIntelligenceBureau@detroitmi.gov.

This dataset contains DPD initiated CAD (Computer Aided Dispatch) records in the City of Detroit since September 20, 2016. This compliments the Police Serviced 911 Calls dataset that is an internally generated equivalent to events reported by civilians that lead to a police response. Examples of records can include activities in which a law enforcement unit or officer initiates contact with the public. This can be to resolve, correct, or assist in a particular situation like helping a motorist, interviewing a witness, conducting a traffic stop, and engaging in foot pursuit. Each row in the dataset represents a DPD initiated record. These records detail when the call was entered, its nature, assigned priority level and DPD responding precinct/unit. When applicable, it also includes dispatch time, travel time, and total response times. Locations of the officer-initiated calls are reported based on the nearest intersection to protect the privacy of individuals. Records in this dataset that are of a more general nature may not have an associated location. Some records in the dataset with a Code Description of “Start of Shift Information” serve as routine informational purposes within DPD. Two other values that appear in the Code Description field frequently are Special Attention and Bus Boarding. Explanations of these values can be seen below. “Special Attention” records may be created for several reasons. Examples include check-ins with Project Green Light (PGL) partners, response to citizen requests such as people request notifying police when they are going out of town, wellness checks, when there has been a series of break-ins or other crimes in an area, or other concerns that prompt DPD to pay special attention to a location. Records may also be initiated by DPD for purposes related to the community. "Bus Boarding" records are entered into the system when the Transit Division of DPD boards a DDOT bus, as part of routine responsibilities. Typically, the officer’s partner trails the bus in their vehicle and picks up the other officer when the ride is over. Should you have questions about this dataset, you may contact the Commanding Officer of the Detroit Police Department's Crime Data Analytics at 313-596-2250 or DPDinformatics@detroitmi.gov. A DPD webpage provides recommendations for reporting different types of crime.

This data layer references data from a high-resolution tree canopy change-detection layer for Seattle, Washington. Tree canopy change was mapped by using remotely sensed data from two time periods (2016 and 2021). Tree canopy was assigned to three classes: 1) no change, 2) gain, and 3) loss. No change represents tree canopy that remained the same from one time period to the next. Gain represents tree canopy that increased or was newly added, from one time period to the next. Loss represents the tree canopy that was removed from one time period to the next. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. Direct comparison was possible because land-cover maps from both time periods were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.University of Vermont Spatial Analysis LaboratoryThis dataset consists of City of Seattle Council District areas as they existed in the first comparison year (2016) which cover the following tree canopy categories:Existing tree canopy percentPossible tree canopy - vegetation percentRelative percent changeAbsolute percent changeFor more information, please see the 2021 Tree Canopy Assessment.