:21-04:00 rehab_established string, null Timezone-aware date and time when rehab was established, expressed in as an ISO-8601 string. 2018-10-10T13:58:21-04:00 event_closed string, null Timezone-aware date and time the call was closed in the CAD, expressed in as an ISO-8601 string. 2018-10-10T13:58:21-04:00

Address Access these items through using the address prefix. For example: address.latitude . name type description example address_id string,null Local unique identifier assigned to this address. address_line1 string Street address for the incident location. 2600 BROOK RD battalion string,null The battalion of the incident location. 1 building_number string The building number. city string The city associated with the incident location. Richmond common_place_name string,null A commonplace name for the incident location. cross_street1 string The name of the first incident cross street. DUBOIS AVE cross_street2 string The name of the second incident cross street. EDGEHILL RD distance_from_fire_department number The distance from the fire department to the emergency. 2.1 elevation number Height in feet above sea level. first_due string The apparatus station which is expected to be the first unit to arrive at the scene. 14 floor

Changing the Time Window on Your Dashboard Your NFORS dashboard is dynamic with respect to time -- meaning you can filter your department data by any time window you would like. First, lets take a look at the top bar on your dashboard with a focus on the text highlighted in blue - This Month Note: When you first log into your dashboard, this text string could be different. When you click there, a drop down menu will appear allowing you select many different time filtering options: Quick , Relative , Absolute , Recent Quick: Using this option allows you to filter your time window on predetermined fixed intervals such as today, week, month, or year as some examples. It is important to note that This Month is different than Last 30 Days . The former will provide filtering based on calls that occurred only in this calendar month while the latter will show results

At present NFORS has two modules available to customers, the analytics suite and the exposure module. Very different data is collected by these two modules, but there are common lines along which they can be joined. The focus of this article will be on the NFORS analytics module. The nature of NFORS data A data feed from local or regional CAD providers The NFORS analytics module consists of incoming data feeds provided by local or regional CAD providers. These data feeds are parsed in order to map the incoming data to a common underlying schema, outlined in the data dictionary tab. This data is then presented to subscribing departments via a business intelligence-style dashboard and visualization interface. Data underlying NFORS is processed and stored as singleton documents adhering to a flexible schema. While there are a "core" of base fields that are "guaranteed," there are often additional fields

Weather Access weather items through using the weather prefix. For example: weather.currently.apparentTemperature . Weather items are drawn through the Dark Sky api. Please refer to their documentation (under "Data Point Object") for data field definitions. Note that the currently prefix refers to weather conditions nearest the timestamp of the incident, while the daily prefix refers to the weather conditions supplied for the day in question.

NFORS Performance Durations In your NFORS dashboards, you may see several different timestamps displayed for a particular incident or aggregated as a larger metric. Some departments calculate response time, event time, alarm handling or other metrics differently than others. To avoid confusion follows terminology and calculations set forth in NFPA 1710/1720 guidelines unless otherwise noted. Here is a list of the most commonly used durations, for all calculated durations, see the schemas. Alarm Answering The time interval that begins when the alarm is received at the communication center and ends when the alarm is acknowledged at the communication center. durations.alarm_answering = description.event_opened - description.psap_answer_time Alarm Processing The time interval from when the alarm is acknowledged at the communication center until response information begins to be transmitted via voice or electronic means to emergency response facilities (ERFs) or the emergency response units (ERUs). durations

NFORS Metrics On this page you will find the definitions of the common statisitical metrics presented on your respective dashboards. Mean Value The arithemetic mean value or more commonly called an 'average' is the central value of a set of points: the sum of the values divided by the number of values. 90th Percentile The 90th percentile is a measure that tells you the value for which 90% of the points are smaller and 10% of the data points are larger. Median The median value represents the value for which 50% of the points are smaller and 50% of the points are larger. In other words, th middle value. Percent Change The percent change represents the relative change compared to a baseline value. Percentile Ranks Percentile ranks show the percentage of observed values which are below a certain value. For example, you may have a performance goal of first

Unit Level Performance An analysis is performed on each unit within a department's response profile. The data can be filtered as a function of specific time intervals (i.e., last shift, last day, last week, last month, last quarter, or last year) to identify trends and assess performance. Incident Type Analysis Response frequency is assessed as relative for the selected time window for each unit. Response frequency is assessed as relative for the selected time window for each unit. The data is broken down into 5 subsets to describe the response from slow to typical to busy. The table below describes the ranges. Bin Range Response 1 0% -- 20% Slow 2 21% -- 40% Typical 3 41% -- 60% Typical 4 61% -- 80% Typical 5 81% -- 100% Busy As an example, in the graph on the left of the figure below, the 471 responses represents a slow number of responses

Have a question when using NFORS? You're not alone. Check out our FAQs to see if we have already addressed the issue. Q: Is there a way to create a ward specific visualization that includes the number of incidents for the ward, and category types for the ward? A: The ward data would be stored in the address.location.ward, or address.location.precinct_ward data sets. The address.location.ward is not currently populated, and would require a GIS service or shape file that we can perform an intersection on. Q: Is there a way to establish specific time filters so that the dashboard will display shift data? For example, if the shift is from 0700 to 0700, is there a way to only display that data? You can set an absolute time, but that doesn’t seem to cover it. The last 24hr is also available

Filtering Your Department Dashboard The default dashboard provides users with metrics based on department level performance. The dynamic nature of the NFORS dashboard allows users to parse the base response into subsets that allow for more granular assessments. For example, on any of the charts where units are explicitly called out, such as Call Volume by Unit and Call Type a user can filter the entire dashboard by unit by selecting the appropriate column. This particular graph, also applies a secondary filter, call type. In the example below, the portion of the E1 responses associated with EMS-1 was selected. Since multiple filters were selected, the user has the option of which ones to apply. In this case, the EMS-1 filter is deselected and only the E1 filter is applied. As the filter is applied, the entire dashboard will update, including the map of calls, heads up metrics

Apparatus The apparatus attribute is an array of units assigned to the incident. Each entry will have the following schema. name type description example car_id string Local unique identifier assigned to this apparatus, if present. 181241 distance number The number of miles this apparatus was from the incident location at dispatch, if present. 1.2 extended_data object Local data specific to this apparatus, including calculated durations such as turnout or travel time. first_due boolean Boolean indicating if the unit is first due as determined by earliest dispatch timestamp. In case of a tie, a unit is chosen 'at-random.' false in_first_due boolean Boolean indicating if the unit is responding within its assigned station area. false personnel array Personnel assigned to a particular apparatus response_priority string Apparatus specific priority identifier for this apparatus. emergent shift string The shift on this apparatus at the time

Click on Dashboard in the side navigation. Click on Create new dashboard button. Click the Add button. In the Add Panels dialogue box select from the list the visualizations you wish to add to your dashboard or click on the Add New Visualization button. Note: see separate page for creating a new visualization. After selecting the visualizations you want to add, click the X on the Add Panels dialogue box. Re-arrange the visualizations by hovering over the top bar of the tile and dragging it to the desired location. The box can be resized by dragging the bottom right corner. Do not forget to click Save at the top of the page to preserve your work.

Fire Department Access these items through using the fire_department prefix. For example: fire_department.fd_id . name type description example fd_id string The NFIRS FD ID for the Fire Department. This field is automatically calculated. 76000 firecares_id string FireCARES ID for the Fire Department. This field is automatically calculated. 93345 name string Name of the Fire Department. This field is automatically calculated. Richmond Fire and Emergency Services state string The state that the Fire Department is within. This field is automatically calculated. VA timezone string The timezone of this department. This field is automatically calculated. US/Eastern

Overview Here's an overview of the NFORS components to prep you: Dashboard A collection of related data visualizations. As filters are applied to a dashboard, the visualizations are automatically updated, allowing the user to compare how the current filter impacts various facets of the data. You can have many different dashboards, for example one for different challenges your department faces. Indices You will see the term "Index", or the plural indicies, a lot throughout our platform (especially in the Dashboard App). These are our internal data orangization mechanisms which hold your data. We currently have 3 seperate indices in which your data is stored. The incident index. This index contains one entry for each incident we receive. The apparatus index. This index contains one entry for each response we receive. The telemetry index. This index contains one entry for each AVL "ping" that we receive. Visualization A way

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Custom Filter Your Dashboard with Freeform Text The NFORS dashboard is built on top of a fully functional search engine. You can leverage the search bar at the top of your dashboard to create custom text filters on your data. The query you type in searches through the CAD notes attached to each call, and the returned results will be reflected in your updated dashboard.

Click on the Add a filter + button at the top of your dashboard. Type/select your filter from the list of drop-downs or based on a particular schema. Below, the _ address.first_due_ option was selected. The next phase of the filter applied the conditional statement - here it is filter on inclusive data. The last piece is to select which data to include as part of that statement. After the filter is created, remember to click Save .

NFORS Apparatus durations The Apparatus index includes a set of fields for each responding unit under apparatus_data.extended_data that provide calculations of durations based on that unit's status update timestamps during its response. The definitions of these durations are provided below. Note that a given response will only have those durations calculated for which there are timestamps available . For example, a unit that is canceled en route and thus has no arrival timestamp will not have its response time calculated, but will have its turnout time calculated. Turnout Turnout duration is the amount of time between the unit's dispatch and its en route acknowledgment apparatus_data.extended_data.turnout_duration = apparatus_data.unit_status.enroute - apparatus_data.unit_status.dispatched Travel Travel duration is the amount of time between the unit's en route acknowledgment and either its staging timestamp or arrival timestamp apparatus_data