TC3.2 - Accessing and using Developer Dashboards

Test Case Title	TC3.2 - Accessing and using Developer Dashboards
Goal	I can: Access to city data on their time line, on historical large data storage in fast manner. Use multiple devices of different kind to access at the dashboards without installation. See the real-time data, and data  H24/7 with automated update for each widget. Monitor the status via different views, graphs and maps
Prerequisites	Using a PC or Mobile with a web browser. All the data arriving in the platform are collected into a noSQL storage and indexed in real-time. Thus they are accessible in the Developer Dashboard for drill down and browsing according to different aspects. The following functionalities are available only for specific Snap4city users with specific privileges.
Expected successful result	See the dashboard and play with them. The user can access to the dashboard and perform a number of action to drill down on data, on time, facet, kind of data, etc. The resulting combination of filter is a new dashboard/view that can be saved locally or on cloud (ProcessLoader, in the future) and shared with other colleagues, also via ProcessLoader.
Steps

 

Please note that some of the following links could be accessible only for registered users.

Snap4City Dashboards can show historical data and can filter and sort them dynamically:

• Historical and real time data can be shown from the Dashboard widget and from the Map towards the widget as single content, time trend compare, or just time trend, gauge, tachymeter, etc. This solution is based on Dashboard Builder.
• By faceted on the basis of several relations, timeline and geospace/maps: see tools such as AMMA, ResDash, DevDash. For example, once performed a selection in a widget/panel of AMMA, all the other views of the Dashboard re-filter the data shown dynamically. This is true for timeline, relations, OD map, Gelocation on Map.  This solution is developed in SOLR and shown on Banana.
• IOT data are automatically collected to form the historical values. They are accessible to be shown on DevDash which is based on SOLR index sharded, and allow you to search, drill on timeline/space and faceting, etc.

 

The visual exploration is possible according to different aspects: geo, text, tabular, relationships.  To this end, it is possible to find new relationships among data, in different domains, by different integrated tools:

• Developer Dashboard: to drill down on time, values via faceted, mixed, etc. The Developer Dashboard can directly compute: statistical values as average, maximum, minimum, etc. comparing visually multiple time trend and metrics, values, creating some heat map, etc.
• GEOspace: browse / search entities by starting from their geographic position and exploring relationships by using the map based tools as: ServiceMap,
  • Showing 3D distribution of data values via ServiceMap3D.
  • Then passing to the Developers Dashboard for further detailed analysis of the data along time trend. (not yet available)
• Entities and relationships: browse /search entities by starting from an entity and navigating among the relationships by using tool https://LOG.DISIT.ORG when the drill down on relationship is needed.

The general idea of Snap4City is to allow performing drill down to arrive at extracting data from different data stores: IOT, mobile, social media, historical, etc. and in any way to identify queries that can be executed automatically by some ETL or DataAnalytics script.

The data selected from the Developer Dashboard can be sent to Data Analytics tools to perform:

• statistical analysis looking for correlations, PCA, descriptive stats, etc.; performing some correlation and/or regression analysis by using R data, such as the example located into StatisticalAnalysisR.zip, including a file with data, the R programme. While the results can be accessed by https://www.snap4city.org/download/out-stat-analysis/ 
• predictive analysis, via number of tools; (available now for parking and Wi-Fi prediction as examples). To test click on the link to see a live example: https://www.km4city.org/webapp-new/?serviceuri=CarParkStazioneFirenzeS.M.N.
• anomaly detections, via a number tools.

This feature is implemented by starting from the Developer Dashboard, ServiceMap, and developing ETL  or Data Analytics processes in R, Java, Python, ETL, .., which in turn, can activate algorithms and tools for machine learning tools, clustering, kriging, etc. According to Snap4City, the scheduling of the Data Analytics can be performed by using DISCES tool, thus making them available in different contexts and scenarios looking for the identification of unexpected correlations as well as anomalies.

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1. Using the Developer Dashboard for data understating
   
   • Different types of Dashboards for developers are available in Snap4City. They are:
     • The dashboard to monitoring the network traffic (AMMA Tool):

1. 1.  

• The dashboard to analyse data (DevDash):

 

• The dashboard to analize the backoffice resources (ResDash)

In the following the Developer Dashboard is used as example.

• Access the DevDah by logging in the Snap4City tools with the credential of AreaManager (Developer). In the right column menu click on Management --> Data Analyzer: DevDash