Radovan Kavický: Open Data @ Towns & Municipalities (Smart Cities, DataViz & Urban Data Science)
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Open Data @ Towns & Municipalities (Smart Cities, DataViz & Urban Data Science), 30. 3. 2017 (Brněnské Pyvo, Sklípek kiwi.com, Hlinky 40/102, Brno), Radovan Kavicky, GapData Institute (GDI), https://pyvo.cz/brno-pyvo/2017-03/ https://www.facebook.com/events/1820650268256801/ --------------------- Brněnské Pyvo – Open Data Sraz se konal ve čtvrtek 30. března 2017 v 19:00. Sklípek kiwi.com, Hlinky 40/102 V březnu si povíme o otevřených datech, abychom byli připraveni: město Brno v rámci iniciativy Otevřená města plánuje spoustu informací uvolnit. Přijďte včas – přednášek je hodně, tak tentokrát začneme hned po sedmé hodině. Přednášky Otevřená data o Brnu Jiří Ulip Jiří Ulip nám poví něco o datech, které město Brno plánuje zveřejnit v rámci iniciativy Otevřená města. Histogramy z otevřených dat s knihovnou physt Jan Pipek Open Data + Pandas == ♥ Eduard Trott O otevřených městech Radovan Kavický Kiwi.com internships Jan Bleha Jan Bleha představí nový program remote stáží pro Kiwi.com BroadApi.com - Otevírání dříve nedostupných dat Vlad Kahoun Data mají být ropou dneška. Proč je tedy ropy všude dost a užitečných dat jako šafránu? Místo Sklípek kiwi.com, Hlinky 40/102 Details V březnu si povíme o otevřených datech, abychom byli připraveni: město Brno v rámci iniciativy Otevřená města plánuje spoustu informací uvolnit. Přednášky: Otevřená data o Brnu -- Jiří Ulip Jiří Ulip nám poví něco o datech, které město Brno plánuje zveřejnit v rámci iniciativy Otevřená města. O otevřených městech -- Radovan Kavický
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Radovan Kavický: Open Data @ Towns & Municipalities (Smart Cities, DataViz & Urban Data Science)
- 1. Open Data @ Towns & Municipalities (Smart Cities, DataViz & Urban Data Science) Radovan Kavický, GapData Institute30. 3. 2017 (Brněnské Pyvo, Sklípek kiwi.com; #Pyvo #Brno)
- 2. GapData Institute (GDI) Economic Research & Public Policy & Data Science think-tank (data-tank) Data. Think. Change. GapData Institute (GDI) is a non-profit nonpartisan research institution harnessing power of data & wisdom of economics for public good. Transparent account (from day #1; SK7383300000002200933920 https://www.fio.sk/ib2/transparent?a=2200933920) Partnership (openness, transparency) 1/8 Open Data @ Towns & Municipalities
- 3. Open Data & Python (where & why to start?) 2/8 Why to open data? - transparency - already paid - modern & new services - not enough data about Open Data Open API LOD (Linked Open Data) Smart City - vision Python/Jupyter + Bokeh (dataviz) AI/Machine & Deep Learning Open Data @ Towns & Municipalities
- 4. How many “Open Data” are there? 3/8 Open Data @ Towns & Municipalities Source: https://www.opendatasoft.com/a-comprehensive-list-of-all-open-data-portals-around-the-world/
- 5. Open Budgets, Transparency & Participation 4/8 OBI 2015 Citizen Budget Citizen Participation Control (local government) Price & service Substantial changes Open Data Visualizations (taxes & spendings) Wikibudgets.org & OpenSpending.org Supervisor (MF ČR) Open Data @ Towns & Municipalities
- 6. Python, R & Tableau (Data Science Toolbox) 5/8 Rodeo (IDE for Python & R) Wing + VIM (IDE for Python) R-Studio (IDE for R) dplyr (data manipulation, dataframe) D3 (DataViz, JavaScript) DataWrangler (wrangle data took) Pandas +geopandas Open Data @ Towns & Municipalities
- 7. Why smart cities… why not? 6/8 Open Data @ Towns & Municipalities
- 8. Data Science (Urban) + Data Visualization 7/8 OSMnx - https://github.com/gboeing/osmnx CARTO.com (maps + predictions) QGIS.org (Open Source GIS) Tableau Desktop 10.2 (interactive DataViz) OpenStreetMap.org Openlayers.org Leaflet (JS, R + maps +ggmap) Mapbox (3D maps/C++, OpenGL) Google fusion tables Open Data @ Towns & Municipalities
- 9. Other activities (GapData Institute) PyData Bratislava, R <- Slovakia, skczTUG Open Data (only the 1st necessary step) Python, R, Tableau community activities Data Visualization (Interactive DataViz Tools) Economic Reforms (any area) Transparent account (from day #1; SK7383300000002200933920 https://www.fio.sk/ib2/transparent?a=2200933920) PyCon CZ 2017 (9th-11th of June 2017, DUP36) 8/8 Open Data @ Towns & Municipalities
- 10. Thank you for your attention Contact: Radovan Kavicky radovan.kavicky@gapdata.org +420 777 595 262 (CZ) +421 949 716 214 (SK) http://www.linkedin.com/in/radovankavicky https://gapdata.slack.com/messages/py-data/ https://github.com/radovankavicky https://github.com/GapData/PyDataBratislava @radovankavicky, @PyDataBA, @GapDataInst #Pyvo #Brno In case you have any question, feel free to ask.
Editor's Notes
- (30s.) 3 parts: About our activities Open Data, Python, DataViz, Tableau, Urban Data Science, Future activites
- (1-2 min.) Basic information about GapData Institute Economic Research & Public Policy & Data Science think-tank (data-tank) Data. Think. Change. GapData Institute (GDI) is a non-profit nonpartisan research institution harnessing power of data & wisdom of economics for public good. Transparent account (from day #1; SK7383300000002200933920 https://www.fio.sk/ib2/transparent?a=2200933920) Partnership (openness, transparency)
- (1-2min.) Open data is data that can be freely used, shared and built-on by anyone, anywhere, for any purpose. This is the summary of the full Open Definition which the Open Knowledge Foundation created in 2005 to provide both a succinct explanation and a detailed definition of open data. As the open data movement grows, and even more governments and organisations sign up to open data, it becomes ever more important that there is a clear and agreed definition for what “open data” means if we are to realise the full benefits of openness, and avoid the risks of creating incompatibility between projects and splintering the community. Open can apply to information from any source and about any topic. Anyone can release their data under an open licence for free use by and benefit to the public. Although we may think mostly about government and public sector bodies releasing public information such as budgets or maps, or researchers sharing their results data and publications, any organisation can open information (corporations, universities, NGOs, startups, charities, community groups and individuals). There are a few key aspects of open which the Open Definition explains in detail. Open Data is useable by anyone, regardless of who they are, where they are, or what they want to do with the data; there must be no restriction on who can use it, and commercial use is fine too. Open data must be available in bulk (so it’s easy to work with) and it should be available free of charge, or at least at no more than a reasonable reproduction cost. The information should be digital, preferably available by downloading through the internet, and easily processed by a computer too (otherwise users can’t fully exploit the power of data – that it can be combined together to create new insights). Open Data must permit people to use it, re-use it, and redistribute it, including intermixing with other datasets and distributing the results. The Open Definition generally doesn’t allow conditions to be placed on how people can use Open Data, but it does permit a data provider to require that data users credit them in some appropriate way, make it clear if the data has been changed, or that any new datasets created using their data are also shared as open data. There are 3 important principles behind this definition of open, which are why Open Data is so powerful: Availability and Access: that people can get the data Re-use and Redistribution: that people can reuse and share the data Universal Participation: that anyone can use the data
- (1-2 min.) The rate of urban migration around the world is rising at an alarming rate. Experts estimate that 70 percent of the world’s population (more than six billion people!) will reside in urban areas by 2050. In response, government officials are investing in data sharing technologies to discover ways to provide public services more efficiently. This form of city planning has invariably been described as “smart”, “intelligent”, “responsive”, “resilient”, and, more recent, “senseable”. But how do these initiatives use open data to address the concerns of residents? In answering this question we discovered projects whose originality left us speechless and dedication to social justice inspired. We’ve assembled the list below both to recognize these accomplishments and promote more work with open data!
- (1-2min.) Budget transparency is particularly important in local government. Globalization has given rise to a greater recognition of the role of local government, demonstrated by a widespread resort to the subsidiary principle and a growing municipal participation in public policies. The strengthening of local governments along with substantial changes in the way those governments operate has kindled the interest of stakeholders in knowing what governments do, how and at what price. Fairly often, international organizations involved in promoting budget transparency consider local governments to be ideal for testing new systems or arrangements before they are implemented at higher levels.
- (1-2min.) Rodeo (IDE for Python & R) Wing + VIM (IDE for Python) R-Studio (IDE for R) dplyr (data manipulation, dataframe) DataWrangler (wrangle data took) IPython/Project Jupyter (Julia, Python + R) Jupyter notebook (.ipynb rendering via web browser) +nbviewer D3 (DataViz, JavaScript) pandas (data manipulation, analysis) pandas datareader (data import) pandas-ply (functional data manipulation)
- (1-2min.) So how will &apos;smart&apos; cities help us deal with tackling climate change and growth at the same time? There are 5 key areas emerging for &apos;smart&apos; services that enable a sustainable, low carbon city. 1. Monitoring and managing the &quot;footprint&quot; of the city for decision-makers2. Connected mobility solutions to enable modal shift, and electric vehicles3. Distributed and community energy solutions4. Smarter buildings that are transparent about energy consumption, use and generation5. Smart energy, water and waste management Behind these key areas are technology solutions like &apos;smart meters&apos; and the &apos;smart grid&apos;, which have been widely covered in the news. But how much more efficient could we really make our lifestyles, today? Could we turn down the office heating without sacrificing comfort? Could we work flexibly, modify our travel patterns, and still achieve the business and mobility services we have come to rely on?
- (2 min.) OSMnx Python for street networks Retrieve, construct, analyze, and visualize street networks from OpenStreetMap: full overview. OSMnx is a Python 2+3 package that lets you download spatial geometries and construct, project, visualize, and analyze street networks from OpenStreetMap&apos;s APIs. Users can download and construct walkable, drivable, or bikable urban networks with a single line of Python code, and then easily analyze and visualize them:
- (1-2 min.) PyData Bratislava, R &lt;- Slovakia, skczTUG Open Data (only the 1st necessary step) Python, R, Tableau community activities Economic Research (studies, papers, publications) Quantitative & Qualitative Analyses (Data/center of it all) Data Visualization (Interactive DataViz Tools) Public Policy (Public Budget, Public Finance) Economic Reforms (any area) PyCon CZ 2017 (9th-11th of June 2017, DUP36)
- Contact: Radovan Kavicky radovan.kavicky@gapdata.org +420 777 595 262 (CZ) +421 949 716 214 (SK) http://www.linkedin.com/in/radovankavicky https://gapdata.slack.com/messages/py-data/ https://github.com/radovankavicky https://github.com/GapData/PyDataBratislava @radovankavicky, @PyDataBA, @GapDataInst