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Making Local Data a First Class Citizen Through Streaming APIs

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Making Local Data a First Class Citizen Through Streaming APIs

Streamdata is investing time to understand what data is available at the local level, and how APIs and streaming technology can make this data more accessible.

· Integration Zone ·
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We've written a number of stories here on the Streamdata blog regarding city data. Showcasing the ways in which problems within cities get reported using 311 data, and how we understand traffic and transit using 511 data, as well as taking a look at emergency data with 911. We want to continue this work with more investment in understanding what data is available at the local level, and how APIs and streaming technology can make this data more accessible, and usable in dashboards that keep citizens informed, and possibly used to train machine learning models that help make sense of what is happening at the ground level. As part of our local data work, we will be looking at local businesses, real estate, churches, clubs and associations, events, activities, and other relevant information that impacts life at the local levels.

We want to understand how data is being generated, stored, and made available (or not) within our communities, and how APIs can be put to use and help make this local data more of a first-class citizen. Without APIs, this data is often locked up in existing systems, spreadsheets, and available on websites, but not able to be easily used in other mobile devices, and consumed by many different users at one time. Impacting life, and business at the local level in a negative way, unless we can help make things more machine-readable by default.

If data is locked up in existing systems, or only available as spreadsheets and HTML, it becomes much more difficult to work with. For us to easily integrate with, analyze, and potentially stream data more efficiently we need data available as simple JSON APIs. Once we have local data available via simple web APIs, we can then begin streaming to dashboards, training machine learning models, and developing topically based subscriptions that help end-users subscribe to only the streams of information they are interested in. Tuning out the noise they do not care about, and allowing them to tune into only the activities, events, services, and other things that positively impact our lives within our communities. Helping us put technology to better use for us, rather than allowing ourselves to be bombarded with useless information throughout the day.

We are processing a variety of local data sources currently, breaking them down into different buckets to better understand the types of data that exist at the local level. Then we are evaluating these data sources for their usability and what percentage is immediately usable within Streamdata.io vs. needing some work before we can put to work. As we process new cities or organize data into a new bucket we will be publishing the data sources to the API Gallery. Helping us better understand what is possible at the local level when it comes to streaming data, while also helping ensure that valuable data becomes more of a first-class citizen, right alongside other data sources like Twitter and Facebook who seem to dominate most conversations when we talk about how data impacts our daily lives.

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Topics:
apis ,integration ,local data ,public data ,open data ,streaming apis

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