Municipalities have been working to open data, and embracing the philosophy of openness and data sharing. But the task is complicated by many factors, not least of which is data integrity and quality. As a result, logistical hurdles are often slowing and frustrating the process of opening data.
A small handful of things can make it easier to open your organization's data with a minimum struggle. These require an initial effort to put in place, but after that, make it easier to store, manage, and use data, in addition to making it easier to share. Here, with brief explanations, are three top suggestions:
1. Provide metadata and contextual data
Metadata is data about data. It includes things like when and where the dataset was collected, and what precision can be expected or the scale of the data. Long strings of time-value pairs rapidly lose meaning. This is because, when someone new gets the data, or even when the original creator returns to it after some time, there's very little to indicate what the data is about, what context it was collected in, how collection occurred, etc. When the dataset's meaning is lost, it's essentially unusable. When that happens, all the work and effort that went into collecting, storing, managing and sharing the data is lost. Metadata and context vastly extend the longevity of your data, because the dataset can be taken up and understood by a new person, or after a long period of time. This extends the life of the dataset, and gets much more value from all the work that went into the data.
2. Make data model and data access method transparent
Data model is the structure of the data, including things like entities, their attributes and the relationships between them. Data access is the way that you retrieve specific pieces of information from the database, such as queries and API calls. When the data model is transparent, you know how the data is structured. When the data access is transparent, you also know how to get at the bits of data you need. Good data models also build in and inherently enforce including contextual and metadata. This ensures that the additional information about the data -- mentioned in #1 -- is present.
3. Make data from disparate systems interoperable
Data from different monitoring programs, or even completely different physical systems, can be interoperable, that is, they can be combined, when the data model and access are consistent and transparent. When systems are interoperable, it is possible to look at the links between different physical systems and the interactions between them. It provides another way to make sense of data and understand physical phenomena. It also makes data more useful, by making it possible to combine and recombine datasets.
4. (Bonus!) Use open standards to manage and store data
Open standards will typically accomplish 1-3, above. They provide transparency in both data model and data access protocol. Because of that, they also provide interoperability. Good standards will also include metadata and contextual data in the data model. Essentially, using open standards allows the data owner to take advantage of all three tips above!
The above are for building-in data integrity, structure, interoperability and reusability. It's still necessary to add privacy protection, such as aggregation, to some sensitive datasets. And of course, it's still necessary to plan for, and design in, data integrity in the data collection process. That having been said, data structure and integrity will go a long way toward easing the data opening and release process.
SensorUp is a data management company that specializes in managing data from the Internet of Things (IoT), also known as Smart Cities when applied in municipalities. Since we've been managing data at 5-Star Open Data readiness levels for a while, we thought we would share some tips about how to make it easier to share data so that it's usable and useful.
SensorUp is bringing a Smart Cities Kit that does all of the above to 10 municipalities across Canada this year. It's Canada's First Smart Cities Tour, and will place fleets of sensors (starting with air quality monitors) across the country. The kit is specifically designed to make it easy for municipalities to get started with a smart cities program that produces open standard smart cities data. All the data in SensorUp's Smart Cities Platform is ready to be released at the 5-Star Open Data level. All data coming in from the 1,500 sensors we're placing will include metadata and contextual data, will be stored in a transparent data model and accessed via transparent protocol. Because of that, the system will be interoperable with any other that chooses to adopt open standards. Partner municipalities will have access to raw data, as well as visualized, mapped, and analyzed data. Ready to go, smart cities open data!