A lot is being discussed in cities about the usage of “open data”. Also the data generated by AiREAS is expected to be open to all users. When dealing however with our work in the field of connecting health measurements with air quality data we enter a whole new area of ethics, delicate communication issues, privacy and quality responsibility.How do we deal with data in this complex challenge?

AiREAS is all about the co-creation of a “healthy city” through value driven multidisciplinary interaction. We use, treat and interpret data from many different sources to direct our actions, some generated by ourselves, some generated by others. We don’t just observe and report, we use data to trigger action. If we want to produce change we need to assure the quality, reliability and trustworthiness of our impulses because people will be making important decisions based on it. Those decisions can produce or not the desired results. What ever the issue, the data should never be a point of dispute yet a trustworthy stimulating partner.

New year fire works ultra fine dust peaks in Eindhoven

New year fire works ultra fine dust peaks in Eindhoven

The ILM (intelligent measurement system)

The data we obtain are based on specialized measurement techniques inside a so called Airbox, attached in a particular, scientifically influenced, way to a public light post. The measurement techniques and means themselves need to be verified against calibrated equipment of official institutes in order to be validated when placed out in the field. But even then the delicate routines can present failures that are difficult to detect. If we want to maximize the reliability we need to regularly calibrate the equipment. This can be done in various ways, for instance by bringing them all together in one place and check if they all measure the same, presenting very similar data under similar circumstances. If one Airbox shows a deviation there is likely to be some problem with it. On the other hand this effort introduces a gap in the measurement routines and data flow of the network. This needs to be administered to avoid disturbance of the averages and other analyses.

Another way to deal with checks is to rotate equipment in the field. If the measurement network remains unchanged all the time faulty measurements are considered “correct” because there is no control element. If the equipment is changed place with another than there should be an expected correlation between the measurements of both Airboxes in the same spot. If there is an inexplicable deviation we need to investigate to determine whether we are dealing with a fault or something else.

This is just an example of the complexity of am as high as possible reliable measurement infrastructure. Another issue is the communication platform that empties the buffer of data obtained in the field into a data collection database. If the communication routines fail then data can be stored in the buffer until the communication is reestablished. The real time feedback will be gone temporarily but the data not, unless the problem continues and the buffer starts overriding data. Then data will be lost which will compromise the completeness of time-stamps and potential analytic processes. Communication and single points of failure need hence to be determined with risk assessment that involves all partners. Especially when very big peak pollution events have been registered in the public space it is unacceptable to have data gaps in the semi-real time routines that combine with real time observations in the streets and neighborhoods.

The airboxes need to be trustworthy at all times

The airboxes need to be trustworthy at all times

There are many more issues (modulation, calibration, validation, verification, data stream design, interpretation, etc) in the ILM that play a security and reliability role to come to a stream of data that can be used for public involvement in their own living space through self determination.

Phase 2: adding health vectors and lifestyle

If the ILM seems complex than consider the situation when measuring the health parameters of real people on a regular basis both clinically as through e-heath lifestyle combinations. We add the following data-streams:

  • Personal ID
  • Historical clinical data
  • Psycho social data
  • Geo location through wearable’s
  • Cardiovascular
  • Lung data
  • etc

Each of the data-streams needs to be qualified, verified and validated. The aggregation process for analysis can only be done when we can fully trust the data sources. In addition we deal with information of real people in which issues like privacy, trust, communication, feedback, secondary effects, etc. play a significant part too. That’s why we involve not only specialized ICT people and partners but also psychologists, medical staff, persuasive technology specialists, etc.

Collecting sensitive data

Collecting sensitive data

Open data or …?

It must be clear that when combining health measurement with air quality in aggregated formats for citizen’s stimulus, scientific research and policy feedback or support, we need to be careful if we want to trigger the desired positive, proactive response. Can we still talk about open data?

During the recent Crossing Border festival we were also dealing with the combined issue of citizen’s initiatives compared to open data requirements of governments and business enterprises. In the world of financial dependencies and transactions a lot of data is being gathered for business and taxation case building. Often the data is gathered without the public knowing (GSM density, traffic flows, demographic developments, etc). The sense of Big Brother is watching you (for dubious reasons) is becoming generalized and in many ways the objections of people are justifiable. Privacy seems to be relative to the purpose that needs to be served. “National security” can be interpreted in many ways, for the risk of a terrorist attack up to the level of suspected individual tax evasion. If security is an issue people tend to open up to analysis of personal data but when they are being watched to sustain the wealth of others or a system at the expense of one’s own, they feel spied upon. AiREAS is healthy city driven but when our press release was issued the local risk avoiding government insisted to explain that the ILM equipment was not just another government element to control people out of bureaucratic interests. It is clear that we are in a process of ethical justification of actions. Transparency in our AiREAS actions was key from a citizen’s point of view since we are a purpose driven venture started by citizens. But in the process the participating institutions reacted with fear. Our current formal society has justice structured around liability and controls rather than moral responsibilities. The political and profit driven economic structure is leading, not the moral consequences. When we turn this around in the AiREAS proactive communicative context all kinds of tensions appear that need to get a place in the institutional position.

When the World Health Organization declared that air pollution a level 1 public threat in a press release of 2013 it automatically put pressure on all government communities because they could become liable in the light of human rights for the damage that is done if no measures are taken. The ethical phase of “we did not know” is behind us and cannot be used anymore as excuse. That is also why we see that local governance supported AiREAS right from the start, out of self interest but the institution also needed to get to terms with its own transformation from a consequence driven approach to a value driven partner. The guts shown by the city governance to overcome their fear when entering into the dynamics of AiREAS is an example for many other cities around the world. After 4 years also the city governance sees the fruit of their leadership as larger national and European governments now start to get inspired by Eindhoven and invest in next steps, directly through the government or by supporting the expansion of AiREAS in their own regions.

What we want to achieve is not always what others perceive

Trust needs to be gained but is extremely difficult to sustain in the dynamic world of transforming paradigms. We simply want to achieve a health city but others see it as an attack on their business interests, the value of their properties or the fear to take responsibility. The three layers of ethics always play a role in every relationship and interact with confrontational strength. AiREAS needs to deal with this to go ahead. We understand the many situations that can appear when one level is confronted with the other. Data has the effect that it can stimulate certain groups but also expose others. In a transformation the exposed groups can be still powerful in their self interests and use instruments of resistance, including justice, to block others, including AiREAS. If our data is compromised or disputable we have everything to loose. This is yet another reason to be extra demanding on our sense of responsibility. Our partners break through their own glass ceilings using their AiREAS relationship, confronting their own conservative pressures with value driven change. It is the AiREAS responsibility to provide indisputable sustainable arguments. The common denominator is “healthy city” and “transformative change” with each of the partners (citizens, business innovators, governance and science). Data is an instrument. It is open, but validated, calibrated and aggregated against that moral, ethical purpose.

Leadership is about change (AiREAS) while management is about sustaining growth of the past (conservatism)

Leadership is about change (s.a. AiREAS) while management is about sustaining growth of the past (conservatism)

The dynamics of purpose drive human kind is captured in STIR Academy. Knowledge about progress is free, about growth is expensive, about harmony is priceless (talent x input = reciprocity)

Positioning human progress in the field of harmony (wellness) rather than growth

Positioning human progress in the field of harmony (wellness) rather than growth. STIR Academy captures the AiREAS learning curves for educational purpose