Lifecycle Data Management in Building Information Modelling
1. What is LCDM in BIM?
Lifecycle Data Management (LCDM) in Building Information Modelling (BIM) allows not only a benefit from BIM data during planning and construction phases but moreover it could also significantly improve the efficiency of the use of workplaces and space in a building when it is under the facility management.
LCDM enables the user to analyse information and data collected within the building in order to improve exploitation of the building’s capacity, efficient use of energy, make particular spaces fit for its purpose and allows for creation of the perfect environment for each individual employee or tenant using time and resources effectively. Therefore, different data in and around the building is collected to describe and show the current state of the building by displaying the data onto the building’s 3D equivalent.
In order to provide accurate, timely, and relevant information the different sets of data need to be gathered continuously. The basis of the data is the construction and design data modelling the building. Adding data about the building itself e.g. room temperature, humidity, room occupancy etc. and also personal data about room or environmental preferences, disabilities, well-being or detailed feedback, occupancy can be managed effectively and to a higher satisfaction of employees and tenants. Also, long-time predictions allowing tenant and environmental management can be drawn from the data sets if collected and stored safely and continuously.
There are examples of business buildings with 28k sensors measuring temperature, humidity, occupancy, need for maintenance or refills in pantries and bathrooms to collect comprehensive data.
Implementing and installing these systems, facility managers face different challenges in order to use the Smart Home to its highest potential.
2. Legal challenges and required contractual regulation
Using data successfully and profiting from it requires accuracy and reliability. Otherwise, the predictions made may be incorrect, inaccurate due to too little comparative data or unreliable. Therefore, during collection, widespread and accurate collection of data as well as safe storage and transmission need to be guaranteed as well as redundancy of data for long-term reliability. Besides these primarily technical issues, there are a number of legal issues that need to be addressed.
The key legal issues concern data protection and privacy, labour law and data-ownership. Measures have to be taken not only while collecting or processing and analysing data but also to secure and guarantee appropriate deletion of data.
The applicable laws and legal principles vary depending on the category of data collected, mainly distinguishing personal and non-personal data. However, the basic question of whom the data belongs to and who is allowed to use it needs to be answered for any data collected separately.
As there is no ownership to data in its natural sense, rights to the data collected need to be arranged and agreed upon contractually. However, design and construction data of the building itself may be protected by copyrights held by the engineers, architects and designers. Other data being collected during the lifecycle of the building generally does not reach the required level of originality to be protected under copyright laws. Hence, the facility manager needs to contractually secure all rights to the data collected and also the data required to be used.
2.1 Personal data of employees and customers
As soon as personal data, namely data that can be connected to a specific person, is collected, data protection laws need to be complied with.
There are no specific rules as to the collection and storage of Smart Building data in the GDPR or other data protection laws. However, any collection of data needs to be justified and if not serving the performance of the employment relationship (employee data) or any other contractual relationship (rental agreement, customers etc.) consent must be obtained from the person affected. In addition, more data protection regulations apply if any of the data is processed by anyone other than the collector. Furthermore, for any collection or processing the person responsible needs to be defined in order to determine the justification for the collection and processing of the data.
If any personal data of employees is collected that might enable the employer to monitor or control the behaviour and performance of its employees, the works council must be involved in any decision allowing the collection and monitoring of such data. If no conclusion whatsoever can be drawn from any of the data, e.g. whether a shared workroom is fully occupied, the works council need not be consulted and no specific labour law regulations apply. This can also be achieved by anonymising data or collecting larger levels of comparative data.
Also, neutral data or different types of data can be collected and connected and then transformed into user profiles which might require special consent.
2.2 Data concerning business operations
Personal and non-personal data collected might also include data that is protected as business or company secrets and needs special consent or might not be able to be collected and processed at all. However, security levels must be adapted accordingly and the collection as well as the processing should be regulated in detail contractually.
2.3 Other legal regulations
Other legal provisions need to be respected when handling sensitive data for example medical data or data of patients visiting doctors’ offices in a Smart Building. The same might apply for data collected from people being forced to visit the building in order to get access to public services etc.
3. Using and collecting data successfully
Regarding many different regulations concerning data protection and many other legal aspects concerned, any collection and processing of data should be regulated contractually where convenient and appropriate. This prevents disputes over legal uncertainties and enables anyone to profit from the analysis and predictions made.