• Paul Peter Nicolai

Infrastructure Data In Contracts

Updated: Nov 8

New deployments of smart devices and smart services are happening rapidly.


Almost all new infrastructure should be informed by new sources and applications of data. Better data can minimize adverse environment impacts, planning roads, and estimating likely traffic outcomes, all of which provides better evidence that can reduce the cost of new infrastructure builds. Data can assist to make smarter decisions about not-so-smart new physical infrastructure, and new smart buildings, cities, and utility networks.


Data and new sources of data can and should be an increasingly important factor in lowering the cost of and maximizing value derived from major infrastructure projects.


Analytics insights of patterns of use of new infrastructure, and changes in surrounding communities driven by new infrastructure, can dramatically improve assessment of infrastructure build outcomes and enable innovative structures like outcomes-based financing that uses quantitively reliable and verified measurement of social outcomes.


Standard contracts and contracting models used today for commissioning and financing of new infrastructure, particularly by government and utilities, has generally not kept pace with the diversity in data sources and data analytics capabilities to inform projects. Too often government and utilities are not achieving the best value for money in planning, building, and operating new infrastructure.


There are a number of reasons why:


Lawyers most familiar with data contracts are technology lawyers, not construction, finance, or infrastructure lawyers. Best practices in data contracting is infiltrating other fields of business lawyering, but only slowly.

Data is not recognized as an asset class, so its importance is overlooked. Infrastructure sectors are only beginning to understand how to derive, capture, and fairly allocate value from data.


There are misconceptions about data ownership. The common misconception is that data should be dealt with as a type of intellectual property, like engineering plans, operations manuals and software. This is often wrong because the others are protectable as copyright works and sometimes as patentable subject matter. Many data sources and data sets are not creations of human hands and are not protectable in these ways.


Insights from data analytics often come through a combination of data from multiple sources or different points in a multiparty data ecosystem, where the rights of aggregation, combination, and use to create outputs and insights are not captured and held by a single party. Variety of parties and data custodians creates contracting challenges, particularly if data value is sought to be captured by the commissioners of a physical infrastructure as a trade secret.

To the extent the value of data in individual projects is brought into expense and revenue projections, data are often valued in relation to a specific project and not for its application to affect a class of infrastructure assets or its potential use to increase utilization of an infrastructure asset.


Misconception as to who owns data causes particular problems. Data, mathematical formulae generally cannot be legally owned as ownership is legally determined in most places. As a result, licensing data often does not make legal sense. The statement that no one owns data is technically true as a matter of property law in many jurisdictions. However, it is also misleading.


The key is that legal ownership of data cannot be definitely assured through intellectual property law or contractual provisions in common use in infrastructure contracts today. Parties commissioning a physical asset must be particularly cautious to ensure that rights to and control of data use and reuse are captured and held by a single party.


The problem also partly comes from an unclear distinction between data and useful information. We use data as a term covering any and all of (1) raw data that may not be discoverable and interpretable by machines, (2) structured data that is ready for machine interpretation, and (3) information carrying human interpretable meaning, like text, music, and images.


The distinction between data and information is critical when considering intellectual property rights and other rights and legitimate expectations of parties sharing data in multiparty data ecosystems. When we use data and information interchangeably, we lose precision in understanding data value.


It is possible to define certain ownership-like rights and obligations in relation to data.


One option is to define ownership-like rights and obligations by contract. The practical difficulty is that contractual rights can only be enforced against a party to the contract in relation to acts or omissions of that party and acts and omissions of third parties for whom that party accepts contractual responsibility.


Another option is to use contract provisions to leverage the laws on confidential information or trade secrets. The Uniform Trade Secrets Act says a trade secret is information that: (i) derives independent economic value, actual or potential, from not being generally known to, and not being readily ascertainable by proper means by, other persons who can obtain economic value from its disclosure or use, and (ii) is the subject of efforts that are reasonable under the circumstances to maintain its secrecy.


The WTO TRIPS Agreement says natural and legal persons have the possibility of preventing information lawfully within their control from being disclosed to, acquired by, or used by others without their consent in a manner contrary to honest commercial practices. Nations that are parties to the TRIPS Agreement must provide the right to control data that is (a) secret, (b) valuable, and (c) safeguarded.


The EU has made an effort to standardize national laws in EU countries against the unlawful acquisition, disclosure, and use of trade secrets. EU Member States must implement its directive which harmonizes the definition of trade secrets according to existing internationally binding standards and defines the relevant forms of misappropriation.


In Australia, trade secrets are generally regarded as a subset of protected confidential information.


If data is public, it is no longer confidential and is no longer a trade secret; regardless of whether it remains commercially valuable. A collation of data that is a database may still be confidential where only some of the much larger collation is in the public domain. A publicly accessible database may be protected if the access is controlled and limited so that the combined accesses do not make the database broadly available. Also, more extensive data sets or fields from collation of data may be allowed to circulate in a controlled and limited section of the public under legally binding confidentiality conditions.


Even where data in a database is not protectable as a trade secret or other intellectual property, the way elements of the database are labelled, structured, managed, correlated, or used often can be protected as a trade secret or as other intellectual property.


Clauses in infrastructure project agreements as commonly negotiated today usually address ownership and assignment of intellectual property rights and rights to confidential information. They often do not capture and allocate data as a class of asset. They do not require each party in a multiparty data ecosystem to take all commercially reasonable steps to ensure protection of data the party handles as a trade secret.


Often the contract leaves ambiguity as to which entity handling data is the holder of the rights that may arise in any to trade secrets in that data.


These issues can be readily addressed in infrastructure contracts. The first step is to recognize the data sets associated with design, build, operation and maintenance of the asset. The second is to assess the value of that data and determine its fair allocation. The third is to work out which entity should control that data, and what each other entity handling that data should be contractually required to do to ensure the ultimate data owner can protect and derive that value. Fourth is to work out what practical controls, safeguards, oversight and verification mechanisms, and other operational data governance should be contractually assured. Once these four steps are completed, the lawyers can draft the contract. The infrastructure contract will need tailoring to ensure (1) key rights of and to data are properly captured and held by a single party; (2) the complexities from data coming from multiple sources at different points in a multiparty shared data ecosystem are properly dealt with so it is clear who holds rights in and to confidential information and trade secrets, including in further transformed and derived information.



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