Building a Legal Data Science Lab

To deal with such a complicated subject, I would like to start with a very simple notion: a chain is only as strong as its weakest link. So, if you are looking to build (or join) a legal data science laboratory within your university, you need to investigate how strong each of the following steps is:

• You have Previous research that have already made it possible to understand the legal context of a delimited field? In other words, do you already master the area of the business?
• Your previous search has been exhausted or was limited by the absence of data? In other words, is it only possible to reach a new scientific level after exploring this horizon?
• After confirming the limitations of the previous step, you have formulated problems whose answers can be obtained from data?
• In addition to the problems, you have already formulated Chance testable with this data?
• It is possible to obtain the data Demanded by his hypothesis? Is this data available at least in an unstructured way?
• If necessary, you have Structuring conditions these data?
• Once you have structured the data, you will be able to Keep updating and Evolve in modeling of the data? In other words, how disposable is your research?
• In addition to you, there is already a team with Data culture who can understand the challenges of this type of research and is willing to move in this direction?
• Your team has a Work routine and Knowledge Management that allow relatively simple individual plans to be carried out in parallel (for example, some TCC), guided by milestones that support more sophisticated research in the future (for example, a doctoral thesis)?
• Have you ever documented a Training cycle minimum to embark new researchers? Are there more cost-effective alternatives to a training cycle that depends on you? For example, is there already a data science training course that is regularly offered and accessible to potential team members?
• In addition to your subordinates, you have people with knowledge of other areas who are able to confirm viability of his ambition?
• That is, with the objective of conducting empirical research in law (applied social science), you have a Network to evolve in partnership with knowledge of technological support (exact sciences)?
• Are you open to accepting and guide your planning From this feasibility analysis, combining immediately viable research projects and a horizon of innovation to be explored?
• The results of the research can be incorporated into products that have value for the market ? You already have a plan to have Market access ?

Of course, this is not a single path. There are several types of laboratories, especially when it comes to the university context, in which a large part of the resources of the laboratories are demands for teaching or basic research activities. But if you're involved in building a laboratory that has a legal purpose and works with data, you may want to take certain precautions. After all, technology is not his main area.

In conclusion, Building a laboratory is not the same as buying equipment . A laboratory is built around problems to be solved. And these are not small problems, as they require collaboration from different areas to be overcome. The work environment and culture of this group of people are the foundations of the laboratory. In fact, it is something quite intangible.

In a world in which technological infrastructure has started to be consumed as a service (cloud computing), having physical resources is no longer an absolute competitive advantage. The real challenge is to develop a work that reconciles research and innovation with the urgency and pragmatism demanded by the market.

After all, in this area, without the market, there is no funded research. And, without money, the other conditions to create and maintain a laboratory of this type will not be present. My recommendation is that you don't go shopping on the first day, because first you need to answer the list of questions listed at the beginning of the post.

PS: While writing the post, I learned that the CNJ, by Ordinance 25/19, created a laboratory (called Inova PJe) and an Artificial Intelligence Center. I don't think the reflections in the post are fully applicable to institutional laboratories. In fact, I see the CNJ more as a decision-making body than an operational one. The operation itself would take place, for example, in an agreement with an academic laboratory, whose operation I described in the post.