BOLD Vision 2020:Designing a vision for the future of Big Open Legal Data

The vision of openlaws.eu is to make access to justice easier for citizens, business- es and legal experts. For this purpose, an innovative legal information platform has been designed by the openlaws.eu project, considering the needs of various stakeholder groups as well as the latest developments in technology and our information society. Access to justice is a fundamental problem in the European Union. There are over 500 million citizens and over 21 million businesses who live, work and operate in 28 jurisdictions, written in 24 official languages. A common market cannot work without a legal system as a basis. Legal information is a public good and it is the duty of governments and the EU to inform citizens and business about the law. In a democracy and under the rule of law everybody should know legislation and case law – or at least have access to it. Legal tech is a new terms for new technology that can be applied to legal information in order to create better access and better understanding of the law. However, just because things can be done, does not mean automatically that they are done. Financial and organisational restrictions and the lack of competency can be a deal-breaker for innovation. Open data, open innovation and open source software can be a potential solution to this problem, especially when combined to one coherent ecosystem. openlaws.eu has developed a prototype platform upon these new open concepts. The application and implementation of some of the features of this innovative legal cloud service indicate where the road of “Big Open Legal Data” can lead us in the upcoming years. The project team envisages an environment, where a “social layer” is put on top of the existing “institutional layer”. Citizens, businesses and legal experts can actively collaborate on the basis of primary legislation and case law. Linked and aggregated legal data provide a solid basis. Such information can then be represented in traditional and more innovative ways. Text and data mining as well as legal intelligence help to process large amounts of legal information automatically, so that experts can focus on the more complicated questions. In the next five years more and more legal data will be opened up, not only because of the PSI Directive, but also because it is in the best interest of governments. As a result, we anticipate that more legal tech start-ups will emerge, as already happened during the past two years. They will apply innovative concepts and new technology on existing legal information and create better access to justice in the EU, in Member States and in the world

Computational fluid dynamic predictions and experimental results for particle deposition in an airway model

An area identified as having a high priority by the National Research Council (NRC 1998) relating to health effects of exposure to urban particulate matter is the investigation of particle deposition patterns in potentially-susceptible subpopulations. A key task for risk assessment is development and refinement of mathematical models that predict local deposition patterns of inhaled particles in airways. Recently, computational fluid dynamic modeling (CFD) has provided the ability to predict local airflows and particle deposition patterns in various structures of the human respiratory tract. Although CFD results generally agree with available data from human studies, there is a need for experimental particle deposition investigations that provide more detailed comparisons with computed local patterns of particle deposition. Idealized 3-generation hollow tracheobronchial models based on the Weibel symmetric morphometry for airway lengths and diameters (generations 3-5) were constructed with physiologically-realistic bifurcations. Monodisperse fluorescent polystyrene latex particles (1 and 10 μm aerodynamic diameter) were deposited in these models at a steady inspiratory flow of 7.5 L/min (equivalent to heavy exertion with a tracheal flow of 60 L/min). The models were opened and the locations of deposited particles were mapped using fluorescence microscopy. The particle deposition predictions using CFD for 10 μm particles correlated well with those found experimentally. CFD predictions were not available for the 1 μm diameter case, but the experimental results for such particles are presented

Final Specification and Vision of Enrichment Tools

This report describes the final specification of the OpenLaws.eu enrichment tools. It is a far more elaborate description than D2.2.d2 – Initial Specification. Not everything described in this report is part of the final OpenLaws.eu portal. Where it is, this is explicitly mentioned. The report describes BOLD objects and networks, the peculiarities of legal documents and data and then ways to analyse and visualize these, providing additional metadata (‘enrichment’), either by humans (‘crowd sourcing’) or automatic means

Final Specification and Vision of Enrichment Tools

This report describes the final specification of the OpenLaws.eu enrichment tools. It is a far more elaborate description than D2.2.d2 – Initial Specification. Not everything described in this report is part of the final OpenLaws.eu portal. Where it is, this is explicitly mentioned. The report describes BOLD objects and networks, the peculiarities of legal documents and data and then ways to analyse and visualize these, providing additional metadata (‘enrichment’), either by humans (‘crowd sourcing’) or automatic means

Software Engineering within a Dynamic Digital Business Ecosystem

The goal of fast adaptations and modifications according to continuous change requests is common to all software engineering methodologies. In most cases, sooner or later this results in a mismatch between the software specification and the actual implementation with related disadvantages such as the impossibility of performing validations of related models. We present here an aspect of the digital business ecosystem concept that gives incentives for more responsible software engineering approaches in general by offering a platform for automatic composition of services and re-adaptation of the specifications based on actual changes. The main innovation is a natural language based modelling notation that enables ecosystems of companies to use software described in a high-level language that can also be understood by non-technical users