Ontology population for open-source intelligence: A GATE-based solution

Open-Source INTelligence is intelligence based on publicly available sources such as news sites, blogs, forums, etc. The Web is the primary source of information, but once data are crawled, they need to be interpreted and structured. Ontologies may play a crucial role in this process, but because of the vast amount of documents available, automatic mechanisms for their population are needed, starting from the crawled text. This paper presents an approach for the automatic population of predefined ontologies with data extracted from text and discusses the design and realization of a pipeline based on the General Architecture for Text Engineering system, which is interesting for both researchers and practitioners in the field. Some experimental results that are encouraging in terms of extracted correct instances of the ontology are also reported. Furthermore, the paper also describes an alternative approach and provides additional experiments for one of the phases of our pipeline, which requires the use of predefined dictionaries for relevant entities. Through such a variant, the manual workload required in this phase was reduced, still obtaining promising results

Formalising responsibility modelling for automatic analysis

Modelling the structure of social-technical systems as a basis for informing software system design is a difficult compromise. Formal methods struggle to capture the scale and complexity of the heterogeneous organisations that use technical systems. Conversely, informal approaches lack the rigour needed to inform the software design and construction process or enable automated analysis. We revisit the concept of responsibility modelling, which models social technical systems as a collection of actors who discharge their responsibilities, whilst using and producing resources in the process. Responsibility modelling is formalised as a structured approach for socio-technical system requirements specification and modelling, with well-defined semantics and support for automated structure and validity analysis. The effectiveness of the approach is demonstrated by two case studies of software engineering methodologies

Beyond the Model Rules: The Place of Examples in Legal Ethics

The Model Rules of Professional Conduct defined the agenda for the post- Watergate renaissance in legal ethics. While there had been some form of codified precepts for American lawyers since at least 1908, Watergate inspired a desire to clean up a disgraced profession. The American Bar Association (ABA) promulgated the Model Rules; law schools instituted mandatory courses; and scholars debated and analyzed the new Model Rules. The organized bar devoted much time and attention to developing these guidelines. The mainstream media covered both the bar\u27s original efforts and the subsequent adoption of the Model Rules by particular jurisdictions. Today, forty-three American jurisdictions have adopted ethics guidelines based closely on the Model Rules

Organizationally Sensible vs. Legal-Centric Approaches to Employment Decisions With Legal Implications

This article is intended to: 1) alert human resource (HR) professionals to the risk that they, and the managers they serve, are unnecessarily contributing to the impact of legal considerations on the management of employees as a result of “legal-centric decision making”; and 2) provide information and guidance that will assist HR professionals in promoting better informed, more organizationally sensible responses to employment issues that have potential legal implications. The “legal-centric decision making” construct is introduced and illustrated, a model of the primary factors contributing to legal-centric decision making is presented, and keys to avoiding legal-centric decision making are identified and discussed

The Lawyer as Legal Scholar

I review Eugene Volokh's recent book, Academic Legal Writing. The book is nominally directed to law students and those who teach them (and for those audiences, it is outstanding), but it also contains a number of valuable lessons for published scholars. The book is more than a writing manual, however. I argue that Professor Volokh suggests implicitly that scholarship is underappreciated as a dimension of the legal profession. A well-trained lawyer, in other words, should have experience as a scholar. The argument sheds new light on ongoing discussions about the character of law schools

Conceptual Modeling in Law: An Interdisciplinary Research Agenda

The article describes how different approaches from the IS field of conceptual modeling should be transferred to the legal domain to enhance comprehensibility of legal regulations and contracts. It is further described how this in turn would benefit the IS discipline. The findings emphasize the importance of further interdisciplinary research on that topic. A research agenda that synthesizes the presented ideas is proposed based on a framework that structures the research field. Researchers from both disciplines, IS and Law, that are interested in this field should use the research agenda to position their research and to derive new and innovative research questions

The Automation of Legal Reasoning: Customized AI Techniques for the Patent Field

As Artificial Intelligence and Machine Learning continue to transform numerous aspects of our everyday lives, their role in the legal profession is growing in prominence. A subfield of Al with particular applicability to legal analysis is Natural Language Processing (NLP). NLP deals with computational techniques for processing human languages such as English, making it a natural tool for processing the text of statutes, regulations, judicial decisions, contracts, and other legal instruments. Paradoxically, although state-of-the-art Machine Learning and NLP algorithms are able to learn and act upon patterns too complex for humans to perceive, they nevertheless perform poorly on many cognitive tasks that humans routinely perform effortlessly. This profoundly limits the ability of Al to assist in many forms of legal analysis and legal decision making. This article offers two theses. First, notwithstanding impressive progress on NLP tasks in recent years, the state-of-the-art in NLP will remain unable to perform legal analysis for some time. Second, lawyers, legal scholars, and other domain experts can play an integral role in designing Al software that can partially automate legal analysis, overcoming some of the limitations in NLP capabilities

Beyond Invention: Patent as Knowledge Law

The decision of the Supreme Court of the United States in Bilski v. Kappos, concerning the legal standard for determining patentable subject matter under the American Patent Act, is used as a starting point for a brief review of historical, philosophical, and cultural influences on subject matter questions in both patent and copyright law. The article suggests that patent and copyright law jurisprudence was constructed initially by the Court with explicit attention to the relationship between these forms of intellectual property law and the roles of knowledge in society. Over time, explicit attention to that relationship has largely disappeared from the Court’s opinions. The article suggests that renewing consideration of the idea of a law of knowledge would bring some clarity not only to patentable subject matter questions in particular but also to much of intellectual property law in general

Engineering enterprise through intellectual property education - pedagogic approaches

Engineering faculties, despite shrinking resources, are delivering to new enterprise agendas that must take account of the fuzzying of disciplinary boundaries. Learning and teaching, curriculum design and research strategies reflect these changes. Driven by changing expectations of how future graduates will contribute to the economy, academics in engineering and other innovative disciplines are finding it necessary to re-think undergraduate curricula to enhance students’ entrepreneurial skills, which includes their awareness and competence in respect of intellectual property rights [IPRs]. There is no well established pedagogy for educating engineers, scientists and innovators about intellectual property. This paper reviews some different approaches to facilitating non-law students’ learning about IP. Motivated by well designed ‘intended learning outcomes’ and assessment tasks, students can be encouraged to manage their learning... The skills involved in learning about intellectual property rights in this way can be applied to learning other key, but not core, subjects. At the same time, students develop the ability to acquire knowledge, rather than rely on receiving it, which is an essential competence for a ‘knowledge’ based worker