2019
Garofalakis, John; Plessas, Konstantinos; Plessas, Athanasios; Spiliopoulou, Panoraia
In: Information, vol. 11, no. 1, 2019.
Abstract | Links | BibTeX | Ετικέτες: Akoma Ntoso, domain specific language, Legal Big Data, Legal Open Data, legal parsing, natural language processing, Open Data Ecosystem
@article{Garofalakis2019b,
title = {Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data},
author = {John Garofalakis and Konstantinos Plessas and Athanasios Plessas and Panoraia Spiliopoulou},
doi = {10.3390/info11010010},
year = {2019},
date = {2019-12-22},
journal = {Information},
volume = {11},
number = {1},
abstract = {Regulation of modern societies requires the generation of large sets of heterogeneous legal documents: bills, acts, decrees, administrative decisions, court decisions, legal opinions, circulars, etc. More and more legal publishing bodies publish these documents online, although usually in formats that are not machine-readable and without following Open Data principles. Until an open by default generation and publication process is employed, ex-post transformation of legal documents into Legal Open Data is required. Since manual transformation is a time-consuming and costly process, automated methods need to be applied. While some research efforts toward the automation of the transformation process exist, the alignment of such approaches with proposed Open Data methodologies in order to promote data exploitation is still an open issue. In this paper, we present a methodology aligned to the Open Data ecosystem approach for the automated transformation of Greek court decisions and legal opinions into Legal Open Data that builds on legal language processing methods and tools. We show that this approach produces Legal Open Data of satisfying quality while highly reducing the need for manual intervention.},
keywords = {Akoma Ntoso, domain specific language, Legal Big Data, Legal Open Data, legal parsing, natural language processing, Open Data Ecosystem},
pubstate = {published},
tppubtype = {article}
}
Regulation of modern societies requires the generation of large sets of heterogeneous legal documents: bills, acts, decrees, administrative decisions, court decisions, legal opinions, circulars, etc. More and more legal publishing bodies publish these documents online, although usually in formats that are not machine-readable and without following Open Data principles. Until an open by default generation and publication process is employed, ex-post transformation of legal documents into Legal Open Data is required. Since manual transformation is a time-consuming and costly process, automated methods need to be applied. While some research efforts toward the automation of the transformation process exist, the alignment of such approaches with proposed Open Data methodologies in order to promote data exploitation is still an open issue. In this paper, we present a methodology aligned to the Open Data ecosystem approach for the automated transformation of Greek court decisions and legal opinions into Legal Open Data that builds on legal language processing methods and tools. We show that this approach produces Legal Open Data of satisfying quality while highly reducing the need for manual intervention.
Garofalakis, John; Plessas, Konstantinos; Plessas, Athanasios; Spiliopoulou, Panoraia
Modelling Legal Documents For Their Exploitation As Open Data Proceedings Article
In: Abramowicz, Witold; Corchuelo, Rafael (Ed.): Business Information Systems. BIS 2019., pp. 30-44, Springer, Cham, 2019, ISBN: 978-3-030-20484-6.
Abstract | Links | BibTeX | Ετικέτες: Akoma Ntoso, Greek legislation, Legal Open Data, Modelling
@inproceedings{Garofalakis2019,
title = {Modelling Legal Documents For Their Exploitation As Open Data},
author = {John Garofalakis and Konstantinos Plessas and Athanasios Plessas and Panoraia Spiliopoulou},
editor = {Witold Abramowicz and Rafael Corchuelo},
url = {https://link.springer.com/chapter/10.1007/978-3-030-20485-3_3},
doi = {10.1007/978-3-030-20485-3_3},
isbn = {978-3-030-20484-6},
year = {2019},
date = {2019-05-18},
booktitle = {Business Information Systems. BIS 2019.},
volume = {353},
pages = {30-44},
publisher = {Springer, Cham},
series = {Lecture Notes in Business Information Processing},
abstract = {As our society becomes more and more complex, legal documents are produced at an increasingly fast pace, generating datasets that show many of the characteristics that define Big Data. On the other hand, as the trend of Open Data has spread widely in the government sector nowadays, publication of legal documents in the form of Open Data is expected to yield important benefits. In this paper, we propose the modelling of Greek legal texts based on the Akoma Ntoso document model, which is a necessary step for their representation as Open Data and we describe use cases that show how these massive legal open datasets could be further exploited.},
keywords = {Akoma Ntoso, Greek legislation, Legal Open Data, Modelling},
pubstate = {published},
tppubtype = {inproceedings}
}
As our society becomes more and more complex, legal documents are produced at an increasingly fast pace, generating datasets that show many of the characteristics that define Big Data. On the other hand, as the trend of Open Data has spread widely in the government sector nowadays, publication of legal documents in the form of Open Data is expected to yield important benefits. In this paper, we propose the modelling of Greek legal texts based on the Akoma Ntoso document model, which is a necessary step for their representation as Open Data and we describe use cases that show how these massive legal open datasets could be further exploited.
2018
Garofalakis, John; Plessas, Konstantinos; Plessas, Athanasios; Spiliopoulou, Panoraia
A Project for the Transformation of Greek Legal Documents into Legal Open Data Proceedings Article
In: Proceedings of the 22th Pan-Hellenic Conference on Informatics, ACM, New York, NY, USA, 2018, ISBN: 978-1-4503-6610-6.
Abstract | Links | BibTeX | Ετικέτες: Akoma Ntoso, Greek legislation, Legal Open Data, Legal Text Analysis
@inproceedings{Garofalakis2018,
title = {A Project for the Transformation of Greek Legal Documents into Legal Open Data},
author = {John Garofalakis and Konstantinos Plessas and Athanasios Plessas and Panoraia Spiliopoulou},
doi = {10.1145/3291533.3291548},
isbn = {978-1-4503-6610-6},
year = {2018},
date = {2018-11-30},
booktitle = {Proceedings of the 22th Pan-Hellenic Conference on Informatics},
publisher = {ACM},
address = {New York, NY, USA},
series = {PCI '18},
abstract = {In modern states, the operation of the three branches of government (executive, legislative and judicial) results in the generation of a huge volume of data (e.g. legislative documents, decisions, reports, statistics etc.). Publication of government data in the form of Open Data is expected, among other benefits, to drive economic development and promote transparency. This is also true for legal data, since new services for citizens, companies, legal professionals and governments could emerge as a result of the availability of Legal Open Data. Since such information is usually published in unstructured formats, automated approaches could highly facilitate the transformation of unstructured data into structured Open Data, according to the 5-star Open Data scheme. In this paper, we present an ongoing project about the automated analysis and processing of Greek legal documents for their transformation into Legal Open Data. We briefly review the current state of Legal Open Data in Greece, we present the project’s research questions and analyze our initial thoughts for the implementation methodology; we discuss the challenges of such an effort and finally we elaborate the expected contributions.},
keywords = {Akoma Ntoso, Greek legislation, Legal Open Data, Legal Text Analysis},
pubstate = {published},
tppubtype = {inproceedings}
}
In modern states, the operation of the three branches of government (executive, legislative and judicial) results in the generation of a huge volume of data (e.g. legislative documents, decisions, reports, statistics etc.). Publication of government data in the form of Open Data is expected, among other benefits, to drive economic development and promote transparency. This is also true for legal data, since new services for citizens, companies, legal professionals and governments could emerge as a result of the availability of Legal Open Data. Since such information is usually published in unstructured formats, automated approaches could highly facilitate the transformation of unstructured data into structured Open Data, according to the 5-star Open Data scheme. In this paper, we present an ongoing project about the automated analysis and processing of Greek legal documents for their transformation into Legal Open Data. We briefly review the current state of Legal Open Data in Greece, we present the project’s research questions and analyze our initial thoughts for the implementation methodology; we discuss the challenges of such an effort and finally we elaborate the expected contributions.