Merenkulun turvallisuuden koetinkiviä : Terminologisen tiedon poiminta teksteistä

The methodology of extracting information from texts has widely been described in the current literature. However, the methodology has been developed mainly for the purposes of other fields than terminology science. In addition, the research has been English language oriented. Therefore, there are no satisfactory language-independent methods for extracting terminological information from texts. The aim of the present study is to form the basis for a further improvement of methods for extraction of terminological information. A further aim is to determine differences in term extraction between subject groups with or without knowledge of the special field in question. The study is based on the theory of terminology, and has mainly a qualitative approach. The research material consists of electronically readable specialized texts in the subject domain of maritime safety. Textbooks, conference papers, research reports and articles from professional journals in Finnish and in Russian are included. The thesis first deals with certain term extraction methods. These are manual term identification and semi-automatic term extraction, the latter of which was carried out by using three commercial computer programs. The results of term extraction were compared and the recall and precision of the methods were evaluated. The latter part of the study is dedicated to the identification of concept relations. Certain linguistic expressions, which some researchers call knowledge probes, were applied to identify concept relations. The results of the present thesis suggest that special field knowledge is an advantage in manual term identification. However, in the candidate term lists the variation between subject groups was not as remarkable as it was between individual subjects. The term extraction software tested here produces candidate term lists which can be useful, but only after some manual work. Therefore, the work emphasizes the need to further develop term extraction software. Furthermore, the analyses indicate that there are a certain number of terms which were extracted by all the subjects and the software. These terms we call core terms. As the result of the experiment on linguistic expressions which signal concept relations, a proposal of Finnish and Russian knowledge probes in the field of maritime safety was made. The main finding was that it would be useful to combine the use of knowledge probes with semi-automatic term extraction since knowledge probes usually occur in the vicinity of terms.

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

Analytiikkajärjestelmän käyttöönottoprojekti, kustannukset ja kustannusten hallinta

Perinteisten kilpailuetujen katoaminen ja kilpailun kiristyminen haastavat yrityksiä etsimään keinoja kilpailukyvyn säilyttämiseksi. Tietotekniikan nopea kehitys ja liiketoiminnassa syntyvän datan määrän kasvu luovat yrityksille mahdollisuuden hyödyntää analytiikkaa päätöksenteon tukena ja liiketoiminnan tehostamisessa. Työ on kirjallisuuskatsaus ja sen tavoitteena on selvittää analytiikkajärjestelmän käyttöönottoprojektin vaiheet, käyttöönottoon liittyvät kustannukset ja miten kustannuksia voidaan hallita. Lisäksi esitetään tiivis katsaus analytiikan kehitykseen ja nykytilaan sekä tarkastellaan hankintamalleja, hankkeiden taloudellista arviointia ja käyttöönottoprojektin kriittisiä menestystekijöitä. Käyttöönottoprojekti on monivaiheinen ja se alkaa liiketoiminnan analysoinnista sekä järjestelmän suunnittelusta ulottuen aina sen toteutukseen ja jälkiarviointiin. Käyttöönottoon liittyy useita kustannuseriä, joita voidaan luokitella niiden ominaisuuksien perusteella. Projektin kustannusten hallinnan prosesseja ovat kustannusten hallinnan suunnittelu, kustannusten arviointi, budjetin määrittäminen ja kustannusten valvonta, jotka limittyvät käyttöönoton vaiheiden kanssa.