Support vector machines in spectral data classification

Työssä käydään läpi tukivektorikoneiden teoreettista pohjaa sekä tutkitaan eri parametrien vaikutusta spektridatan luokitteluun.

m-Equine : IS support for the horse industry

The horse industry is in many ways still operating the same way as it did in the beginning of the 20th century. At the same time the role of the horse has changed dramatically, from a beast of burden to a top athlete, a production animal or a beloved pet. A racehorse or an equestrian sport horse is trained and taken care of like any other athlete, but unlike its human counterpart, it might end up on our plate. According to European and many other countries’ laws, a horse is a production animal. The medical data of a horse should be known if it is to be slaughtered, to ensure that the meat is safe for human consumption. Today this vital medical information should be noted in the horse’s passport, but this paperbased system is not reliable. If a horse gets sold, depending on the country’s laws, the medical records might not be transferred to the new owner, the horse’s passport might get lost etc. Thus the system is not fool proof. It is not only the horse owners who have to struggle with paperwork; veterinarians as well as other officials often use much time on redundant paperwork. The main research question of this thesis is if IS could be used to help the different stakeholders within the horse industry? Veterinarians in particular who travel to stables to treat horses cannot always take with them their computers, since the somewhat unsanitary environment is not suitable for a sensitive technological device. Currently there is no common medical database developed for horses, although such a database with a support system could help with many problems. These include vaccination and disease control, food-safety, as well as export and import problems. The main stakeholders within the horse industry, including equine veterinarians and horse owners, were studied to find out their daily routines and needs for a possible support system. The research showed that there are different aspects within the horse industry where IS could be used to support the stakeholders daily routines. Thus a support system including web and mobile accessibility for the main stakeholders is under development. Since veterinarians will be the main users of this support system, it is very important to make sure that they find it useful and beneficial in their daily work. To ensure a desired result, the research and development of the system has been done iteratively with the stakeholders following the Action Design Research methodology.

Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

Finnish SMEs and Russian Business Environment: Challenges and Support Activities

The purpose of this study is based on the need of finding what kind of problems Finnish SMEs face in Russian market and how they could be supported. Used support activities in certain levels of internationalization and internationalization patterns are evaluated, international experience of entrepreneur is compared to used support activities and the most challenging pillars in Russia from the Institutional Theory are defined. The empirical part of the study is a semi structured qualitative analysis of ten case companies that represent different industry fields. All of them are SMEs and they represent different levels of internationalization and internationalization patterns. The results of this study indicated that usefulness of support activities have to be evaluated case by case. All the companies are individual organizations and usefulness of support activities have to be evaluated according to the actual situation of the company. International experience of manager has effect on the use of support activities. SMEs identified many problems related to pillars of Institutional theory and regulative environment seems to be the most challenging one.

Fuzzy ontology for knowledge mobilisation and decision support

A growing concern for organisations is how they should deal with increasing amounts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advantage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available information systems are not capable of handling imprecise data, even though it can offer various advantages. Expert knowledge stored as linguistic expressions is a good example of imprecise but valuable data, i.e. data that is hard to exactly pinpoint to a definitive value. There is an obvious concern among organisations on how this problem should be handled; finding new methods for processing and storing imprecise data are therefore a key issue. Additionally, it is equally important to show that tacit knowledge and imprecise data can be used with success, which encourages organisations to analyse their imprecise data. The objective of the research conducted was therefore to explore how fuzzy ontologies could facilitate the exploitation and mobilisation of tacit knowledge and imprecise data in organisational and operational decision making processes. The thesis introduces both practical and theoretical advances on how fuzzy logic, ontologies (fuzzy ontologies) and OWA operators can be utilized for different decision making problems. It is demonstrated how a fuzzy ontology can model tacit knowledge which was collected from wine connoisseurs. The approach can be generalised and applied also to other practically important problems, such as intrusion detection. Additionally, a fuzzy ontology is applied in a novel consensus model for group decision making. By combining the fuzzy ontology with Semantic Web affiliated techniques novel applications have been designed. These applications show how the mobilisation of knowledge can successfully utilize also imprecise data. An important part of decision making processes is undeniably aggregation, which in combination with a fuzzy ontology provides a promising basis for demonstrating the benefits that one can retrieve from handling imprecise data. The new aggregation operators defined in the thesis often provide new possibilities to handle imprecision and expert opinions. This is demonstrated through both theoretical examples and practical implementations. This thesis shows the benefits of utilizing all the available data one possess, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web movement, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision.

An Open Source, DDI-based Curation System for Social Science Data

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

An Alternative American Approach to Repositories

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Interoperability specifications and an automatic validation tool as a key factor for the support of a repository ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Task Force on Librarians’ Competencies in Support of E-Research and Scholarly Communication

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Towards multi bibliographic format support in Invenio

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Using ArchivesSpace to Support Research Data Curation

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

ORCIDs in the Wild: Implementing ORCIDs into Research Support and Repository Systems

Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Dealing with Funder Mandates: Practical Support for Repository Practitioners – A Workshop

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014