OpenTox predictive toxicology framework: toxicological ontology and semantic media wiki-based OpenToxipedia

<p>Abstract</p> <p>Background</p> <p>The OpenTox Framework, developed by the partners in the OpenTox project (<url>http://www.opentox.org</url>), aims at providing a unified access to toxicity data, predictive models and validation procedures. Interoperability of resources is achieved using a common information model, based on the OpenTox ontologies, describing predictive algorithms, models and toxicity data. As toxicological data may come from different, heterogeneous sources, a deployed ontology, unifying the terminology and the resources, is critical for the rational and reliable organization of the data, and its automatic processing.</p> <p>Results</p> <p>The following related ontologies have been developed for OpenTox: a) Toxicological ontology – listing the toxicological endpoints; b) Organs system and Effects ontology – addressing organs, targets/examinations and effects observed in <it>in vivo</it> studies; c) ToxML ontology – representing semi-automatic conversion of the ToxML schema; d) OpenTox ontology– representation of OpenTox framework components: chemical compounds, datasets, types of algorithms, models and validation web services; e) ToxLink–ToxCast assays ontology and f) OpenToxipedia community knowledge resource on toxicology terminology.</p> <p>OpenTox components are made available through standardized REST web services, where every compound, data set, and predictive method has a unique resolvable address (URI), used to retrieve its Resource Description Framework (RDF) representation, or to initiate the associated calculations and generate new RDF-based resources.</p> <p>The services support the integration of toxicity and chemical data from various sources, the generation and validation of computer models for toxic effects, seamless integration of new algorithms and scientifically sound validation routines and provide a flexible framework, which allows building arbitrary number of applications, tailored to solving different problems by end users (e.g. toxicologists).</p> <p>Availability</p> <p>The OpenTox toxicological ontology projects may be accessed via the OpenTox ontology development page <url>http://www.opentox.org/dev/ontology</url>; the OpenTox ontology is available as OWL at <url>http://opentox.org/api/1 1/opentox.owl</url>, the ToxML - OWL conversion utility is an open source resource available at <url>http://ambit.svn.sourceforge.net/viewvc/ambit/branches/toxml-utils/</url></p

Poslovna inteligencija u funkciji autorizovanog modela sistema za učenje na daljinu

Ideja da svo znanje ovog sveta može biti smešteno na jednom mestu, stara je više hiljada godina. Zvuči kao neka fantazija, ali to je stvarnost koja se već dogodila u Aleksandriji. Viziju te moćne ideje imao je Aleksandar Veliki. Može se reći da je Aleksandrija grad sagrađen od sna. To je i grad gde je Aleksandar Veliki sahranjen, grad gde je Kleopatra zavela Marka Antonija i Cezara, konačno taj grad je bio dom jednom od sedam svetskih čuda antičkog sveta. Međutim, bezuslovna ambicija Aleksandra Velikog da Aleksandrija postane najmoćniji grad na svetu, sprovedena je tako što je svo znanje ovog sveta bilo zarobljeno među zidovima Aleksandrijske biblioteke [Hughes, 2010]. Samo je potvrđeno: znanje je moć. Možda smo samo malo doradili ideju Aleksandra Velikog i dobili pojam Poslovna inteligencija u čijoj osnovi leži skladištenje podataka i otkrivanje znanja u tim podacima, a savremena, današnja Aleksandrijska biblioteka je naš Web. U vremenu koje karakterišu nepredvidive promene, posebno u oblasti informaciono komunikacionih tehnologija od izuzetnog je značaja razumevanje važnosti znanja. Za uspešan i razvijen svet znanje je jedina trajna vrednost. Onaj ko ga poseduje ima velike šanse za uspeh. Onaj ko ga nema, nema se čemu nadati. Kao i sve što vredi, znanje košta: truda, vremena i novaca. Mora se graditi svakodnevno i po određenim pravilima, ali pre svega mora mu se krenuti u susret. Shodno tome, u ovom radu razmatrana je primena poslovne inteligencije i definisanje analitičkog modela autorizovanog sistema za učenje na daljinu, kako bi se realizovala potreba za analizama podataka unutar DLS platforme. Svi podaci koji su korišćeni pri OLAP (On-line Analytical Processing) i EDM (Educational Data Mining) analizama prikupljeni su delimično pomoću autorizovanog sistema za učenja na daljinu (tj. dinamičke interaktivne DLS Web aplikacije, nazvane DLS platforma) i iz dokumenata u papirnatom izdanju (poput dnevnika, matičnih knjiga učenika). Metodologija poslovne inteligencije je postojeću transakcionu DLS bazu podataka, delimično pomoću procesa ETL (Extract, Transform and Load), prevela u analitičku DLS bazu podataka, tj. definasan je model skladišta podataka (Data Warehouse, DW) autorizovanog sistema za učenja na daljinu koji je omogućio OLAP i EDM analize, sa ciljem da se unapredi nastavni proces i ostvari što kvalitetnije usvajanje znanja učenika srednje tehničke škole u Srbiji, kao glavnih korisnika DLS platforme. U ovom radu sprovedene su sledeće analize: analiza uspeha školovanja, analiza urađenih resursa za učenje, analiza ocena učenika i ocena predmeta, analiza vrednovanja Distance Learning (DL) obrazovanja. Primenom koncepta poslovne inteligencije, dobijeni rezultati analiza ukazuju na to da je moguće pravovremenom intervencijom doći do znanja neophodnog za donošenje ispravnih odluka i samim tim sprovođenja niza akcija koje bi poboljšale uspeh učenika.The idea that all the knowledge of the world can be stored in one place, is thousands of years old. It sounds like a fantasy, but it is a reality that has already happened in Alexandria. It was Alexander the Great who had the vision of this powerful idea. One can say that Alexandria was a city built on dreams. It is also the city where Alexander the Great was buried, the city where Cleopatra seduced Marcus Antonius and Caesar, and finally this city was home to one of the seven wonders of the ancient world. However, unconditional ambition of Alexander the Great for Alexandria to become the most powerful city in the world, was implemented so that all the knowledge of the world was to be captured within the walls of the Library of Alexandria [Hughes, 2010]. This only confirms: knowledge is power. We may have only slightly improved the idea of Alexander the Great and came up with the concept of Business Intelligence at which basis lies data warehousing and knowledge discovery from this data, so the modern, Alexandrian library of today is our Web. In the time that is characterized by unpredictable changes, especially in the field of information and communication technologies it is of great importance to understand the importance of knowledge. In a successful and developed world, knowledge is the only permanent value. The one who possesses it has a good chance of success. The one who does not, has nothing to hope for. Like everything of value, knowledge has a price: effort, time and money. It must be built up on a daily basis and according to certain rules, but above all you must go for it. Consequently, this paper considers the application of business intelligence and analytical model definition of an authorized distance learning system, in order to realize the need for data analysis within the DLS platform. All data used in OLAP (Online Analytical Processing) and EDM (Educational Data Mining) was collected through analyses in part by an authorized distance learning system (i.e., dynamic interactive DLS Web applications, called DLS platform) and from paper documents (such as logs, student registry books). The methodology of business intelligence has translated an existing transactional database, partly through the process of ETL (Extract, Transform and Load), into an analytical database, i.e. it defined the data warehouse model (Data Warehouse, DW) of an authorized distance learning system, which enabled OLAP and EDM analysis, with the goal to improve the teaching process and achieve the best possible learning skills of students in secondary technical schools in Serbia, as major users of the DLS platform. In this paper the following analyses were conducted: analysis of the education success, analysis of the implemented learning resources, analysis of students grades and an evaluation of subjects, analysis of the evaluation of Distance Learning (DL) education. By applying the concept of business intelligence, the results obtained from these analyses indicate that it is possible, with a timely intervention, to aquire the knowledge necessary to make proper decisions and therefore the implementation of a series of actions that would improve student success