Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

Towards Persistent Storage and Retrieval of Domain Models using Graph Database Technology

We employ graph database technology to persistently store and retrieve robot domain models.Comment: Presented at DSLRob 2015 (arXiv:1601.00877

The MultiDark Database: Release of the Bolshoi and MultiDark Cosmological Simulations

We present the online MultiDark Database -- a Virtual Observatory-oriented, relational database for hosting various cosmological simulations. The data is accessible via an SQL (Structured Query Language) query interface, which also allows users to directly pose scientific questions, as shown in a number of examples in this paper. Further examples for the usage of the database are given in its extensive online documentation (www.multidark.org). The database is based on the same technology as the Millennium Database, a fact that will greatly facilitate the usage of both suites of cosmological simulations. The first release of the MultiDark Database hosts two 8.6 billion particle cosmological N-body simulations: the Bolshoi (250/h Mpc simulation box, 1/h kpc resolution) and MultiDark Run1 simulation (MDR1, or BigBolshoi, 1000/h Mpc simulation box, 7/h kpc resolution). The extraction methods for halos/subhalos from the raw simulation data, and how this data is structured in the database are explained in this paper. With the first data release, users get full access to halo/subhalo catalogs, various profiles of the halos at redshifts z=0-15, and raw dark matter data for one time-step of the Bolshoi and four time-steps of the MultiDark simulation. Later releases will also include galaxy mock catalogs and additional merging trees for both simulations as well as new large volume simulations with high resolution. This project is further proof of the viability to store and present complex data using relational database technology. We encourage other simulators to publish their results in a similar manner.Comment: 28 pages, 9 figures, submitted to New Astronom

Extending the data dictionary for data/knowledge management

Current relational database technology provides the means for efficiently storing and retrieving large amounts of data. By combining techniques learned from the field of artificial intelligence with this technology, it is possible to expand the capabilities of such systems. This paper suggests using the expanded domain concept, an object-oriented organization, and the storing of knowledge rules within the relational database as a solution to the unique problems associated with CAD/CAM and engineering data

Using meta-reflection to enhance performance

Much evidence supports the use of reflective practice for personal development, yet it is not commonly used as a learning tool in students. More typically, reflective writing is assessed as a stand-alone piece of work. The objective is then simply a grade. The proposed project would actively promote the use reflections to improve performance by means of using technology to record, store and retrieve them. These individual reflections will populate a database so that ultimately, with permission, each individual's reflections can be accessed by others via the database. Thus these reflections will become a learning tool for students. Using technology facilitates classification and retrieval and reduces the problems associated with human memory

Study on evaluation of International Science and Technology Cooperation Project (ISTCP) in China

This paper presents an overview of evaluation of ISTCP in China. We discuss briefly the history of evaluation and the strengths and weaknesses of different assessment systems. On this basis, with Analytical Hierarchy Process (AHP), we establish evaluation indicator system for ISTCP that includes research project establishment evaluation, mid-period evaluation system, effect evaluation system, and confirm the value of each indicator. At the same time, we established expert database, project database, research organization database, researcher database etc. We therefore establish an evaluation platform for international science and technology cooperation project. We use it to realize full process supervision from evaluation expert selection to project management