Education in Computer Science and the Role of the Teacher in the Environment of Open Educational Resources

Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013

Links and Hubs of Scientific Information – the Case of the MTMT

We present the Hungarian National Scientific Bibliography project: the MTMT. We argue that presently available commercial systems cannot be used as a comprehensive national bibliometric tool. The new database was created from existing databases of the Hungarian Academy of Sciences, but expected to be re-engineered in the future. The data curation model includes harvesting, the work of expert bibliographers and author feedback. MTMT will work together with the other services in the web of scientific information, using standard protocols and formats, and act as a hub. It will present the scientific output of Hungary together with the repositories containing the full text, wherever available. The database will be open, but not freely harvestable, and only for non-commercial use.

Key Aspects and Approaches of Open Access, Open Data and Open Science

Overview of the key aspects and approaches to open access, open data and open science, emphasizing on sharing scientific knowledge for sustainable progress and development.

Importance and Benefits of OPEN SCIENCE for Ubiquitous Sharing, Dissemination and Impact

While openness is well applied to software development and exploitation (open sources), and successfully applied to new business models (open innovation), fundamental and applied research seems to lag behind. Even after decades of advocacy, in 2011 only 50% of the public-funded research was freely available and accessible (Archambault et al., 2013). The current research workflows, stemming from a pre-internet age, result in loss of opportunity not only for the researchers themselves (cf. extensive literature on topic at Open Access citation project, http://opcit.eprints.org/), but also slows down innovation and application of research results (Houghton & Swan, 2011). Recent studies continue to suggest that lack of awareness among researchers, rather than lack of e-infrastructure and methodology, is a key reason for this loss of opportunity (Graziotin 2014). The session will focus on why Open Science is ideally suited to achieving tenure-relevant researcher impact in a “Publish or Perish” reality. Open Science encapsulates tools and approaches for each step along the research cycle: from Open Notebook Science to Open Data, Open Access, all setting up researchers for capitalising on social media in order to promote and discuss, and establish unexpected collaborations. Incorporating these new approaches into a updated personal research workflow is of strategic beneficial for young researchers, and will prepare them for expected long term funder trends towards greater openness and demand for greater return on investment (ROI) for public funds.

Business Models for Open Access. Copyright and Licensing under Open Access

The lecture analyses the traditional business model in scientific communication and describes the new emerging models in the context of Open Access. Copyright and licensing part provides an overview of the legal issues and copyright at the heart of Open Access.

Open Access Strategy of UNESCO

One of UNESCO’s overarching goals is to build inclusive knowledge societies by harnessing information and communication technologies to maintain, increase and diffuse knowledge in the fields of education, the sciences, culture, and communication and information, including through open access. Open Access (OA) is the provision of free access to peer-reviewed, scholarly, research information (both scientific papers and research data) to all. It envisages that the rights-holder grants worldwide irrevocable right of access to copy, use, distribute, transmit, and make derivative works in any format for any lawful activities with proper attribution to the original author. Through Open Access, researchers and students from around the world gain increased access to knowledge, publications have greater visibility and readership, and the potential impact of research is heightened.

Open Research Data

Open Research Data - A step by step guide through the research data lifecycle, data set creation, big data vs long-tail, metadata, data centres/data repositories, open access for data, data sharing, data citation and publication.

Policy Framework and Roadmap for Open Access, Open Research Data and Open Science

Overview of the growth of policies and a critical appraisal of the issues affecting open access, open data and open science policies. Example policies and a roadmap for open access, open research data and open science are included.

Open Access to Publications and Research Data in Horizon 2020: What Are the Requirements and How Can Institutional Repositories and OpenAIRE Help to Meet Them?

In the last decade the principle of Open Access to publicly funded research has been getting a growing support from policy makers and funders across Europe, both at national level and within the European Union context. At European level some of the first relevant steps taken by the European Research Council (ERC) with a statement supporting Open Access (2006), shortly followed by guidelines for researchers funded by the ERC (2007) stating that all peer-reviewed publications from ERC funded projects should be made openly accessible shortly after their publication. Those guidelines were revised in October 2013, reinforcing the mandatory character of the requirements and expanding them to monographs.

Making sense of microposts (#MSM2013) concept extraction challenge

Microposts are small fragments of social media content that have been published using a lightweight paradigm (e.g. Tweets, Facebook likes, foursquare check-ins). Microposts have been used for a variety of applications (e.g., sentiment analysis, opinion mining, trend analysis), by gleaning useful information, often using third-party concept extraction tools. There has been very large uptake of such tools in the last few years, along with the creation and adoption of new methods for concept extraction. However, the evaluation of such efforts has been largely consigned to document corpora (e.g. news articles), questioning the suitability of concept extraction tools and methods for Micropost data. This report describes the Making Sense of Microposts Workshop (#MSM2013) Concept Extraction Challenge, hosted in conjunction with the 2013 World Wide Web conference (WWW'13). The Challenge dataset comprised a manually annotated training corpus of Microposts and an unlabelled test corpus. Participants were set the task of engineering a concept extraction system for a defined set of concepts. Out of a total of 22 complete submissions 13 were accepted for presentation at the workshop; the submissions covered methods ranging from sequence mining algorithms for attribute extraction to part-of-speech tagging for Micropost cleaning and rule-based and discriminative models for token classification. In this report we describe the evaluation process and explain the performance of different approaches in different contexts.

A simple remote sensing based information system for monitoring sites of conservation importance

Monitoring is essential for conservation of sites, but capacity to undertake it in the field is often limited. Data collected by remote sensing has been identified as a partial solution to this problem, and is becoming a feasible option, since increasing quantities of satellite data in particular are becoming available to conservationists. When suitably classified, satellite imagery can be used to delineate land cover types such as forest, and to identify any changes over time. However, the conservation community lacks (a) a simple tool appropriate to the needs for monitoring change in all types of land cover (e.g. not just forest), and (b) an easily accessible information system which allows for simple land cover change analysis and data sharing to reduce duplication of effort. To meet these needs, we developed a web-based information system which allows users to assess land cover dynamics in and around protected areas (or other sites of conservation importance) from multi-temporal medium resolution satellite imagery. The system is based around an open access toolbox that pre-processes and classifies Landsat-type imagery, and then allows users to interactively verify the classification. These data are then open for others to utilize through the online information system. We first explain imagery processing and data accessibility features, and then demonstrate the toolbox and the value of user verification using a case study on Nakuru National Park, Kenya. Monitoring and detection of disturbances can support implementation of effective protection, assist the work of park managers and conservation scientists, and thus contribute to conservation planning, priority assessment and potentially to meeting monitoring needs for Aichi target 11.

Leveraging product adopter information from online reviews for product recommendation

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

Perceptions and experiences of the implementation, management, use and optimisation of electronic prescribing systems in hospital settings:protocol for a systematic review of qualitative studies

Introduction: There is increasing evidence that electronic prescribing (ePrescribing) or computerised provider/physician order entry (CPOE) systems can improve the quality and safety of healthcare services. However, it has also become clear that their implementation is not straightforward and may create unintended or undesired consequences once in use. In this context, qualitative approaches have been particularly useful and their interpretative synthesis could make an important and timely contribution to the field. This review will aim to identify, appraise and synthesise qualitative studies on ePrescribing/CPOE in hospital settings, with or without clinical decision support. Methods and analysis: Data sources will include the following bibliographic databases: MEDLINE, MEDLINE In Process, EMBASE, PsycINFO, Social Policy and Practice via Ovid, CINAHL via EBSCO, The Cochrane Library (CDSR, DARE and CENTRAL databases), Nursing and Allied Health Sources, Applied Social Sciences Index and Abstracts via ProQuest and SCOPUS. In addition, other sources will be searched for ongoing studies (ClinicalTrials.gov) and grey literature: Healthcare Management Information Consortium, Conference Proceedings Citation Index (Web of Science) and Sociological abstracts. Studies will be independently screened for eligibility by 2 reviewers. Qualitative studies, either standalone or in the context of mixed-methods designs, reporting the perspectives of any actors involved in the implementation, management and use of ePrescribing/CPOE systems in hospital-based care settings will be included. Data extraction will be conducted by 2 reviewers using a piloted form. Quality appraisal will be based on criteria from the Critical Appraisal Skills Programme checklist and Standards for Reporting Qualitative Research. Studies will not be excluded based on quality assessment. A postsynthesis sensitivity analysis will be undertaken. Data analysis will follow the thematic synthesis method. Ethics and dissemination: The study does not require ethical approval as primary data will not be collected. The results of the study will be published in a peer-reviewed journal and presented at relevant conferences.

A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^