![]() A few months ago we released Docear4Word.Of all the free options, Mendeley has arguably the best tools for library management, including tools for automatically naming and organizing PDF files. Docear4Word is an add-on for Microsoft Word that allows you to insert and format citations and bibliographies very easily in MS Word. Many of our users love Docear4Word. However, not all of our users are using Microsoft Word but many are using OpenOffice or LibreOffice. One of them is Stephen from Uberstudent which is a Linux distribution for learners. Stephen, as many others, urged us to develop an add-on, comparable to Docear4Word, for Libre of OpenOffice. Unfortunately, we don’t have the expertise to do this. Do you have experience in developing add-ons for LibreOffice and/or OpenOffice? Then, please contact us. We have prepared a description of what Docear4Libre/OpenOffice should be able to do. Read it carefully, and tell us how long you would need to implement it. And don’t forget to tell us how much money you would want for it. Exactly, we are not expecting you to do it for free. We would be willing to pay something for it. Once we found an appropriate developer we will ask our users to donate for Docear4Libre/OpenOffice and give a good amount ourselves. ![]() Also Stephen will ask the users from Uberstudent to donate. Since March, Docear offers a simple web-based mind map viewer, developed with some of our volunteering students, and supported by the Freeplane team. On next Friday, July 12th, at 10:30am the students will present their final work at the HTW in Berlin. You are sincerely invited to join the presentation and be first to see Docear’s new collaboration and synchronization feature. ![]() The work is not yet ready to be released to the public but we hope to completely finish the work in the next few months. However, even the preview is really amazing! Compared to the current online viewer the new “Docear Web” offers lots of features. First of all, you can edit your mind maps online and not only on your own but together with your colleagues. The collaboration works both with your local desktop Docear and with your web-based Docear. That means, you can just start Docear Desktop as you are used to and colleagues of you may work on the same mind maps you are editing either on the Web or with Docear Desktop as well. Collaboration is in real-time, similarly to Google Docs. In addition, there is a Dropbox-like utility that synchronizes all your data between different devices (and the Web). As said, not everything is already fully functional but the preview version has at least all the basic features and gives you a very good idea what to expect for the final version. The last version of Docear was released three month ago and you might wonder what we were doing. Well, I can tell you we were really busy. Besides working on some research papers for conferences in Indianapolis and on Malta (read here and here), we finally implemented two major milestones for Docear. These two milestones actually were the last ones we had on our road-map for releasing the final 1.0 version of Docear. And here it is, Docear 1.0 (RC 1) with: 1. We have completely redesigned the dialog that appears when Docear is first started. We believe it to be much more user friendly and intuitive. We also listened to those users who criticized that our terms of service had to be accepted even when no online services were activated. You can either use Docear as a registered user and enjoy the full potential including PDF metadata retrieval, online backup, online mind map viewer, and recommendations. Or you can use Docear as a local user with no data at all being submitted to Docear and no requirement for accepting any terms of service (just use Docear as you would use any other GPL desktop software).Īfter three demo-papers were accepted for JCDL 2013, we just received notice that another three posters were accepted for presentation at TPDL 2013 on Malta in September 2013. ![]() They cover some novel aspects of recommender systems relating to re-showing recommendations multiple times, considering user demographics when evaluating recommender systems, and investigating the effect of labelling recommendations.
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