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Smart Minds Wanted

New Internship Opportunity @

In conjunction with Springer Nature,  DBpedia offers a 3 months internship at Springer Nature in London, UK and at DBpedia in Leipzig, Germany.

Internship Details

Position DBpedia Intern
Main Employer DBpedia Association
Deadline June 30th, 2017
Duration 3 months/full-time, internship will starts in the second half of 2017
Location 50% in London (UK) and 50% in Leipzig (GER)
Type of students desired Undergraduate, Graduate (Junior role)
Compensation You will receive a stipend of 1300€ per month and additional reimbursement of your travel and visa costs (total up to 1000€)

The student intern will be responsible for assisting with mappings for DBpedia at SpringerNature. Your tasks include and are not restricted to improving the quality of the extraction mechanism of DBpedia scholarly references/wikipedia citations to Springer Nature URIs and Text mining of DBpedia entities from Springer Nature publication content.

Did we spark your interest? Check  our website for further information or apply directly via our online application form

We are looking forward to meet all the whiz kids out there.

Your

DBpedia Association

GSoC 2017- may the code be with you

GSoC students have finally been selected.

We are very excited to announce this year’s final students for our projects  at the Google Summer of Code program (GSoC).

Google Summer of Code is a global program focused on bringing more student developers into open source software development. Stipends are awarded to students to work on a specific DBpedia related project together with a set of dedicated mentors during summer 2017 for the duration of three months.

For the past 5 years DBpedia has been a vital part of the GSoC program. Since the very first time many Dbpedia projects have been successfully completed.

In this years GSoC edition, DBpedia received more than 20 submissions for selected DBpedia projects. Our mentors read many promising proposals, evaluated them and now the crême de la crême of students snatched a spot for this summer.  In the end 7 students from around the world were selected and will jointly work together with their assigned mentors on their projects. DBpedia developers and mentors are really excited about this 7 promising student projects.

List of students and projects:

You want to read more about their specific projects? Just click below… or check GSoC pages for details.

 Ismael Rodriguez – Project Description: Although the DBPedia Extraction Framework was adapted to support RML mappings thanks to a project of last year GSoC, the user interface to create mappings is still done by a MediaWiki installation, not supporting RML mappings and needing expertise on Semantic Web. The goal of the project is to create a front-end application that provides a user-friendly interface so the DBPedia community can easily view, create and administrate DBPedia mapping rules using RML. Moreover, it should also facilitate data transformations and overall DBPedia dataset generation. Mentors: Anastasia Dimou, Dimitris Kontokostas, Wouter Maroy 

Ram Ganesan Athreya – Project Description:The requirement of the project is to build a conversational Chatbot for DBpedia which would be deployed in at least two social networks.There are three main challenges in this task. First is understanding the query presented by the user, second is fetching relevant information based on the query through DBpedia and finally tailoring the responses based on the standards of each platform and developing subsequent user interactions with the Chatbot.Based on my understanding, the process of understanding the query would be undertaken by one of the mentioned QA Systems (HAWK, QANARY, openQA). Based on the response from these systems we need to query the DBpedia dataset using SPARQL and present the data back to the user in a meaningful way. Ideally, both the presentation and interaction flow needs to be tailored for the individual social network.I would like to stress that although the primary medium of interaction is text, platforms such as Facebook insist that a proper mix between chat and interactive elements such as images, buttons etc would lead to better user engagement. So I would like to incorporate these elements as part of my proposal.

Mentor: Ricardo Usbeck

 

Nausheen Fatma – Project discription:  Knowledge base embeddings has been an active area of research. In recent years a lot of research work such as TransE, TransR, RESCAL, SSP, etc. has been done to get knowledge base embeddings. However none of these approaches have used DBpedia to validate their approach. In this project, I want to achieve the following tasks: i) Run the existing techniques for KB embeddings for standard datasets. ii) Create an equivalent standard dataset from DBpedia for evaluations. iii) Evaluate across domains. iv) Compare and Analyse the performance and consistency of various approaches for DBpedia dataset along with other standard datasets. v)Report any challenges that may come across implementing the approaches for DBpedia. Along the way, I would also try my best to come up with any new research approach for the problem.

Mentors: Sandro Athaide Coelho, Tommaso Soru

 

Akshay Jagatap – Project Description: The project aims at defining embeddings to represent classes, instances and properties. Such a model tries to quantify semantic similarity as a measure of distance in the vector space of the embeddings. I believe this can be done by implementing Random Vector Accumulators with additional features in order to better encode the semantic information held by the Wikipedia corpus and DBpedia graphs.

Mentors: Pablo Mendes, Sandro Athaide Coelho, Tommaso Soru

 

Luca Virgili –  Project Description: In Wikipedia a lot of data are hidden in tables. What we want to do is to read correctly all tables in a page. First of all, we need a tool that can allow us to capture the tables represented in a Wikipedia page. After that, we have to understand what we read previously. Both these operations seem easy to make, but there are many problems that could arise. The main issue that we have to solve is due to how people build table. Everyone has a particular style for representing information, so in some table we can read something that doesn’t appear in another structure. In this paper I propose to improve the last year’s project and to create a general way for reading data from Wikipedia tables. I want to review the parser for Wikipedia pages for trying to understand more types of tables possible. Furthermore, I’d like to build an algorithm that can compare the column’s elements (that have been read previously by the parser) to an ontology so it could realize how the user wrote the information. In this way we can define only few mapping rules, and we can make a more generalized software.

Mentors: Emanuele Storti, Domenico Potena

 

Shashank Motepalli – Project Description: DBpedia tries to extract structured information from Wikipedia and make information available on the Web. In this way, the DBpedia project develops a gigantic source of knowledge. However, the current system for building DBpedia Ontology relies on Infobox extraction. Infoboxes, being human curated, limit the coverage of DBpedia. This occurs either due to lack of Infoboxes in some pages or over-specific or very general taxonomies. These factors have motivated the need for DBTax.DBTax follows an unsupervised approach to learning taxonomy from the Wikipedia category system. It applies several inter-disciplinary NLP techniques to assign types to DBpedia entities. The primary goal of the project is to streamline and improve the approach which was proposed. As a result, making it easy to run on a new DBpedia release. In addition to this, also to work on learning taxonomy of DBTax to other Wikipedia languages.

Mentors: Marco Fossati, Dimitris Kontokostas

 

Krishanu Konar – Project Description: Wikipedia, being the world’s largest encyclopedia, has humongous amount of information present in form of text. While key facts and figures are encapsulated in the resource’s infobox, and some detailed statistics are present in the form of tables, but there’s also a lot of data present in form of lists which are quite unstructured and hence its difficult to form into a semantic relationship. The project focuses on the extraction of relevant but hidden data which lies inside lists in Wikipedia pages. The main objective of the project would be to create a tool that can extract information from wikipedia lists, form appropriate RDF triplets that can be inserted in the DBpedia dataset.

Mentor: Marco Fossati 

Read more

Congrats to all selected students! We will keep our fingers crossed now and patiently wait until early September, when final project results are published.

An encouraging note to the less successful students.

The competition for GSoC slots is always on a very high level and DBpedia only has a limited amount of slots available for students.  In case you weren’t among the selected, do not give up on DBpedia just yet. There are plenty of opportunities to prove your abilities and be part of the DBpedia experience. You, above all, know DBpedia by heart. Hence, contributing to our support system is not only a great way to be part of the DBpedia community but also an opportunity to be vital to DBpedia’s development. Above all, it is a chance for current DBpedia mentors to get to know you better. It will give your future mentors a chance to  support you and help you to develop your ideas from the very beginning.

Go on you smart brains, dare to become a top DBpedia expert and provide good support for other DBpedia Users. Sign up to our support page  or check out the following ways to contribute:

Get involved:
  • Join our DBpedia-discussion -mailinglist, where we discuss current DBpedia developments. NOTE: all mails announcing tools or call to papers unrelated to DBpedia are not allowed. This is a community discussion list.
  • If you like to join DBpedia developers discussion and technical discussions sign up in Slack
  • Developer Discussion
  • Become a DBpedia Student and sign up for free at the DBpedia Association. We offer special programs that provide training and other opportunities to learn about DBpedia and extend your Semantic Web and programming skills

We are looking forward to working with you!

You don’t have enough of DBpedia yet? Stay tuned and join us on facebook, twitter or subscribe to our newsletter for the latest news!

 

Have a great weekend!

Your

DBpedia Association

DBpedia+Spotlight accepted @ Google Summer of Code 2013

Google Summer of Code (GSoC) is a global program that offers post-secondary student developers (ages 18 and older, BSc, MSc, PhD)  stipends to write code for various open source software projects. Since its inception in 2005, the program has brought together over 6,000 successful student participants and over 3,000 mentors from over 100 countries worldwide, all for the love of code.

DBpedia participated successfully in last’s year GSoC as DBpedia Spotlight. We were allowed with 4 students (out of a total 37 applications) and managed to enhance DBpedia Spotlight in time performance, accuracy and extra functionality.  We are thrilled to announce, that we were accepted again in GSoC 2013. We are participating with all DBpedia-family products this time – that is DBpedia, DBpedia Spotlight and DBpedia Wiktionary – and we hope we share the same luck, again.

This year we have  brand new and exciting ideas so, if you know energetic students (BSc, MSc, PhD) interested in working with DBpedia, text processing, and semantics, please encourage them to apply!

If you are a student, the application period starts in 2 weeks (deadline May 3rd). Judging from last year’s competition, writing a good application can be a really hard task so you should start preparing from now. We already created a dedicated mailing list and a few  warm-up tasks ( to get you familiar with our technologies) and we will of course be always available to any questions.

So go ahead, choose your idea, write your application and impress us;)

http://www.google-melange.com/gsoc/org/google/gsoc2013/dbpediaspotlight

On behalf of the DBpedia GSoC team,

Dimitris Kontokostas

OpenData Challenge awards 20.000€ prizes to open public data apps

European public bodies produce thousands upon thousands of datasets every year – about everything from how our tax money is spent to the quality of the air we breathe.

The Opendata competition aims to challenge designers, developers, journalists, researchers and the general public to come up with something useful, valuable or interesting using open public data.

There are four main strands to the competition:

  • Ideas – Anyone can suggest an idea for projects which reuse public information to do something interesting or useful.
  • Apps – Teams of developers can submit working applications which reuse public information.
  • Visualisations – Designers, artists and others can submit interesting or insightful visual representations of public information.
  • Datasets – We encourage the submission of any form of open datasets produced by public governmental bodies, either submitted directly by the public body or by developers or others who have transformed, cleaned or interlinked the data.
  •  

    The competition is open til 5th June midnight. The winners will be selected by an all star cast of open data gurus – and announced in mid June at the European Digital Assembly in Brussels. More information can be found at: http://opendatachallenge.org/

    DBpedia 3.6 AMI Available

    In line with prior releases of DBpedia, there is a new 3.6 edition of the DBpedia AMI available from Amazon EC2.

    What is a DBpedia AMI?

    A preconfigured Virtuoso Cluster Edition database that includes a preloaded DBpedia dataset. The entire deliverable is packaged as an Amazon Machine Instance (AMI); which is a cloud hosted virtual machine.

    Why is it Important?

    It enables you to productively exploit the power of the DBpedia within minutes. Basically, you can make DBpedia instances that serve you personal or service  specific needs. Thus, you do not have to constrain your use of DBpedia via the live instance which is configured for Web Scale use, based on server side constraints that affect concurrent connections, query timeouts, and result set sizes.

    How do I use it?

    Simply follow the instructions in the DBpedia AMI guide which boils down to:

    1. Instantiating a Virtuoso EC2 AMI
    2. Mounting the Amazon Elastic Block Storage (EBS) snapshot that hosts the preloaded Virtuoso Database.

    Enjoy!

    DBpedia in ReadWriteWeb’s Top 10 Semantic Web Products of 2009

    The new year is slowly approaching and people start compiling their top x lists of 2009, with x usually ranging between 10 and 365. 😉

    The popular Web technology blog ReadWriteWeb has chosen x with value 10 and picked DBpedia as one of their top Semantic Web products of 2009. Its actually the only non-commercial community project in the list and in good company with products such as Google’s Search Options and Rich Snippets, Apperture and Data.gov. Other picks, which btw. heavily use or link to DBpedia, include OpenCalais, Freebase, BBC Music and Zemanta.

    Read the full article at http://www.readwriteweb.com/archives/top_10_semantic_web_products_of_2009.php

    Want to bring your Blog, Wiki, WebApp to the Semantic Web?

    DBpedia exposes semantics extracted from one of the largest information sources on the Web. But one of the nice things about the Web is the variety and wealth of content (including your Blog, Wiki, CMS or other WebApp). In order to make this large variety of small Websites better mashable and bring them on the Semantic Web the makers of DBpedia released technologies, which dramatically simplify the “semantification” of your Websites. Please check out Triplify (a generic plugin for Webapps with preconfigurations for Drupal, WordPress, WackoWiki), D2RQ (a Java software for mapping and serving relational DB content for the Semantic Web) and Virtuoso (a comprehensive DB, knowledge store infrastructure).

    flickr photo collection links added to DBpedia

    Christian Becker (Freie Universität Berlin) has implemented a wrapper around flickr which generates photo collections depicting DBpedia concepts. See flickr wrappr for details. We have interlinked all DBpedia concepts with the corresponding photo collections. You can now use any Semantic Web browser to navigate from a DBpedia concept to flickr  photos depicting it by following the dbpedia:hasPictureCollection property. This means an additional 30-50 million photos are accessible through DBpedia.

    For example, click on the URIs below or paste them into your Semantic Web browser:

    Photos depicting Brandenburg Gate: http://www4.wiwiss.fu-berlin.de/flickrwrappr/photos/Brandenburg_Gate
    DBpedia URI for Brandenburg Gate : http://dbpedia.org/resource/Brandenburg_Gate