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antropologiaNet, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
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OpenGraphiti : Data Visualization Framework | #SNA #open #dataviz

OpenGraphiti : Data Visualization Framework | #SNA #open #dataviz | e-Xploration | Scoop.it
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Description

OpenGraphiti is a free and open source 3D data visualization engine for data scientists to visualize semantic networks and to work with them. It offers an easy-to-use API with several associated libraries to create custom-made datasets. It leverages the power of GPUs to process and explore the data and sits on a homemade 3D engine.

 

YOUTUBE: https://www.youtube.com/watch?v=TE9qsYBu8MM

 

 

 

 

 

 

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Lincoln #Logarithms: Finding Meaning in Sermons | #dataviz #sna #DH

Lincoln #Logarithms: Finding Meaning in Sermons | #dataviz #sna #DH | e-Xploration | Scoop.it
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The content and the tools


We explored the power and possibility of four digital tools—MALLET, Voyant, Paper Machines, andViewshare.  MALLET, Paper Machines, and Voyant all examine text.  They show how words are arranged in texts, their frequency, and their proximity. Voyant and Paper Machines also allow users to make visualizations of word patterns. Viewshare allows users to create timelines, maps, and charts of bodies of material. In this project, we wanted to experiment with understanding what these tools, which are in part created to reveal, could and could not show us in a small, but rich corpus.  What we have produced is an exploration of the possibilities and the constraints of these tools as applied to this collection.

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Exemple de #visualisation Web d’une #ontologie simple | #Objets Numériques et #Sémantique

Exemple de #visualisation Web d’une #ontologie simple | #Objets Numériques et #Sémantique | e-Xploration | Scoop.it

Via @backbook
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Pour avancer sur cette idée, nous avons choisi l’ontologie de Bloom que nous avons créée dans le cadre du projet ILOT (voir cet article). Dans son état actuel, il s’agit principalement d’un thésaurus, qui aurait pu être représenté en SKOS, mais, qui, pour des raisons liées au déroulement du projet ILOT, a été réalisée sous forme d’une ontologie OWL, exploitant une partie du vocabulaire de SKOS. Clairement, il s’agit d’un arbre composant un vocabulaire avec des concepts/mots généraux et une hiérarchie de mots limitant le champs du concept.

 

L’ontologie est disponible ici.

 

Pour l’affichage Web d’un arbre, nous avons rapidement identifié la librairie javascript d3.js comme étant fiable et facilement adaptable,offrant diverses possibilités pour l’affichage de données arborescentes.

 

d3.js offre des fonctionnalités intéressantes pour charger des données décrites dans une structure json et les afficher. Pour cela, on va partir d’un modèle d’affichage d’arbre avec un fonctionnement par défaut de l’objet tree, qui suppose une structure bien définie de l’objet json, mais qui repose sur des méthodes que l’on peut redéfinir. En première approche, il suffit de redéfinir deux méthodes:

 

children, qui partant d’un nœud renvoie une table de ses fils directs,une fonction qui renvoie le label à afficher pour un nœud donné. 

Nous y reviendrons une fois générée la structure JSON que nous allons utiliser.

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La Fable des Abeilles | #CollectiveIntelligence #semantic via @plevy

La Fable des Abeilles | #CollectiveIntelligence #semantic via @plevy | e-Xploration | Scoop.it
La fable des abeilles de l'ère industrielle En 1714, Bernard de Mandeville donna le coup d'envoi de la réflexion sur l'économie capitaliste industrielle en train de naître en Angleterre par la publ...
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La fable des abeilles sémantiques


Sur une planète de science-fiction, des humains vivent en symbiose avec des abeilles sémantiques. Lorsque les gens cherchent, rêvent, lisent, écrivent, apprennent, dialoguent, s’amusent et joutent dans le monde extérieur, la pensée de chacun d’eux, de chacune d’elles, se reflète par le vol d’une abeille dans un monde sémantique. Les voyages des abeilles dans leur monde obéissent instantanément aux pensées humaines et les pensées humaines en retour sont informées par l’expérience des abeilles dans leur monde sémantique.

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Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis I #dataviz #semantic #similarity

Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis I #dataviz #semantic #similarity | e-Xploration | Scoop.it
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Statistical topic models can help analysts discover patterns in large text corpora by identifying recurring sets of words and enabling exploration by topical concepts. However, understanding and validating the output of these models can itself be a challenging analysis task. In this paper, we offer two design considerations - interpretation and trust - for designing visualizations based on data-driven models. Interpretation refers to the facility with which an analyst makes inferences about the data through the lens of a model abstraction. Trust refers to the actual and perceived accuracy of an analyst's inferences. These considerations derive from our experiences developing the Stanford Dissertation Browser, a tool for exploring over 9,000 Ph.D. theses by topical similarity, and a subsequent review of existing literature. We contribute a novel similarity measure for text collections based on a notion of "word-borrowing" that arose from an iterative design process. Based on our experiences and a literature review, we distill a set of design recommendations and describe how they promote interpretable and trustworthy visual analysis tools.

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WORDij Semantic Network Tools

WORDij Semantic Network Tools | e-Xploration | Scoop.it
Overview of WORDij WORDij is a family of various programs designed to automate content analysis a substantial amount. The software runs on Windows 32-bit and 64-bit, Mac 32-bit and 64-bit, and Linux 74-bit OS. WORDij runs very efficiently and therfore is fast.This is because the basic tools are written in C++ and optimized considerably. Java is used only for the Graphical User Interface. The suite can run data files as large as 550 megabytes with 8 gigabytes of RAM on a 64-bit machine. Small files with only 10s or 100s of documents can also be effectively analyzed. Files analyzed are in UTF-8 format, so the programs can handle languages with graphic characters such as Chinese or Russian. WordLink, a program that moves a window through text to count word pairs, is proximity based, and therefore is more precise than "bag of words" programs. By using an "include list," the opposite of "drop list or stop list," networks among the included words only can be analyzed.. For example, a list of persons' names can be entered and news documents or meeting notes can be run to find the network of persons based on their co-occurrence closely in texts such as news stories
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Analyse de #sentiments automatique, pourquoi est-ce si compliqué ? | #datascience #lexicometric

Analyse de #sentiments automatique, pourquoi est-ce si compliqué ? | #datascience #lexicometric | e-Xploration | Scoop.it

A l’heure où le big data représente l’un des grands défis technologiques et économiques actuels, de nombreux outils d’analyse se positionnent sur le marché afin d’offrir aux entreprises une connaissance clients davantage poussée.

luiy's insight:

Certaines techniques actuelles font appel à des traitements lexicométriques, mêlant analyses linguistiques et statistiques. D’autres s’appuient sur des techniques d’apprentissage automatique afin d’améliorer automatiquement les performances des programmes d’analyse au fur et à mesure de leur utilisation.

 

Quelle que soit la méthode utilisée, toutes les subtilités du langage ne peuvent être reconstituées sous forme d’algorithmes pour être reconnues par un système informatique. En effet, la langue comprend différents niveaux d’articulation, chaque niveau comportant son lot de difficultés :

 

- Niveau lexical

- Niveau syntaxique

- Niveau sémantique

- Niveau pragmatique

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Marlowe : Vers un générateur d’expériences de pensée sur des dossiers #complexes | #DH #AI #agents

Marlowe : Vers un générateur d’expériences de pensée sur des dossiers #complexes | #DH #AI #agents | e-Xploration | Scoop.it
Marlowe, Toward A Generator of Thought Experiments on Complex Files: An author, an experimenter and a reviewer of the computer programs, Marlowe and Prospero, contribute in this article, respectively and successively, an extensive and detailed presentation of Marlowe, a report on what it is like to interact with Marlowe and a review of the recently-published work, by the first author, describing the development of Prospero for the Analyse of complex dossiers of texts concerning a social controversy, and Prospero's extension and adaptation with Marlowe to direct natural language dialog with researchers concerning specific complex dossiers.
luiy's insight:

Comme première définition du type d’expériences engendrées par Marlowe, on peut parler de « dialogues avec un ensemble de mémoires externes ». Marlowe (nom de code : MRLW) est en effet dépositaire de structures de représentation et de stocks de connaissances qui permettent de lui déléguer des tâches d’enquête fastidieuses. Ses ressources étant en grande partie externalisées, MRLW peut permettre un travail collectif via le cumul de concepts et d’exemples, de règles et de procédures éprouvées sur différents dossiers. Contrairement au chercheur humain, MRLW peut explorer, et exploiter, sans autre limite que les capacités de la machine qui l’abrite, d’innombrables combinaisons. Comme la restitution pure et simple de l’ensemble des combinaisons ou des chemins possibles n’aurait aucun sens – augmentant considérablement le travail interprétatif du chercheur – le dialogue sert de cadrage, ou plutôt d’espace de négociation des prises pertinentes par lesquelles s’affirme la maîtrise d’un ou de plusieurs dossiers. MRLW joue son rôle de maintien de la réflexivité à partir de quatre grands types de fonctionnalités :

 

- des accès documentés à des informations difficiles à extraire manuellement (c’est-à-dire par la recherche visuelle dans de multiples fenêtres) ;

 

- des opérations d’évaluation et de synthèse offrant des angles de vue diversifiés sur un même corpus ;

 

- des modèles ou des espaces de calcul aidant à éprouver la consistance des interprétations du chercheur ;

 

- des outils de contrôle sur la composition du corpus, le cadre d’analyse et les priorités du chercheur.

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#Open Software for Text Analysis, Text Mining, Text Analytics | #clustering #patterns

#Open Software for Text Analysis, Text Mining, Text Analytics | #clustering #patterns | e-Xploration | Scoop.it
Review of Top 11 Free Software for Text Analysis, Text Mining, Text Analytics ? KH Coder, Carrot2, GATE, tm, Gensim, Natural Language Toolkit, RapidMiner, Unstructured Information Management Architecture, OpenNLP, KNIME, Orange-Textable and LPU are some of the key vendors who provides text analytics software

Via ukituki
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What is Chat, Twitter, text messaging and instant messaging abbreviations? - Definition I #semantic #cyberculture

This is a long list of abbreviations used in e-mail and online chatting. Chat abbreviations are commonly used in e-mail, online chatting, online discussion forum postings, instant messaging, and in text messaging, especially between cell phone users.
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AbbreviationMeaning<3heart404I haven't a clueA3Anyplace, anywhere, anytimeADNAny day nowAFAIKAs far as I knowAFKAway from keyboardAREAcronym-rich environmentASAPAs soon as possible
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#Socientize as e-Infrastructure through technology, innovation and creativity I #Science #semantic

#Socientize as e-Infrastructure through technology, innovation and creativity I #Science #semantic | e-Xploration | Scoop.it
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Citizen science is an innovative concept to involve the general public in scientific processes. One of the best ways to help people understand science is by letting them participate in scientific research and experiments. This is what citizen science tries to achieve.

Citizen science is an innovative concept to involve the general public in scientific processes. One of the best ways to help people understand science is by letting them participate in scientific research and experiments. This is what citizen science tries to achieve.

 

The SOCIENTIZE project will coordinate all agents involved in the citizen science process, setting the basis for this new open science paradigm. The project will promote the usage of science infrastructures composed of dedicated and external resources, including professional and amateur scientists. SOCIENTIZE will set-up a network where infrastructure providers and researchers will recruit volunteers from a general public to perform science at home.

Individual citizens will contribute to scientific studies with their own knowledge and resources participating in an active way. Citizens will be donors by connecting their own computing resources, such us smart phones, desktop computers or other devices to science infrastructure. But, citizens will also be actors when they actively participate in the scientific process, in different phases: from short and easy activities to the inception of new research lines, leading people driven developments or in the development of software components, similar to open-source communities. We propose to open e-science to the people, even considering the knowledge and the time of the citizen scientists as part of the resources that constitute the e-infrastructures, and call this enhanced citizen-based infrastructure “c-infrastructure”.

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lapdftext - Layout-Aware Text #Extraction from Full-text PDF of Scientific Articles | #semantic #scientometrics

lapdftext - Layout-Aware Text #Extraction from Full-text PDF of Scientific Articles | #semantic #scientometrics | e-Xploration | Scoop.it
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Publications

 

If you use LA-PDFText in your project, please cite us as follows:

Ramakrishnan, C., A. Patnia, E. Hovy and G. Burns (2012). "Layout-Aware Text Extraction from Full-text PDF of Scientific Articles."Source Code for Biology and Medicine 7(1): 7. [http://www.scfbm.org/content/7/1/7/abstract]

 

Introduction

 

The Portable Document Format (PDF) is the almost universally used file format for online scientific publications. It is also notoriously difficult to read and handle computationally, presenting challenges for developers of biomedical text mining or biocuration informatics systems that use the published literature as an information source. To facilitate the effective use of scientific literature in such systems we introduce Layout-Aware PDF Text Extraction (LA-PDFText).

See Overview for a list of commands that you can execute with this tool. This includes simple and more detailed text extraction from PDF files.

 

LA-PDFText has been developed by members of the Biomedical Knowledge Engineering group @ the Information Sciences Institute. It is intended for use both scientists and NLP engineers interested in getting access to text within specific sections of research articles. The system is open-source and provides a simple baseline function for extracting text from primary research articles using rules that developers can customize. This means that the system works quite well for most applications (and might occasionally make mistakes and extract the wrong text), but it is always possible to 'hack' your own rules and improve performance.

 

For questions about future development or support of the current tool, please contact Gully Burns (gully@usc.edu). For discussions concerning the work contributing to this project, please contact any of the research team: Gully Burns, Cartic

 

Ramakrishnan (rcartic@gmail.com) or Ed Hovy (hovy@isi.edu).

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