International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

COMPARISON OF GRUFF 5.5.0 AND GRUFF 5.6.1 ON ALLEGROGRAPH 3.3 USING SAME TRIPLESTORE Mradula Singh Computer science and engineering, Shri Vaishnav Institute of Technology and Science Indore (M.P), India Pallavi Jain Assistant Prof., Computer science and engineering, Shri Vaishnav Institute of Technology and Science Indore (M.P), India

ABSTRACT A wide range of RDF (Resource Description Framework) tools are available. All have different features and highlight different aspect of RDF. Tools concentrate on programming environment, graphical representation and some act as a triple store. AllegroGraph is a triplestore or RDF Database and Gruff is custom browser available for viewing graphs. In this paper two versions of Gruff are compared using same triplestore. Few queries are performed to see which version gives better result. Keywords—Resource Description Framework (RDF), Allegrograph , Gruff 5.5.0, Gruff 5.6.1, SPARQL;

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

I. INTRODUCTION RDF is said to be a very flexible technology which can address wide range of problems. RDF is a data model which shows information in subject – predicate – object form. We can combine many statements together by matching their subjects and objects (nodes). Predicated are lines that join these subjects and objects together. This whole representation forms a “Triple”. When all statements are converted in node–edge–node format (triples) they form a network which is known as RDF graph. RDF is a framework, data model for making complex vocabularies. RDF data is stored in triplestore. It is a framework for storing and querying RDF data. The numbers of triple stores have increased, from Jena and Sesame to AllegroGraph, BigOWLIM, Jena TDB, Jena SDB, Virtuoso, BigData, Mulgara, Sesame, 3Store and RDF Gateway etc. II. ALLEGROGRAPH AllegroGraph is a said to be a closed source triplestore designed to store RDF triples. To view and query this triplestore AllegroGraph provides us with a custom browser named “GRUFF”. It is easy to use and can accept various serialization formats of RDF. AllegroGraph is used in Open Source Projects, commercial projects etc. To query RDF data we have a standard query language called SPARQL. AllegroGraph server 4 runs on x86-64 bit machine, for which we have to set up Linux Virtual machine on OS (Windows or Mac). And for other 64-bit Mac, Windows, Solaris, and all 32-bit systems we have AllegroGraph 3.3.

Fig. 1. Representation of RDF triple In fig.1 there is a company named HUL (HINDUSTAN UNILIVER LIMITED) (Subject) whose website (Predicate) is www.hul.co.in (Object). But when we write this information in Ntriple format is written as follows: .

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

This information is loaded in Gruff and we can see the Graphical view of the triple as shown in Fig.1. III. GRUFF Gruff is a triplestore browser which is very interactive, it shows triplestore data in graphical form. It has query manager and editor which are built in AllegroGraph. Queries can be written in SPARQL and code. It also enables user to query triplestore by designing queries graphically with nodes and links. Gruff has many views in which we can see the triplestore. Some of which are: The Graph View, The Table View, The Outline View, The Query View, The Graphical Query View. In every view you can use different features of Gruff and query data. Gruff is very user-friendly and can be learned very easily. Creating a triple store in Gruff is also very easy. You just need to classify information in Subject-Predicate-Object form. 1. THE GRAPH VIEW: Graph view is used to see visual graphs of nodes connected with links. All the links are displayed with different colors. Subjects and objects are of different colors.

Fig. 2. The Graph View Of Gruff

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

2. THE TABLE VIEW: Table view is for listing nodes and we can also edit the properties of nodes here

Fig. 3. The Table View Of Gruff 3. THE OUTLINE VIEW: Outline view is for viewing parts of a graph. We can create whole triplestore from a scratch using this view.

Fig. 4. The Outline View Of Gruff

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

4. THE QUERY VIEW: Query view is for querying triplestore with SPARQL or Prolog code and viewing result. We can save the result obtained as CSV file. We can also create its report.

Fig. 5. The Query View Of Gruff 5. THE GRAPHICAL QUERY VIEW: Graphical view allows user to design queries as diagrams of nodes and links

Fig. 6. The Graphical Query View of Gruff

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

Query generated with above graphical query and its reslt can be seen in Query view.

Fig. 7. Result of Graphical Query View in Gruff IV. COMPARISON OF GRUFF 5.5.0 AND GRUFF 5.6.1 Here we are comparing two versions of Gruff on the basis of their response time. We have listed 10 queries below with their execution time.

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

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International Journal of Research in Management, Economics & Commerce Impact Factor: 5.662, ISSN 2250-057X, Volume 5 Issue 5, May 2015 Website: www.indusedu.org

CONCLUSION Here we have performed these queries on same data and we recorded their execution time from both the versions. We can clearly see that at some places Gruff 5.6.1 is taking lesser time than Gruff 5.5.0 and Gruff 5.6.1 produces result in systematic order which lacks in Gruff 5.5.0. Rest all the features are more or less same. ACKNOWLEDGMENT I would like to thank whole Computer Science Department of Shri Vaishnav Institute of Technology and Science Indore (M.P) for all of its support. I would also like to thank my guide Miss Pallavi Jain for her efforts and guidance. REFERENCES 1. http://en.m.wikipedia.org/wiki/AllegroGraph 2. Shelley Powers, “Practical RDF”, First edition 2003, pp.1-20. 3. en.wikipedia.org/wiki/SPARQL. 4. http://www.w3.org/TR/rdf-concepts/ 5. http://www.w3.org/TR/2004/REC-rdf-concepts-20040210/ 6. Bob DuCharme “Learning Sparql” First Edition 2011, pp 1-5. 7. http://www.mkbergman.com/483/advantages-and-myths-of-rdf/

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