Dr. Diego Collarana

Dr. Diego Collarana left SDA. The profile below reflects the status at the point of his departure and is no longer updated.

Senior Research Engineer
Enterprise Information Systems
Fraunhofer IAIS

Profiles: LinkedIn, DBLP

Schloss Birlinghoven, 53757 Sankt Augustin, Germany

collaran@iai.uni-bonn.de

Short CV

Dr. Diego Collarana is a Senior Research Engineer at the Enterprise Information Systems of the Fraunhofer IAIS.

Research Interests

Semantic Web,
Linked Data, Web and Mobile applications for enterprises
Knowledge Engineering

Projects

LiDaKrAv
EDSA
VISTRA – Proect Development of a Picture Archiving and Communication System PACS

Publications

2022

Knoblach, Judith; Acharya, Nikhil; Koranemkattil, Bhavya; Both, Andreas; Collarana, Diego

Combining Knowledge Graphs and Language Models to Answer Questions over Tables Inproceedings

In: Proceedings of Poster and Demo Track and Workshop Track of the 18th International Conference on Semantic Systems co-located with 18th International Conference on Semantic Systems (SEMANTiCS 2022), Vienna, Austria, September 13th to 15th, 2022, CEUR-WS.org, 2022.

Westphal, Patrick; Grubenmann, Tobias; Collarana, Diego; Bin, Simon; Bühmann, Lorenz; Lehmann, Jens

Spatial concept learning and inference on geospatial polygon data Journal Article

In: Knowl. Based Syst., vol. 241, pp. 108233, 2022.

2021

Wilhelm, Nico; Collarana, Diego; Lehmann, Jens

A Virtual Knowledge Graph for Enabling Defect Traceability and Customer Service Analytics Inproceedings

In: The Semantic Web: ESWC 2021 Satellite Events - Virtual Event, June 6-10, 2021, Revised Selected Papers, pp. 245–248, Springer, 2021.

Graux, Damien; Collarana, Diego; Orlandi, Fabrizio

Formal Concept Analysis for Semantic Compression of Knowledge Graph Versions Inproceedings

In: Proceedings of the 9th International Workshop "What can FCA do for Artificial Intelligence?" co-located with the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), Montréal, Québec, Canada, August 21, 2021, pp. 131–138, CEUR-WS.org, 2021.

Sadeghi, Afshin; Malik, Hirra; Collarana, Diego; Lehmann, Jens

Relational Pattern Benchmarking on the Knowledge Graph Link Prediction Task Inproceedings

In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021, December 2021, virtual, 2021.

Sadeghi, Afshin; Collarana, Diego; Graux, Damien; Lehmann, Jens

Embedding Knowledge Graphs Attentive to Positional and Centrality Qualities Inproceedings

In: Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part II, pp. 548–564, Springer, 2021.

Rivas, Ariam; Grangel-González, Irlán; Collarana, Diego; Lehmann, Jens; Vidal, Maria-Esther

Discover Relations in the Industry 4.0 Standards Via Unsupervised Learning on Knowledge Graph Embeddings Journal Article

In: J. Data Intell., vol. 2, no. 3, pp. 326–347, 2021.

2020

Iglesias, Enrique; Jozashoori, Samaneh; Chaves-Fraga, David; Collarana, Diego; Vidal, Maria-Esther

SDM-RDFizer: An RML Interpreter for the Efficient Creation of RDF Knowledge Graphs Inproceedings

In: CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020, pp. 3039–3046, ACM, 2020.

Rivas, Ariam; Grangel-González, Irlán; Collarana, Diego; Lehmann, Jens; Vidal, Maria-Esther

Unveiling Relations in the Industry 4.0 Standards Landscape Based on Knowledge Graph Embeddings Inproceedings

In: Database and Expert Systems Applications - 31st International Conference, DEXA 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings, Part II, pp. 179–194, Springer, 2020.

Arispe, Martin; Tasnim, Mayesha; Graux, Damien; Orlandi, Fabrizio; Collarana, Diego

Verbalizing the Evolution of Knowledge Graphs with Formal Concept Analysis Inproceedings

In: Joint Proceedings of Workshops AI4LEGAL2020, NLIWOD, PROFILES 2020, QuWeDa 2020 and SEMIFORM2020 Colocated with the 19th International Semantic Web Conference (ISWC 2020), Virtual Conference, November, 2020, pp. 72–79, CEUR-WS.org, 2020.

Tasnim, Mayesha; Collarana, Diego; Graux, Damien; Vidal, Maria-Esther

Context-Based Entity Matching for Big Data Incollection

In: Knowledge Graphs and Big Data Processing, vol. 12072, pp. 122–146, Springer, 2020.

2019

Tasnim, Mayesha; Collarana, Diego; Graux, Damien; Galkin, Mikhail; Vidal, Maria-Esther

COMET: A Contextualized Molecule-Based Matching Technique Inproceedings

In: Database and Expert Systems Applications - 30th International Conference, DEXA 2019, Linz, Austria, August 26-29, 2019, Proceedings, Part I, pp. 175–185, Springer, 2019.

Bajwa, Awais Manzoor; Collarana, Diego; Vidal, Maria-Esther

Interaction Network Analysis Using Semantic Similarity Based on Translation Embeddings Inproceedings

In: Semantic Systems. The Power of AI and Knowledge Graphs - 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9-12, 2019, Proceedings, pp. 249–255, Springer, 2019.

Nejad, Najmeh Mousavi; Graux, Damien; Collarana, Diego

Towards Measuring Risk Factors in Privacy Policies Inproceedings

In: Proceedings of the Workshop on Artificial Intelligence and the Administrative State co-located with 17th International Conference on AI and Law (ICAIL 2019), Montreal, QC, Canada, June 17, 2019, pp. 18–20, CEUR-WS.org, 2019.

Tasnim, Mayesha; Collarana, Diego; Graux, Damien; Orlandi, Fabrizio; Vidal, Maria-Esther

Summarizing Entity Temporal Evolution in Knowledge Graphs Inproceedings

In: Companion of The 2019 World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019, pp. 961–965, ACM, 2019.

Vargas, Diego Collarana

Strategies and Techniques for Federated Semantic Knowledge Retrieval and Integration PhD Thesis

University of Bonn, Germany, 2019, ISBN: 978-1-64368-046-0.

Abstract | Links | BibTeX

@phdthesis{DBLP:phd/dnb/Vargas19,

title = {Strategies and Techniques for Federated Semantic Knowledge Retrieval

and Integration},

author = {Diego Collarana Vargas},

url = {https://doi.org/10.3233/SSW200002-mono},

doi = {10.3233/SSW200002-mono},

isbn = {978-1-64368-046-0},

year = {2019},

date = {2019-01-01},

school = {University of Bonn, Germany},

abstract = {The vast amount of data shared on the Web requires effective and efficient techniques to retrieve and create machine usable knowledge out of it. The creation of integrated knowledge from the Web, especially knowledge about the same entity spread over different web data sources, is a challenging task. Several data interoperability problems such as schema, structure, or domain conflicts need to be solved during the integration process. Semantic Web Technologies have evolved as a novel approach to tackle the problem of knowledge integration out of heterogeneous data. However, knowledge retrieval and integration from web data sources is an expensive process, mainly due to the Extraction-Transformation-Load approach that predominates the process. In addition, there are increasingly many scenarios, where a full physical integration of the data is either prohibitive (e.g. due to data being hidden behind APIs) or not allowed (e.g. for data privacy concerns). Thus, a more cost-effective and federated integration approach is needed, a method that supports organizations to create valuable insights out of the heterogeneous data spread on web sources. In this thesis, we tackle the problem of knowledge retrieval an integration from heterogeneous web sources and propose a holistic semantic knowledge retrieval and integration approach that creates knowledge graphs on-demand from a federation of web sources. We focus on the representation of web sources data, which belongs to the same entity, as pieces of knowledge to then synthesize them as knowledge graph solving interoperability conflicts at integration time. First, we propose MINTE, a novel semantic integration approach that solves interoperability conflicts present in heterogeneous web sources. MINTE defines the concept of RDF molecules to represent web sources data as pieces of knowledge. Then, MINTE relies on a semantic similarity function to determine RDF molecules belonging to the same entity. Finally, MINTE employs fusion policies for the synthesis of RDF molecules into a knowledge graph. Second, we define a similarity framework for RDF molecules to identify semantically equivalent entities. The framework includes state-of-the-art semantic similarity metrics, such as GADES, but also a semantic similarity metric based on embeddings named MateTee developed in the scope of this thesis. Ultimately, based on MINTE and our similarity framework, we design a federated semantic retrieval engine named FuhSen. FuhSen is able to effectively integrate data from heterogeneous web data sources and create an integrated knowledge graphs on-demand. FuhSen is equipped with a faceted browsing user interface oriented to facilitate the exploration of on-demand built knowledge graphs. We conducted several empirical evaluations to assess the effectiveness and efficiency of our holistic approach. More importantly, three domain applications, i.e., Law Enforcement, Job Market Analysis, and Manufacturing, have been developed and managed by our approach. Both the empirical evaluations and concrete applications provide evidence that the methodology and techniques proposed in this thesis help to effectively integrate the pieces of knowledge about entities that are spread over heterogeneous web data sources.},

keywords = {},

pubstate = {published},

tppubtype = {phdthesis}

}

The vast amount of data shared on the Web requires effective and efficient techniques to retrieve and create machine usable knowledge out of it. The creation of integrated knowledge from the Web, especially knowledge about the same entity spread over different web data sources, is a challenging task. Several data interoperability problems such as schema, structure, or domain conflicts need to be solved during the integration process. Semantic Web Technologies have evolved as a novel approach to tackle the problem of knowledge integration out of heterogeneous data. However, knowledge retrieval and integration from web data sources is an expensive process, mainly due to the Extraction-Transformation-Load approach that predominates the process. In addition, there are increasingly many scenarios, where a full physical integration of the data is either prohibitive (e.g. due to data being hidden behind APIs) or not allowed (e.g. for data privacy concerns). Thus, a more cost-effective and federated integration approach is needed, a method that supports organizations to create valuable insights out of the heterogeneous data spread on web sources. In this thesis, we tackle the problem of knowledge retrieval an integration from heterogeneous web sources and propose a holistic semantic knowledge retrieval and integration approach that creates knowledge graphs on-demand from a federation of web sources. We focus on the representation of web sources data, which belongs to the same entity, as pieces of knowledge to then synthesize them as knowledge graph solving interoperability conflicts at integration time. First, we propose MINTE, a novel semantic integration approach that solves interoperability conflicts present in heterogeneous web sources. MINTE defines the concept of RDF molecules to represent web sources data as pieces of knowledge. Then, MINTE relies on a semantic similarity function to determine RDF molecules belonging to the same entity. Finally, MINTE employs fusion policies for the synthesis of RDF molecules into a knowledge graph. Second, we define a similarity framework for RDF molecules to identify semantically equivalent entities. The framework includes state-of-the-art semantic similarity metrics, such as GADES, but also a semantic similarity metric based on embeddings named MateTee developed in the scope of this thesis. Ultimately, based on MINTE and our similarity framework, we design a federated semantic retrieval engine named FuhSen. FuhSen is able to effectively integrate data from heterogeneous web data sources and create an integrated knowledge graphs on-demand. FuhSen is equipped with a faceted browsing user interface oriented to facilitate the exploration of on-demand built knowledge graphs. We conducted several empirical evaluations to assess the effectiveness and efficiency of our holistic approach. More importantly, three domain applications, i.e., Law Enforcement, Job Market Analysis, and Manufacturing, have been developed and managed by our approach. Both the empirical evaluations and concrete applications provide evidence that the methodology and techniques proposed in this thesis help to effectively integrate the pieces of knowledge about entities that are spread over heterogeneous web data sources.

2018

Galkin, Mikhail; Collarana, Diego; Vidal, Maria-Esther; Tasnim, Mayesha

Synthesizing a Knowledge Graph of Data Scientist Job Offers with MINTE+ Inproceedings

In: Proceedings of the ISWC 2018 Posters & Demonstrations, Industry and Blue Sky Ideas Tracks co-located with 17th International Semantic Web Conference (ISWC 2018), Monterey, USA, October 8th - to - 12th, 2018, CEUR-WS.org, 2018.

Collarana, Diego; Heuss, Timm; Lehmann, Jens; Lytra, Ioanna; Maheshwari, Gaurav; Nedelchev, Rostislav; Schmidt, Thorsten; Trivedi, Priyansh

A Question Answering System on Regulatory Documents Inproceedings

In: Legal Knowledge and Information Systems - JURIX 2018: The Thirty-first Annual Conference, Groningen, The Netherlands, 12-14 December 2018, pp. 41–50, IOS Press, 2018.

Collarana, Diego; Galkin, Mikhail; Lange, Christoph; Scerri, Simon; Auer, Sören; Vidal, Maria-Esther

Synthesizing Knowledge Graphs from Web Sources with the MINTE ^+ + Framework Inproceedings

In: The Semantic Web - ISWC 2018 - 17th International Semantic Web Conference, Monterey, CA, USA, October 8-12, 2018, Proceedings, Part II, pp. 359–375, Springer, 2018.

2017

Galkin, Mikhail; Collarana, Diego; Ribón, Ignacio Traverso; Vidal, Maria-Esther; Auer, Sören

SJoin: A Semantic Join Operator to Integrate Heterogeneous RDF Graphs Inproceedings

In: Database and Expert Systems Applications - 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part I, pp. 206–221, Springer, 2017.

Galkin, Mikhail; Endris, Kemele M.; Acosta, Maribel; Collarana, Diego; Vidal, Maria-Esther; Auer, Sören

SMJoin: A Multi-way Join Operator for SPARQL Queries Inproceedings

In: Proceedings of the 13th International Conference on Semantic Systems, SEMANTiCS 2017, Amsterdam, The Netherlands, September 11-14, 2017, pp. 104–111, ACM, 2017.

Galkin, Mikhail; Auer, Sören; Vidal, Maria-Esther; Scerri, Simon

Enterprise Knowledge Graphs: A Semantic Approach for Knowledge Management in the Next Generation of Enterprise Information Systems Inproceedings

In: ICEIS 2017 - Proceedings of the 19th International Conference on Enterprise Information Systems, Volume 2, Porto, Portugal, April 26-29, 2017, pp. 88–98, SciTePress, 2017.

Collarana, Diego; Galkin, Mikhail; Ribón, Ignacio Traverso; Lange, Christoph; Vidal, Maria-Esther; Auer, Sören

Semantic Data Integration for Knowledge Graph Construction at Query Time Inproceedings

In: 11th IEEE International Conference on Semantic Computing, ICSC 2017, San Diego, CA, USA, January 30 - February 1, 2017, pp. 109–116, IEEE Computer Society, 2017.

Sibarani, Elisa Margareth; Scerri, Simon; Morales, Camilo; Auer, Sören; Collarana, Diego

Ontology-guided Job Market Demand Analysis: A Cross-Sectional Study for the Data Science field Inproceedings

In: Proceedings of the 13th International Conference on Semantic Systems, SEMANTiCS 2017, Amsterdam, The Netherlands, September 11-14, 2017, pp. 25–32, ACM, 2017.

Collarana, Diego

A Semantic Integration Approach for Building Knowledge Graphs On-Demand Inproceedings

In: Web Engineering - 17th International Conference, ICWE 2017, Rome, Italy, June 5-8, 2017, Proceedings, pp. 575–583, Springer, 2017.

Morales, Camilo; Collarana, Diego; Vidal, Maria-Esther; Auer, Sören

MateTee: A Semantic Similarity Metric Based on Translation Embeddings for Knowledge Graphs Inproceedings

In: Web Engineering - 17th International Conference, ICWE 2017, Rome, Italy, June 5-8, 2017, Proceedings, pp. 246–263, Springer, 2017.

Fuenmayor, Luis; Collarana, Diego; Lohmann, Steffen; Auer, Sören

FaRBIE: A Faceted Reactive Browsing Interface for Multi RDF Knowledge Graph Exploration Inproceedings

In: Proceedings of the Third International Workshop on Visualization and Interaction for Ontologies and Linked Data co-located with the 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, October 22, 2017, pp. 111–122, CEUR-WS.org, 2017.

Collarana, Diego; Galkin, Mikhail; Ribón, Ignacio Traverso; Vidal, Maria-Esther; Lange, Christoph; Auer, Sören

MINTE: semantically integrating RDF graphs Inproceedings

In: Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, WIMS 2017, Amantea, Italy, June 19-22, 2017, pp. 22:1–22:11, ACM, 2017.

2016

Grangel-González, Irlán; Collarana, Diego; Halilaj, Lavdim; Lohmann, Steffen; Lange, Christoph; Vidal, Maria-Esther; Auer, Sören

Alligator: A Deductive Approach for the Integration of Industry 4.0 Standards Inproceedings

In: Knowledge Engineering and Knowledge Management - 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings, pp. 272–287, 2016.

Grangel-González, Irlán; Halilaj, Lavdim; Auer, Sören; Lohmann, Steffen; Lange, Christoph; Collarana, Diego

An RDF-based approach for implementing industry 4.0 components with Administration Shells Inproceedings

In: 21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016, Berlin, Germany, September 6-9, 2016, pp. 1–8, IEEE, 2016.

Collarana, Diego; Galkin, Mikhail; Lange, Christoph; Grangel-González, Irlán; Vidal, Maria-Esther; Auer, Sören

FuhSen: A Federated Hybrid Search Engine for Building a Knowledge Graph On-Demand (Short Paper) Inproceedings

In: On the Move to Meaningful Internet Systems: OTM 2016 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2016, Rhodes, Greece, October 24-28, 2016, Proceedings, pp. 752–761, 2016.

Grangel-González, Irlán; Halilaj, Lavdim; Coskun, Gökhan; Auer, Sören; Collarana, Diego; Hoffmeister, Michael

Towards a Semantic Administrative Shell for Industry 4.0 Components Inproceedings

In: Tenth IEEE International Conference on Semantic Computing, ICSC 2016, Laguna Hills, CA, USA, February 4-6, 2016, pp. 230–237, IEEE Computer Society, 2016.

Collarana, Diego; Lange, Christoph; Auer, Sören

FuhSen: A Platform for Federated, RDF-based Hybrid Search Inproceedings

In: Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Montreal, Canada, April 11-15, 2016, Companion Volume, pp. 171–174, ACM, 2016.

2014

Hess, Steffen; Collarana, Diego; Dörr, Jörg

Requirements Engineering und Konzeption von "Gamified" Apps Journal Article

In: Softwaretechnik-Trends, vol. 34, no. 1, 2014.