Publications - Semantic Web Lab, Edinburgh

Lab members have published 37 papers in peer reviewed conferences and journals. Below you will find a complete listing of all our contributions (93) to conferences, journals, workshops, proceedings, and technical recommendations, as well as PhD theses.

2022

Creating and Exploiting the Intrinsically Disordered Protein Knowledge Graph (IDP-KG)
Gray, Alasdair J. G. and Papadopoulos, Petros and Asif, Imran and Micetic, Ivan and Hatos, András
In 13th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, SWAT4HCLS 2022, Virtual Event, Leiden, The Netherlands, January 10th to 14th, 2022, CEUR Workshop Proceedings, 3127, pages 1–10, CEUR-WS.org, 2022

There are many data sources containing overlapping information about Intrinsically Disordered Proteins (IDP). IDPcentral aims to be a registry to aid the discovery of data about proteins known to be intrinsically disordered by aggregating the content from these sources. Traditional ETL approaches for populating IDPcentral require the API and data model of each source to be wrapped and then transformed into a common model. In this paper, we investigate using Bioschemas markup as a mechanism to populate the IDPcentral registry by constructing the Intrinsically Disordered Protein Knowledge Graph (IDP-KG). Bioschemas markup is a machine-readable, lightweight representation of the content of each page in the site that is embedded in the HTML. For any site it is accessible through a HTTP request. We harvest the Bioschemas markup in three IDP sources and show the resulting IDP-KG has the same breadth of proteins available as the original sources, and can be used to gain deeper insight into their content by querying them as a single, consolidated knowledge graph.
```
@inproceedings{GrayEtal:bioschemas-idpkg:swat4hcls2022,
  author = {Gray, Alasdair J. G. and Papadopoulos, Petros and Asif, Imran and Micetic, Ivan and Hatos, Andr{\'{a}}s},
  title = {Creating and Exploiting the Intrinsically Disordered Protein Knowledge Graph {(IDP-KG)}},
  booktitle = {13th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, {SWAT4HCLS} 2022, Virtual Event, Leiden, The Netherlands, January 10th to 14th, 2022},
  series = {{CEUR} Workshop Proceedings},
  volume = {3127},
  pages = {1--10},
  publisher = {CEUR-WS.org},
  year = {2022},
  url = {http://ceur-ws.org/Vol-3127/paper-1.pdf}
}
```

2021

Reference Statistics in Wikidata Topical Subsets
Hosseini Beghaeiraveri, Seyed Amir and Gray, Alasdair J. G. and McNeill, Fiona
In Proceedings of the 2nd Wikidata Workshop (Wikidata 2021), co-located with the 20th International Semantic Web Conference (ISWC 2021), 2021

Wikidata is the only general-purpose open knowledge graph with the capability of specifying references for every single statement. Currently, about 68% of Wikidata statements have at least one reference but the quality of these references is rarely covered in data quality studies. There is also a lack of a comprehensive framework for evaluating references. In this paper, we investigate the statistics of Wikidata references in 6 topical subsets of Wikidata. We compare these statistics over two Wikidata dumps; one from 2016 and one from 2021.
```
@inproceedings{HosseiniBeghaeiraveri2021:RefStats:wikidata2021,
  title = {Reference Statistics in Wikidata Topical Subsets},
  booktitle = {Proceedings of the 2nd Wikidata Workshop (Wikidata 2021), co-located with the 20th International Semantic Web Conference (ISWC 2021)},
  keywords = {Reference quality, Wikidata, Data quality, Topical subset, WikiProject, Gene Wiki},
  author = {Hosseini Beghaeiraveri, Seyed Amir and Gray, Alasdair J. G. and McNeill, Fiona},
  year = {2021},
  month = oct,
  url = {http://ceur-ws.org/Vol-2982/paper-3.pdf}
}
```
Experiences of Using WDumper to Create Topical Subsets from Wikidata
Hosseini Beghaeiraveri, Seyed Amir and Gray, Alasdair J. G. and McNeill, Fiona
In Proceedings of the 2nd International Workshop on Knowledge Graph Construction, co-located with the 18th Extended Semantic Web Conference (ESWC 2021), CEUR Workshop Proceedings, 2873, CEUR Workshop Proceedings (CEUR-WS.org), 2021

Wikidata is a general-purpose knowledge graph covering a wide variety of topics with content being crowd-sourced through an open wiki. There are now over 90M interrelated data items in Wikidata which are accessible through a public query endpoint and data dumps. However, execution timeout limits and the size of data dumps make it difficult to use the data. The creation of arbitrary topical subsets of Wikidata, where only the relevant data is kept, would enable reuse of that data with the benefits of cost reduction, ease of access, and flexibility. In this paper, we provide a formal definition of topical subsets over the Wikidata Knowledge Graph and evaluate a third-party tool (WDumper) to extract these topical subsets from Wikidata.
```
@inproceedings{HosseiniBeghaeiraveri2021:TopicalSubsets:KGConstruction2021,
  title = {Experiences of Using WDumper to Create Topical Subsets from Wikidata},
  booktitle = {Proceedings of the 2nd International Workshop on Knowledge Graph Construction, co-located with the 18th Extended Semantic Web Conference (ESWC 2021)},
  keywords = {Wikidata, Topical subset, WikiProject, Gene Wiki},
  author = {{Hosseini Beghaeiraveri}, {Seyed Amir} and Gray, {Alasdair J. G.} and McNeill, Fiona},
  year = {2021},
  month = jun,
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR Workshop Proceedings (CEUR-WS.org)},
  volume = {2873},
  url = {http://ceur-ws.org/Vol-2873/paper13.pdf}
}
```
Exploiting Bioschemas Markup to Populate IDPcentral
Gray, Alasdair J G and Papadopoulos, Petros and Mičetić, Ivan and Hatos, András
Technical Report. BioHackrXiv. jun, 2021

One of the goals of the ELIXIR Intrinsically Disordered Protein (IDP) community is create a registry called IDPcentral. The registry will aggregate data contained in the community’s specialist data sources such as DisProt, MobiDB, and Protein Ensemble Database (PED) so that proteins that are known to be intrinsically disordered can be discovered; with summary details of the protein presented, and the specialist source consulted for more detailed data. At the ELIXIR BioHackathon-Europe 2020, we aimed to investigate the feasibility of populating IDPcentral harvesting the Bioschemas markup that has been deployed on the IDP community data sources. The benefit of using Bioschemas markup, which is embedded in the HTML web pages for each protein in the data source, is that a standard harvesting approach can be used for all data sources; rather than needing bespoke wrappers for each data source API. We expect to harvest the markup using the Bioschemas Markup Scraper and Extractor (BMUSE) tool that has been developed specifically for this purpose. The challenge, however, is that the sources contain overlapping information about proteins but use different identifiers for the proteins. After the data has been harvested, it will need to be processed so that information about a particular protein, which will come from multiple sources, is consolidated into a single concept for the protein, with links back to where each piece of data originated. As well as populating the IDPcentral registry, we plan to consolidate the markup into a knowledge graph that can be queried to gain further insight into the IDPs.
```
@techreport{gray:bioschemas-idpcntral:2021,
  title = {Exploiting Bioschemas Markup to Populate IDPcentral},
  url = {biohackrxiv.org/v3jct},
  doi = {10.37044/osf.io/v3jct},
  publisher = {BioHackrXiv},
  author = {Gray, Alasdair J G and Papadopoulos, Petros and Mičetić, Ivan and Hatos, András},
  year = {2021},
  month = jun
}
```
Knowledge graphs and wikidata subsetting
Labra-Gayo, Jose E and Hevia, Alejandro G and Álvarez, Daniel F and Ammar, Ammar and Brickley, Dan and Gray, Alasdair J G and Prud’hommeaux, Eric and Slenter, Denise and Solbrig, Harold and Beghaeiraveri, Seyed A H and et al.
Technical Report. BioHackrXiv. apr, 2021

Knowledge graphs have successfully been adopted by academia, governement and industry to represent large scale knowledge bases. Open and collaborative knowledge graphs such as Wikidata capture knowledge from different domains and harmonize them under a common format, making it easier for researchers to access the data while also supporting Open Science. Wikidata keeps getting bigger and better, which subsumes integration use cases. Having a large amount of data such as the one presented in a scopeless Wikidata offers some advantages, e.g., unique access point and common format, but also poses some challenges, e.g., performance. Regular wikidata users are not unfamiliar with running into frequent timeouts of submitted queries. Due to its popularity, limits have been imposed to allow for fair access to many. However this suppreses many interesting and complex queries that require more computational power and resources. Replicating Wikidata on one’s own infrastructure can be a solution which also offers a snapshot of the contents of wikidata at some given point in time. There is no need to replicate Wikidata in full, it is possible to work with subsets targeting, for instance, a particular domain. Creating those subsets has emerged as an alternative to reduce the amount and spectrum of data offered by Wikidata. Less data makes more complex queries possible while still keeping the compatibility with the whole Wikidata as the model is kept. In this paper we report the tasks done as part of a Wikidata subsetting project during the Virtual BioHackathon Europe 2020 and SWAT4(HC)LS 2021, which had already started at NBDC/DBCLS BioHackathon 2019 in Japan, SWAT4(HC)LS hackathon 2019, and Virtual COVID-19 BioHackathon 2019. We describe some of approaches we identified to create subsets and some susbsets from the Life Sciences domain as well as other use cases we also discussed.
```
@techreport{labra-gayo:kg-subsetting:biohackrxiv2021,
  title = {Knowledge graphs and wikidata subsetting},
  url = {biohackrxiv.org/wu9et},
  doi = {10.37044/osf.io/wu9et},
  publisher = {BioHackrXiv},
  author = {Labra-Gayo, Jose E and Hevia, Alejandro G and Álvarez, Daniel F and Ammar, Ammar and Brickley, Dan and Gray, Alasdair J G and Prud'hommeaux, Eric and Slenter, Denise and Solbrig, Harold and Beghaeiraveri, Seyed A H and et al.},
  year = {2021},
  month = apr
}
```
RO-Crate Metadata Specification 1.1.1
Sefton, Peter and Carragáin, Eoghan Ó and Soiland-Reyes, Stian and Corcho, Oscar and Garijo, Daniel and Palma, Raul and Coppens, Frederik and Goble, Carole and Fernández, José María and Chard, Kyle and Gomez-Perez, Jose Manuel and Crusoe, Michael R and Eguinoa, Ignacio and Juty, Nick and Holmes, Kristi and Clark, Jason A. and Capella-Gutierrez, Salvador and Gray, Alasdair J. G. and Owen, Stuart and Williams, Alan R. and Tartari, Giacomo and Bacall, Finn and Thelen, Thomas and Ménager, Hervé and Rodríguez-Navas, Laura and Walk, Paul and brandon whitehead and Wilkinson, Mark and Groth, Paul and Bremer, Erich and Castro, LJ Garcia and Sebby, Karl and Kanitz, Alexander and Trisovic, Ana and Kennedy, Gavin and Graves, Mark and Koehorst, Jasper and Leo, Simone and Portier, Marc
Technical Report. researchobject.org. feb, 2021
Recommendation published by researchobject.org - see https://w3id.org/ro/crate/1.1 for web version.

This document specifies a method, known as RO-Crate (Research Object Crate), of aggregating and describing research data with associated metadata. RO-Crates can aggregate and describe any resource including files, URI-addressable resources, or use other addressing schemes to locate digital or physical data. RO-Crates can describe data in aggregate and at the individual resource level, with metadata to aid in discovery, re-use and long term management of data. Metadata includes the ability to describe the context of data and the entities involved in its production, use and reuse. For example: who created it, using which equipment, software and workflows, under what licenses can it be re-used, where was it collected, and/or where is it about.RO-Crate uses JSON-LD to to express this metadata using linked data, describing data resources as well as contextual entities such as people, organizations, software and equipment as a series of linked JSON-LD objects - using common published vocabularies, chiefly schema.org.The core of RO-Crate is a JSON-LD file, the RO-Crate Metadata File, named ro-crate-metadata.json. This file contains structured metadata about the dataset as a whole (the Root Data Entity) and, optionally, about some or all of its files. This provides a simple way to, for example, assert the authors (e.g. people, organizations) of the RO-Crate or one its files, or to capture more complex provenance for files, such as how they were created using software and equipment.While providing the formal specification for RO-Crate, this document also aims to be a practical guide for software authors to create tools for generating and consuming research data packages, with explanation by examples.
```
@techreport{RO-Crate-1-1,
  title = {RO-Crate Metadata Specification 1.1.1},
  author = {Sefton, Peter and Carrag{\'a}in, {Eoghan {\'O}} and Soiland-Reyes, Stian and Corcho, Oscar and Garijo, Daniel and Palma, Raul and Coppens, Frederik and Goble, Carole and Fern{\'a}ndez, {Jos{\'e} Mar{\'i}a} and Chard, Kyle and Gomez-Perez, {Jose Manuel} and Crusoe, {Michael R} and Eguinoa, Ignacio and Juty, Nick and Holmes, Kristi and Clark, {Jason A.} and Capella-Gutierrez, Salvador and Gray, {Alasdair J. G.} and Owen, Stuart and Williams, {Alan R.} and Tartari, Giacomo and Bacall, Finn and Thelen, Thomas and M{\'e}nager, Herv{\'e} and Rodr{\'i}guez-Navas, Laura and Walk, Paul and brandon whitehead and Wilkinson, Mark and Groth, Paul and Bremer, Erich and Castro, {LJ Garcia} and Sebby, Karl and Kanitz, Alexander and Trisovic, Ana and Kennedy, Gavin and Graves, Mark and Koehorst, Jasper and Leo, Simone and Portier, Marc},
  note = {Recommendation published by researchobject.org - see https://w3id.org/ro/crate/1.1 for web version.},
  year = {2021},
  month = feb,
  doi = {10.5281/zenodo.4541002},
  publisher = {researchobject.org},
  address = {United Kingdom}
}
```
SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts
Kruiper, Ruben and Konstas, Ioannis and Gray, Alasdair J G and Sadeghineko, Fahrad and Watson, Richard and Kumar, Bimal
In Natural Legal Language Processing workshop, EMNLP, Punta Cana, Dominican Republic, pages 129-143, Association for Computational Linguistics, 2021

Automated Compliance Checking (ACC) systems aim to semantically parse building regulations to a set of rules. However, semantic parsing is known to be hard and requires large amounts of training data. The complexity of creating such training data has led to research that focuses on small sub-tasks, such as shallow parsing or the extraction of a limited subset of rules. This study introduces a shallow parsing task for which training data is relatively cheap to create, with the aim of learning a lexicon for ACC. We annotate a small domain-specific dataset of 200 sentences, SPaR.txt, and train a sequence tagger that achieves 79,93 F1-score on the test set. We then show through manual evaluation that the model identifies most (89,84%) defined terms in a set of building regulation documents, and that both contiguous and discontiguous Multi-Word Expressions (MWE) are discovered with reasonable accuracy (70,3%).
```
@inproceedings{Kruiper2021:SPaRtxt:nllp2021,
  author = {Kruiper, Ruben and Konstas, Ioannis and Gray, Alasdair J G and Sadeghineko, Fahrad and Watson, Richard and Kumar, Bimal},
  title = {SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts},
  optcrossref = {},
  optkey = {},
  booktitle = {Natural Legal Language Processing workshop, EMNLP},
  year = {2021},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  pages = {129-143},
  optmonth = nov,
  address = {Punta Cana, Dominican Republic},
  optorganization = {},
  publisher = {Association for Computational Linguistics},
  optnote = {},
  url = {https://aclanthology.org/2021.nllp-1.14},
  optannote = {}
}
```
Using Nanopublications to Detect and Explain Contradictory Research Claims
Asif, Imran and Tiddi, Ilaria and Gray, Alasdair J. G.
In 2021 IEEE 17th International Conference on eScience (eScience), pages 1-10, 2021

We tackle the problem of automatically detecting conflicting claims in research outputs. This has become even more urgent in recent years, with the increasing volume of scientific publications available. Researchers are struggling to keep pace with the literature, and to efficiently make comparisons between the results of different published studies. We hypothesise that the difficult and time-consuming process of searching and comparing results across research publications can be facilitated using machine-readable, standardised knowledge representation methods. To this end, we propose to exploit Nanopublications as the standard framework to represent the claims in research studies, and use provenance data expressed by the model as an indicator of the source of the contradiction between different claims. We evaluate this idea over the Cooperation Databank (CoDa); a repository of social science studies. Our results show that the use of provenance information can be a good factor to identify the cause of conflicting claims, and that our method can support scientists in comparing literature in a more automated way.
```
@inproceedings{asif:nanopub-contradictions:eScience2021,
  author = {Asif, Imran and Tiddi, Ilaria and Gray, Alasdair J. G.},
  booktitle = {2021 IEEE 17th International Conference on eScience (eScience)},
  title = {Using Nanopublications to Detect and Explain Contradictory Research Claims},
  year = {2021},
  pages = {1-10},
  doi = {10.1109/eScience51609.2021.00010}
}
```

2020

Data integration for offshore decommissioning waste management
Akinyemi, Abiodun G. and Sun, Ming and Gray, Alasdair J. G.
Automation in Construction, 109:103010, Elsevier, 2020

Offshore decommissioning represents significant business opportunities for oil and gas service companies. However, for owners of offshore assets and regulators, it is a liability because of the associated costs. One way of mitigating decommissioning costs is through the sales and reuse of decommissioned items. To achieve this effectively, reliability assessment of decommissioned items is required. Such an assessment relies on data collected on the various items over the lifecycle of an engineering asset. Considering that offshore platforms have a design life of about 25 years and data management techniques and tools are constantly evolving, data captured about items to be decommissioned will be in varying forms. In addition, considering the many stakeholders involved with a facility over its lifecycle, information representation of the items will have variations. These challenges make data integration difficult. As a result, this research developed a data integration framework that makes use of Semantic Web technologies and ISO 15926 - a standard for process plant data integration - for rapid assessment of decommissioned items. The proposed solution helps in determining the reuse potential of decommissioned items, which can save on cost and benefit the environment.
```
@article{Akinyemi:offshore-data-integration:2020,
  doi = {10.1016/j.autcon.2019.103010},
  url = {https://www.sciencedirect.com/science/article/pii/S0926580518304059},
  year = {2020},
  month = nov,
  publisher = {Elsevier},
  volume = {109},
  pages = {103010},
  author = {Akinyemi, Abiodun G. and Sun, Ming and Gray, Alasdair J. G.},
  title = {Data integration for offshore decommissioning waste management},
  journal = {Automation in Construction}
}
```

2019

Generating corrupted data sources for the evaluation of matching systems
McNeill, Fiona and Bental, Diana and Gray, Alasdair J. G. and Jedrzejczyk, Sabina and Alsadeeqi, Ahmad
In The Fourteenth International Workshop on Ontology Matching, CEUR Workshop Proceedings, 2536, pages 41–45, CEUR Workshop Proceedings (CEUR-WS.org), 2019

One of the most difficult aspects of developing matching systems – whether for matching ontologies or for other types of mismatched data – is evaluation. The accuracy of matchers are usually evaluated by measuring the results produced by the systems against reference sets, but gold-standard reference sets are expensive and difficult to create. In this paper we introduce crptr, which generates multiple variations of different sorts of dataset, where the degree of variation is controlled, in order that they can be used to evaluate matchers in different context.
```
@inproceedings{McNeill:crptr-matching-evaluation:OM2019,
  title = {Generating corrupted data sources for the evaluation of matching systems},
  keywords = {Matching, Evaluation, Data Corruption},
  author = {McNeill, Fiona and Bental, Diana and Gray, Alasdair J. G. and Jedrzejczyk, Sabina and Alsadeeqi, Ahmad},
  year = {2019},
  month = oct,
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR Workshop Proceedings (CEUR-WS.org)},
  volume = {2536},
  pages = {41--45},
  booktitle = {The Fourteenth International Workshop on Ontology Matching},
  url = {http://ceur-ws.org/Vol-2536/om2019_STpaper2.pdf}
}
```
Data Quality Issues in Current Nanopublications
Asif, Imran and Chen-Burger, Jessica and Gray, Alasdair J. G.
In 2019 15th International Conference on eScience (eScience), , pages 522-527, 2019

Nanopublications are a granular way of publishing scientific claims together with their associated provenance and publication information. More than 10 million nanopublications have been published by a handful of researchers covering a wide range of topics within the life sciences. We were motivated to replicate an existing analysis of these nanopublications, but then went deeper into the structure of the existing nanopublications. In this paper, we analyse the usage of nanopublications by investigating the distribution of triples in each part and discuss the data quality issues that were subsequently revealed. We argue that there is a need for the community to develop a set of guidelines for the modelling of nanopublications.
```
@inproceedings{Asif:NanopubQuality:eScience2019,
  author = {Asif, Imran and Chen-Burger, Jessica and Gray, Alasdair J. G.},
  booktitle = {2019 15th International Conference on eScience (eScience)},
  title = {Data Quality Issues in Current Nanopublications},
  year = {2019},
  volume = {},
  number = {},
  pages = {522-527},
  keywords = {},
  doi = {10.1109/eScience.2019.00069},
  month = sep
}
```
ToCo: An Ontology for Representing Hybrid Telecommunication Networks
Zhou, Qianru and Gray, Alasdair J. G. and McLaughlin, Stephen
In The Semantic Web - 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2-6, 2019, Proceedings, Lecture Notes in Computer Science, 11503, pages 507–522, Springer, 2019

The TOUCAN project proposed an ontology for telecommunication networks with hybrid technologies – the TOUCAN Ontology (ToCo), available at http://purl.org/toco/, as well as a knowledge design pattern Device-Interface-Link (DIL) pattern. The core classes and relationships forming the ontology are discussed in detail. The ToCo ontology can describe the physical infrastructure, quality of channel, services and users in heterogeneous telecommunication networks which span multiple technology domains. The DIL pattern is observed and summarised when modelling networks with various technology domains. Examples and use cases of ToCo are presented for demonstration.
```
@inproceedings{DBLP:conf/esws/ZhouGM19,
  author = {Zhou, Qianru and Gray, Alasdair J. G. and McLaughlin, Stephen},
  title = {ToCo: An Ontology for Representing Hybrid Telecommunication Networks},
  booktitle = {The Semantic Web - 16th International Conference, {ESWC} 2019, Portoro{\v{z}},
                 Slovenia, June 2-6, 2019, Proceedings},
  series = {Lecture Notes in Computer Science},
  volume = {11503},
  pages = {507--522},
  publisher = {Springer},
  month = jun,
  year = {2019},
  url = {https://doi.org/10.1007/978-3-030-21348-0\_33},
  doi = {10.1007/978-3-030-21348-0\_33}
}
```
The Semantic Web - 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2-6, 2019, Proceedings
Hitzler, Pascal and Fernández, Miriam and Janowicz, Krzysztof and Zaveri, Amrapali and Gray, Alasdair J. G. and López, Vanessa and Haller, Armin and Hammar, Karl
Lecture Notes in Computer Science, 11503, Springer, 2019
ISBN: 978-3-030-21347-3

This book constitutes the refereed proceedings of the 16th International Semantic Web Conference, ESWC 2019, held in Portorož, Slovenia. The 39 revised full papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in three tracks: research track, resources track, and in-use track and deal with the following topical areas: distribution and decentralisation, velocity on the Web, research of research, ontologies and reasoning, linked data, natural language processing and information retrieval, semantic data management and data infrastructures, social and human aspects of the Semantic Web, and, machine learning.
```
@proceedings{eswc2019,
  editor = {Hitzler, Pascal and Fern{\'{a}}ndez, Miriam and Janowicz, Krzysztof and Zaveri, Amrapali and Gray, Alasdair J. G. and L{\'{o}}pez, Vanessa and Haller, Armin and Hammar, Karl},
  title = {The Semantic Web - 16th International Conference, {ESWC} 2019, Portoro{\v{z}},
                 Slovenia, June 2-6, 2019, Proceedings},
  series = {Lecture Notes in Computer Science},
  volume = {11503},
  publisher = {Springer},
  month = jun,
  year = {2019},
  url = {https://doi.org/10.1007/978-3-030-21348-0},
  doi = {10.1007/978-3-030-21348-0},
  isbn = {978-3-030-21347-3}
}
```
SARA - A Semantic Access Point Resource Allocation Service for Heterogenous Wireless Networks
Zhou, Qianru and Gray, Alasdair J. G. and Pezaros, Dimitrios and McLaughlin, Stephen
In 2019 Wireless Days, WD 2019, Manchester, United Kingdom, April 24-26, 2019, pages 1–8, IEEE, 2019

In this paper, we present SARA, a Semantic Access point Resource Allocation service for heterogenous wireless networks with various wireless access technologies existing together. By automatically reasoning on the knowledge base of the full system provided by a knowledge based autonomic network management system - SEANET, SARA selects the access point providing the best quality of service among the different access technologies. Based on an ontology assisted knowledge based system SEANET, SARA can also adapt the access point selection strategy according to customer defined rules automatically. Results of our evaluation based on emulated networks with hybrid access technologies and various scales show that SARA is able to improve the channel condition, in terms of throughput, evidently. Comparisons with current AP selection algorithms demonstrate that SARA outperforms the existing AP selection algorithms. The overhead in terms of time expense is reasonable and is shown to be faster than traditional access point selection approaches.
```
@inproceedings{DBLP:conf/wd/ZhouGPM19,
  author = {Zhou, Qianru and Gray, Alasdair J. G. and Pezaros, Dimitrios and McLaughlin, Stephen},
  title = {{SARA} - {A} Semantic Access Point Resource Allocation Service for
                 Heterogenous Wireless Networks},
  booktitle = {2019 Wireless Days, {WD} 2019, Manchester, United Kingdom, April 24-26,
                 2019},
  pages = {1--8},
  publisher = {{IEEE}},
  month = apr,
  year = {2019},
  url = {https://doi.org/10.1109/WD.2019.8734260},
  doi = {10.1109/WD.2019.8734260}
}
```

2018

Using a Jupyter Notebook to perform a reproducible scientific analysis over semantic web sources
Gray, Alasdair J G
In Enabling Open Semantic Science, Monterey, California, USA, 2018
Executable version: https://mybinder.org/v2/gh/AlasdairGray/SemSci2018/master?filepath=SemSci2018%20Publication.ipynb

In recent years there has been a reproducibility crisis in science. Computational notebooks, such as Jupyter, have been touted as one solution to this problem. However, when executing analyses over live SPARQL endpoints, we get different answers depending upon when the analysis in the notebook was executed. In this paper, we identify some of the issues discovered in trying to develop a reproducible analysis over a collection of biomedical data sources and suggest some best practice to overcome these issues.
```
@inproceedings{Gray2018:jupyter:SemSci2018,
  author = {Gray, Alasdair J G},
  title = {Using a Jupyter Notebook to perform a reproducible scientific analysis over semantic web sources},
  optcrossref = {},
  optkey = {},
  booktitle = {Enabling Open Semantic Science},
  year = {2018},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  optpages = {},
  month = oct,
  address = {Monterey, California, USA},
  optorganization = {},
  optpublisher = {},
  note = {Executable version: https://mybinder.org/v2/gh/AlasdairGray/SemSci2018/master?filepath=SemSci2018%20Publication.ipynb},
  url = {http://ceur-ws.org/Vol-2184/paper-02/paper-02.html},
  optannote = {}
}
```
An ontology-based data integration framework for construction information management
Akinyemi, Abiodun and Sun, Ming and Gray, Alasdair J G
Proceedings of the Institution of Civil Engineers - Management, Procurement and Law, 171(3):111–125, Thomas Telford Ltd., 2018

Information management during the construction phase of a built asset involves multiple stakeholders using multiple software applications to generate and store data. This is problematic as data come in different forms and are labour intensive to piece together. Existing solutions to this problem are predominantly in proprietary applications, which are sometimes cost prohibitive for small engineering firms, or conceptual studies with use cases that cannot be easily adapted. In view of these limitations, this research presents an ontology-based data integration framework that makes use of open-source tools that support Semantic Web technologies. The proposed framework enables rapid answering of queries over construction data integrated from heterogeneous sources, data quality checks and reuse of project software resources. The attributes and functionalities of the proposed solution align with the requirements common to small firms with limited information technology skill and budget. Consequently, this solution can be of great benefit for their data projects.
```
@article{Akinyemi_2018,
  doi = {10.1680/jmapl.17.00052},
  url = {https://doi.org/10.1680%2Fjmapl.17.00052},
  year = {2018},
  month = jun,
  publisher = {Thomas Telford Ltd.},
  volume = {171},
  number = {3},
  pages = {111--125},
  author = {Akinyemi, Abiodun and Sun, Ming and Gray, Alasdair J G},
  title = {An ontology-based data integration framework for construction information management},
  journal = {Proceedings of the Institution of Civil Engineers - Management, Procurement and Law}
}
```
ReasoNet: Inferring Network Policies Using Ontologies
Rotsos, Charalampos and Farshad, Arsham and King, Daniel and Hutchison, David and Zhou, Qianru and Gray, Alasdair J. G. and Wang, Cheng-Xiang and McLaughlin, Stephen
In 4th IEEE Conference on Network Softwarization and Workshops, NetSoft 2018, Montreal, QC, Canada, June 25-29, 2018, pages 159–167, IEEE, 2018

Modern Software Defined Networking (SDN) control stacks consist of multiple abstraction and virtualization layers to enable flexibility in the development of new control features. Rich data modeling frameworks are essential when sharing information across control layers. Unfortunately, existing Network Operating System (NOS) data modeling capabilities are limited to simple type-checking and code templating. We present an exploration of a more extreme point on SDN data modeling: ReasoNet. Developers can use semantic web technologies to enrich their data models with reasoning rules and integrity/consistency constraints, and automate state inference across layers. We demonstrate the ability of ReasoNet to automate state verification and cross-layer debugging, through the implementation of two popular control applications, a learning switch and a Quality of Service (QoS) policy engine.
```
@inproceedings{DBLP:conf/netsoft/RotsosFKHZGWM18,
  author = {Rotsos, Charalampos and Farshad, Arsham and King, Daniel and Hutchison, David and Zhou, Qianru and Gray, Alasdair J. G. and Wang, Cheng{-}Xiang and McLaughlin, Stephen},
  title = {ReasoNet: Inferring Network Policies Using Ontologies},
  booktitle = {4th {IEEE} Conference on Network Softwarization and Workshops, NetSoft
                 2018, Montreal, QC, Canada, June 25-29, 2018},
  pages = {159--167},
  publisher = {{IEEE}},
  month = jun,
  year = {2018},
  url = {https://doi.org/10.1109/NETSOFT.2018.8460050},
  doi = {10.1109/NETSOFT.2018.8460050}
}
```
The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY
Harding, Simon D. and Sharman, Joanna L. and Faccenda, Elena and Southan, Christopher and Pawson, Adam J. and Ireland, Sam and Gray, Alasdair J. G. and Bruce, Liam and Alexander, Stephen P. H. and Anderton, Stephen and Bryant, Clare and Davenport, Anthony P. and Doerig, Christian and Fabbro, Doriano and Levi-Schaffer, Francesca and Spedding, Michael and Davies, Jamie A. and Nc-Iuphar
Nucleic Acids Research, 46(Database-Issue):D1091–D1106, 2018

The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, www.guidetopharmacology.org) and its precursor IUPHAR-DB, have captured expert-curated interactions between targets and ligands from selected papers in pharmacology and drug discovery since 2003. This resource continues to be developed in conjunction with the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS). As previously described, our unique model of content selection and quality control is based on 96 target-class subcommittees comprising 512 scientists collaborating with in-house curators. This update describes content expansion, new features and interoperability improvements introduced in the 10 releases since August 2015. Our relationship matrix now describes ∼9000 ligands, ∼15 000 binding constants, ∼6000 papers and ∼1700 human proteins. As an important addition, we also introduce our newly funded project for the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb, www.guidetoimmunopharmacology.org). This has been ‘forked’ from the well-established GtoPdb data model and expanded into new types of data related to the immune system and inflammatory processes. This includes new ligands, targets, pathways, cell types and diseases for which we are recruiting new IUPHAR expert committees. Designed as an immunopharmacological gateway, it also has an emphasis on potential therapeutic interventions.
```
@article{Harding:GtoPdb:NAR2018,
  author = {Harding, Simon D. and Sharman, Joanna L. and Faccenda, Elena and Southan, Christopher and Pawson, Adam J. and Ireland, Sam and Gray, Alasdair J. G. and Bruce, Liam and Alexander, Stephen P. H. and Anderton, Stephen and Bryant, Clare and Davenport, Anthony P. and Doerig, Christian and Fabbro, Doriano and Levi{-}Schaffer, Francesca and Spedding, Michael and Davies, Jamie A. and Nc{-}Iuphar},
  title = {The {IUPHAR/BPS} Guide to {PHARMACOLOGY} in 2018: updates and expansion
                 to encompass the new guide to {IMMUNOPHARMACOLOGY}},
  journal = {Nucleic Acids Research},
  volume = {46},
  number = {Database-Issue},
  pages = {D1091--D1106},
  year = {2018},
  url = {https://doi.org/10.1093/nar/gkx1121},
  doi = {10.1093/nar/gkx1121}
}
```

2017

Lost Silence: An emergency response early detection service through continuous processing of telecommunication data streams
Zhou, Qianru and McLaughlin, Stephen and Gray, Alasdair J G and Wu, Shangbin and Wang, Chengxiang
In Web Stream Processing 2017, Vienna, Austria, 2017

Early detection of significant traumatic events, e.g. terrorist events, ship capsizes, is important to ensure that a prompt emergency response can occur. In the modern world telecommunication systems can and do play a key role in ensuring a successful emergency response by detecting such incidents through significant changes in calls and access to the networks. In this paper a methodology is illustrated to detect such incidents immediately (with the delay in the order of milliseconds), by processing semantically annotated streams of data in cellular telecommunication systems. In our methodology, live information of phones’ positions and status are encoded as RDF streams. We propose an algorithm that processes streams of RDF annotated telecommunication data to detect abnormality. Our approach is exemplified in the context of capsize of a passenger cruise ship but is readily translatable to other incidents. Our evaluation results show that with properly chosen window size, such incidents can be detected effectively.
```
@inproceedings{ZhouEtal2017:LostSilence:WSP2017,
  author = {Zhou, Qianru and McLaughlin, Stephen and Gray, Alasdair J G and Wu, Shangbin and Wang, Chengxiang},
  title = {Lost Silence: An emergency response early detection service through continuous processing of telecommunication data streams},
  optcrossref = {},
  optkey = {},
  booktitle = {Web Stream Processing 2017},
  year = {2017},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  optpages = {},
  month = oct,
  address = {Vienna, Austria},
  optorganization = {},
  optpublisher = {},
  optnote = {},
  url = {http://ceur-ws.org/Vol-1936/paper-03.pdf},
  optannote = {}
}
```
Bioschemas: From Potato Salad to Protein Annotation
Gray, Alasdair J. G. and Goble, Carole A. and Jimenez, Rafael
In Proceedings of the ISWC 2017 Posters & Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, October 23rd - to - 25th, 2017., CEUR Workshop Proceedings, 1963, CEUR-WS.org, 2017
(Poster paper)

The life sciences have a wealth of data resources with a wide range of overlapping content. Key repositories, such as UniProt for protein data or Entrez Gene for gene data, are well known and their content easily discovered through search engines. However, there is a long-tail of bespoke datasets with important content that are not so prominent in search results. Building on the success of Schema.org for making a wide range of structured web content more discoverable and interpretable, e.g. food recipes, the Bioschemas community (http://bioschemas.org) aim to make life sciences datasets more findable by encouraging data providers to embed Schema.org markup in their resources.
```
@inproceedings{Gray:BioschemasPotatoSalad:ISWC2017,
  author = {Gray, Alasdair J. G. and Goble, Carole A. and Jimenez, Rafael},
  booktitle = {Proceedings of the {ISWC} 2017 Posters {\&} Demonstrations and Industry Tracks co-located with 16th International Semantic Web Conference {(ISWC} 2017), Vienna, Austria, October 23rd - to - 25th, 2017.},
  month = oct,
  note = {(Poster paper)},
  publisher = {CEUR-WS.org},
  series = {{CEUR} Workshop Proceedings},
  title = {Bioschemas: From Potato Salad to Protein Annotation},
  url = {http://ceur-ws.org/Vol-1963/paper579.pdf},
  volume = {1963},
  year = {2017}
}
```
Systematically corrupting data to assess data linkage quality
Alsadeeqi, Ahmad and Gray, Alasdair J G
In The Systematic Linking of Historical Records, University of Guelph, Guelph, Canada, 2017
Workshop website \urlhttp://recordlink.org/

Computer algorithms use string matching techniques to assess how likely two historical records are to be the same. The quality of linkage is unclear without knowing the correct links or ground truth. Synthetically generated datasets for which ground truth is known are helpful but the data typically are too clean to be representative of historical records. We assess data linkage algorithms under different data quality scenarios, e.g. with errors typical of historical transcriptions. A data corrupting model injects four types of mistakes: character level (e.g. an f is represented as an s – OCR Corruptions), attribute level (e.g. male changed to female due to false entry), record level (e.g. missing records), and group of records level (e.g. coffee spilt over a page, lost parish records in fire). We then evaluate record linkage algorithms over synthetically generated datasets with known ground truth and data corruptions matching a given profile.
```
@inproceedings{alsadeeqiGray:systematicCorruption:2017,
  author = {Alsadeeqi, Ahmad and Gray, Alasdair J G},
  title = {Systematically corrupting data to assess data linkage quality},
  optcrossref = {},
  optkey = {},
  booktitle = {The Systematic Linking of Historical Records},
  year = {2017},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  optpages = {},
  month = may,
  address = {University of Guelph, Guelph, Canada},
  optorganization = {},
  optpublisher = {},
  note = {Workshop website \url{http://recordlink.org/}},
  optannote = {}
}
```
Interoperability and FAIRness through a novel combination of Web technologies
Wilkinson, Mark D. and Verborgh, Ruben and da Silva Santos, Luiz Olavo Bonino and Clark, Tim and Swertz, Morris A. and Kelpin, Fleur D. L. and Gray, Alasdair J. G. and Schultes, Erik A. and van Mulligen, Erik M. and Ciccarese, Paolo and Kuzniar, Arnold and Gavai, Anand and Thompson, Mark and Kaliyaperumal, Rajaram and Bolleman, Jerven T. and Dumontier, Michel
PeerJ Computer Science, 3:e110, 2017

Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general- or special-purpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved at the level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs.
```
@article{Wilkinson:InteropFAIRWebTech:PeerJ2017,
  author = {Wilkinson, Mark D. and Verborgh, Ruben and da Silva Santos, Luiz Olavo Bonino and Clark, Tim and Swertz, Morris A. and Kelpin, Fleur D. L. and Gray, Alasdair J. G. and Schultes, Erik A. and van Mulligen, Erik M. and Ciccarese, Paolo and Kuzniar, Arnold and Gavai, Anand and Thompson, Mark and Kaliyaperumal, Rajaram and Bolleman, Jerven T. and Dumontier, Michel},
  title = {Interoperability and FAIRness through a novel combination of Web technologies},
  journal = {PeerJ Computer Science},
  volume = {3},
  pages = {e110},
  year = {2017},
  url = {https://doi.org/10.7717/peerj-cs.110},
  doi = {10.7717/peerj-cs.110}
}
```

2016

Describing Datasets with the Health Care and Life Sciences Community Profile
Gray, Alasdair J. G. and Dumontier, Michel and Marshall, M. Scott
In Semantic Web Applications and Tools for Life Sciences (SWAT4LS 2016), Amsterdam, The Netherlands, 2016
(Tutorial)
```
@inproceedings{Gray:HCLS:SWAT4LSTutorial2016,
  address = {Amsterdam, The Netherlands},
  author = {Gray, Alasdair J. G. and Dumontier, Michel and Marshall, M. Scott},
  booktitle = {Semantic Web Applications and Tools for Life Sciences (SWAT4LS 2016)},
  month = dec,
  note = {(Tutorial)},
  title = {Describing Datasets with the Health Care and Life Sciences Community Profile},
  year = {2016}
}
```
Validata: A tool for testing profile conformance
Gray, Alasdair J. G.
In Smart Descriptions & Smarter Vocabularies (SDSVoc), Amsterdam, The Netherlands, 2016

Validata is an online web application for validating a dataset description expressed in RDF against a community profile expressed as a Shape Expression (ShEx). Additionally it provides an API for programmatic access to the validator. Validata is capable of being used for multiple community agreed standards, e.g. DCAT, the HCLS community profile, or the Open PHACTS guidelines, and there are currently deployments to support each of these. Validata can be easily repurposed for different deployments by providing it with a new ShEx schema. The Validata code is available from GitHub.
```
@inproceedings{Gray2016SDSVocValidata,
  author = {Gray, Alasdair J. G.},
  title = {Validata: A tool for testing profile conformance},
  optcrossref = {},
  optkey = {},
  booktitle = {Smart Descriptions \& Smarter Vocabularies (SDSVoc)},
  year = {2016},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  optpages = {},
  month = nov,
  address = {Amsterdam, The Netherlands},
  optorganization = {},
  optpublisher = {},
  optnote = {},
  url = {https://www.w3.org/2016/11/sdsvoc/SDSVoc16_paper_2},
  optannote = {}
}
```
The HCLS Community Profile: Describing Datasets, Versions, and Distributions
Dumontier, Michel and Gray, Alasdair J. G. and Marshall, M. Scott
In Smart Descriptions & Smarter Vocabularies (SDSVoc), Amsterdam, The Netherlands, 2016

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting HCLS community profile covers elements of description, identification, attribution, versioning, provenance, and content summarization. The HCLS community profile reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets. The goal of this presentation is to give an overview of the HCLS Community Profile and explain how it extends and builds upon other approaches.
```
@inproceedings{Gray2016SDSVocHCLS,
  author = {Dumontier, Michel and Gray, Alasdair J. G. and Marshall, M. Scott},
  title = {The {HCLS} Community Profile: Describing Datasets, Versions, and Distributions},
  optcrossref = {},
  optkey = {},
  booktitle = {Smart Descriptions \& Smarter Vocabularies (SDSVoc)},
  year = {2016},
  opteditor = {},
  optvolume = {},
  optnumber = {},
  optseries = {},
  optpages = {},
  month = nov,
  address = {Amsterdam, The Netherlands},
  optorganization = {},
  optpublisher = {},
  optnote = {},
  url = {https://www.w3.org/2016/11/sdsvoc/SDSVoc16_paper_3},
  optannote = {}
}
```
The Semantic Web - ISWC 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17-21, 2016, Proceedings, Part II
Groth, Paul T. and Simperl, Elena and Gray, Alasdair J. G. and Sabou, Marta and Krötzsch, Markus and Lécué, Freddy and Flöck, Fabian and Gil, Yolanda
Lecture Notes in Computer Science, 9982, 2016
ISBN: 978-3-319-46546-3
```
@proceedings{iswc2016-2,
  editor = {Groth, Paul T. and Simperl, Elena and Gray, Alasdair J. G. and Sabou, Marta and Kr{\"{o}}tzsch, Markus and L{\'{e}}cu{\'{e}}, Freddy and Fl{\"{o}}ck, Fabian and Gil, Yolanda},
  title = {The Semantic Web - {ISWC} 2016 - 15th International Semantic Web Conference,
                 Kobe, Japan, October 17-21, 2016, Proceedings, Part {II}},
  series = {Lecture Notes in Computer Science},
  volume = {9982},
  month = oct,
  year = {2016},
  url = {http://dx.doi.org/10.1007/978-3-319-46547-0},
  doi = {10.1007/978-3-319-46547-0},
  isbn = {978-3-319-46546-3}
}
```
The Semantic Web - ISWC 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17-21, 2016, Proceedings, Part I
Groth, Paul T. and Simperl, Elena and Gray, Alasdair J. G. and Sabou, Marta and Krötzsch, Markus and Lécué, Freddy and Flöck, Fabian and Gil, Yolanda
Lecture Notes in Computer Science, 9981, 2016
ISBN: 978-3-319-46522-7
```
@proceedings{iswc2016-1,
  editor = {Groth, Paul T. and Simperl, Elena and Gray, Alasdair J. G. and Sabou, Marta and Kr{\"{o}}tzsch, Markus and L{\'{e}}cu{\'{e}}, Freddy and Fl{\"{o}}ck, Fabian and Gil, Yolanda},
  title = {The Semantic Web - {ISWC} 2016 - 15th International Semantic Web Conference,
                 Kobe, Japan, October 17-21, 2016, Proceedings, Part {I}},
  series = {Lecture Notes in Computer Science},
  volume = {9981},
  month = oct,
  year = {2016},
  url = {http://dx.doi.org/10.1007/978-3-319-46523-4},
  doi = {10.1007/978-3-319-46523-4},
  isbn = {978-3-319-46522-7}
}
```
The health care and life sciences community profile for dataset descriptions
Dumontier, Michel and Gray, Alasdair JG and Marshall, M Scott and Alexiev, Vladimir and Ansell, Peter and Bader, Gary and Baran, Joachim and Bolleman, Jerven T and Callahan, Alison and Cruz-Toledo, José and others
PeerJ, 4:e2331, PeerJ Inc., 2016

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.
```
@article{Dumontier:HCLS-datadesc:PeerJ2016,
  title = {The health care and life sciences community profile for dataset descriptions},
  author = {Dumontier, Michel and Gray, Alasdair JG and Marshall, M Scott and Alexiev, Vladimir and Ansell, Peter and Bader, Gary and Baran, Joachim and Bolleman, Jerven T and Callahan, Alison and Cruz-Toledo, Jos{\'e} and others},
  journal = {PeerJ},
  volume = {4},
  pages = {e2331},
  year = {2016},
  month = aug,
  url = {https://doi.org/10.7717/peerj.2331},
  doi = {10.7717/peerj.2331},
  publisher = {PeerJ Inc.}
}
```
Administrative social science data: The challenge of reproducible research
Playford, Christopher J and Gayle, Vernon and Connelly, Roxanne and Gray, Alasdair JG
Big Data and Society, 3(2):2053951716684143, 2016

Powerful new social science data resources are emerging. One particularly important source is administrative data, which were originally collected for organisational purposes but often contain information that is suitable for social science research. In this paper we outline the concept of reproducible research in relation to micro-level administrative social science data. Our central claim is that a planned and organised workflow is essential for high quality research using micro-level administrative social science data. We argue that it is essential for researchers to share research code, because code sharing enables the elements of reproducible research. First, it enables results to be duplicated and therefore allows the accuracy and validity of analyses to be evaluated. Second, it facilitates further tests of the robustness of the original piece of research. Drawing on insights from computer science and other disciplines that have been engaged in e-Research we discuss and advocate the use of Git repositories to provide a useable and effective solution to research code sharing and rendering social science research using micro-level administrative data reproducible.
```
@article{Playford:AdminSocSciRep:BDS2016,
  author = {Playford, Christopher J and Gayle, Vernon and Connelly, Roxanne and Gray, Alasdair JG},
  title = {Administrative social science data: The challenge of reproducible research},
  journal = {Big Data and Society},
  volume = {3},
  number = {2},
  pages = {2053951716684143},
  year = {2016},
  doi = {10.1177/2053951716684143},
  url = {https://doi.org/10.1177/2053951716684143},
  eprint = {https://doi.org/10.1177/2053951716684143}
}
```
The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, Mark D and Dumontier, Michel and Aalbersberg, IJsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and da Silva Santos, Luiz Bonino and Bourne, Philip E and others
Scientific data, 3(1):1–9, Nature Publishing Group, 2016

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
```
@article{Wilkinson:FAIRPrinciples:SciData2016,
  title = {The FAIR Guiding Principles for scientific data management and stewardship},
  author = {Wilkinson, Mark D and Dumontier, Michel and Aalbersberg, IJsbrand Jan and Appleton, Gabrielle and Axton, Myles and Baak, Arie and Blomberg, Niklas and Boiten, Jan-Willem and da Silva Santos, Luiz Bonino and Bourne, Philip E and others},
  journal = {Scientific data},
  volume = {3},
  number = {1},
  pages = {1--9},
  year = {2016},
  publisher = {Nature Publishing Group},
  doi = {10.1038/sdata.2016.18}
}
```

2015

Dataset Descriptions: HCLS Community Profile
Gray, A. J. G. and Baran, Joachim and Marshall, M Scott and Dumontier (Eds), Michel
W3C Interest Group Note. World Wide Web Consortium. may, 2015
```
@techreport{Gray2015HCLS,
  author = {Gray, A. J. G. and Baran, Joachim and Marshall, M Scott and {Dumontier (Eds)}, Michel},
  month = may,
  publisher = {World Wide Web Consortium},
  type = {{W3C Interest Group Note}},
  title = {{Dataset Descriptions: {HCLS} Community Profile}},
  year = {2015},
  url = {https://www.w3.org/TR/hcls-dataset/}
}
```

2014

Bring Your Own Data Workshops: A Mechanism to Aid Data Owners to Comply with Linked Data Best Practices
Roos, Marco and Gray, Alasdair J. G. and Waagmeester, Andra and Thompson, Mark and Kaliyaperumal, Rajaram and van der Horst, Eelke and Mons, Barend and Wilkinson, Mark
In Proceedings of the 7th International Workshop on Semantic Web Applications and Tools for Life Sciences, Berlin, Germany, December 9-11, 2014., CEUR Workshop Proceedings, 1320, CEUR-WS.org, 2014
```
@inproceedings{DBLP:conf/swat4ls/RoosGWTKHMW14,
  author = {Roos, Marco and Gray, Alasdair J. G. and Waagmeester, Andra and Thompson, Mark and Kaliyaperumal, Rajaram and van der Horst, Eelke and Mons, Barend and Wilkinson, Mark},
  title = {Bring Your Own Data Workshops: {A} Mechanism to Aid Data Owners to
                 Comply with Linked Data Best Practices},
  booktitle = {Proceedings of the 7th International Workshop on Semantic Web Applications
                 and Tools for Life Sciences, Berlin, Germany, December 9-11, 2014.},
  series = {{CEUR} Workshop Proceedings},
  volume = {1320},
  publisher = {CEUR-WS.org},
  month = dec,
  year = {2014},
  url = {http://ceur-ws.org/Vol-1320/paper\_36.pdf}
}
```
A Justification-based Semantic Framework for Representing , Evaluating and Utilizing Terminology Mappings
Hussain, Sajjad and Sun, Hong and Erturkmen, Gokce Banu Laleci and Yuksel, Mustafa and Mead, Charles and Gray, Alasdair J G and Forsberg, Kerstin
In Context Interpretation and Meaning, Riva del Garda, Italy, 2014

Use of medical terminologies and mappings across them are consid- ered to be crucial pre-requisites for achieving interoperable eHealth applica- tions. However, experiences from several research projects have demonstrated that the mappings are not enough. Also the context of the mappings is needed to enable interpretation of the meaning of the mappings. Built upon these experi- ences, we introduce a semantic framework for representing, evaluating and uti- lizing terminology mappings together with the context in terms of the justifica- tions for, and the provenance of, the mappings. The framework offers a plat- form for i) performing various mappings strategies, ii) representing terminology mappings together with their provenance information, and iii) enabling termi- nology reasoning for inferring both new and erroneous mappings. We present the results of the introduced framework using the SALUS project where we evaluated the quality of both existing and inferred terminology mappings among standard terminologies.
```
@inproceedings{Hussain2014CIM,
  address = {Riva del Garda, Italy},
  author = {Hussain, Sajjad and Sun, Hong and Erturkmen, Gokce Banu Laleci and Yuksel, Mustafa and Mead, Charles and Gray, Alasdair J G and Forsberg, Kerstin},
  booktitle = {Context Interpretation and Meaning},
  title = {{A Justification-based Semantic Framework for Representing , Evaluating and Utilizing Terminology Mappings}},
  url = {http://www.macs.hw.ac.uk/~fm206/cim14/cim20140_submission_2.pdf},
  month = oct,
  year = {2014}
}
```
Capturing Provenance for a Linkset of Convenience
Jupp, Simon and Malone, James and Gray, Alasdair J. G.
In Proceedings of the 4th Workshop on Linked Science 2014 - Making Sense Out of Data (LISC2014) co-located with the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, October 19, 2014., pages 71–75, 2014

Biological interactions such as those between genes and proteins are complex and require intricate OWL models. However, direct links between biological entities can support search and data integration. In this paper we introduce linksets of convenience that capture these direct links. We show the provenance statements required to track the derivation of such linksets; linking them back to the full biological justification.
```
@inproceedings{JuppMG14,
  author = {Jupp, Simon and Malone, James and Gray, Alasdair J. G.},
  title = {Capturing Provenance for a Linkset of Convenience},
  booktitle = {Proceedings of the 4th Workshop on Linked Science 2014 - Making Sense
                 Out of Data {(LISC2014)} co-located with the 13th International Semantic
                 Web Conference {(ISWC} 2014), Riva del Garda, Italy, October 19, 2014.},
  pages = {71--75},
  month = oct,
  year = {2014},
  url = {http://ceur-ws.org/Vol-1282/lisc2014_submission_7.pdf}
}
```
Scientific Lenses to Support Multiple Views over Linked Chemistry Data
Batchelor, Colin R. and Brenninkmeijer, Christian Y. A. and Chichester, Christine and Davies, Mark and Digles, Daniela and Dunlop, Ian and Evelo, Chris T. A. and Gaulton, Anna and Goble, Carole A. and Gray, Alasdair J. G. and Groth, Paul T. and Harland, Lee and Karapetyan, Karen and Loizou, Antonis and Overington, John P. and Pettifer, Steve and Steele, Jon and Stevens, Robert and Tkachenko, Valery and Waagmeester, Andra and Williams, Antony J. and Willighagen, Egon L.
In The Semantic Web - ISWC 2014 - 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part I, Lecture Notes in Computer Science, 8796, pages 98–113, Springer, 2014
(Alphabetical authorship)
```
@inproceedings{Batchelor:SciLenses:ISWC2014,
  author = {Batchelor, Colin R. and Brenninkmeijer, Christian Y. A. and Chichester, Christine and Davies, Mark and Digles, Daniela and Dunlop, Ian and Evelo, Chris T. A. and Gaulton, Anna and Goble, Carole A. and Gray, Alasdair J. G. and Groth, Paul T. and Harland, Lee and Karapetyan, Karen and Loizou, Antonis and Overington, John P. and Pettifer, Steve and Steele, Jon and Stevens, Robert and Tkachenko, Valery and Waagmeester, Andra and Williams, Antony J. and Willighagen, Egon L.},
  title = {Scientific Lenses to Support Multiple Views over Linked Chemistry
                 Data},
  booktitle = {The Semantic Web - {ISWC} 2014 - 13th International Semantic Web Conference,
                 Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part {I}},
  series = {Lecture Notes in Computer Science},
  volume = {8796},
  pages = {98--113},
  publisher = {Springer},
  month = oct,
  year = {2014},
  note = {(Alphabetical authorship)},
  url = {https://doi.org/10.1007/978-3-319-11964-9\_7},
  doi = {10.1007/978-3-319-11964-9\_7}
}
```
Help me describe my data: A demonstration of the Open PHACTS VoID Editor
Goble, Carole A. and Gray, Alasdair J. G. and Tatakis, Eleftherios
In Proceedings of the ISWC 2014 Posters & Demonstrations Track a track within the 13th International Semantic Web Conference, ISWC 2014, Riva del Garda, Italy, October 21, 2014., CEUR Workshop Proceedings, 1272, pages 29–32, CEUR-WS.org, 2014
(Demo paper)
```
@inproceedings{Goble:VoIDEditor:ISWC2014,
  author = {Goble, Carole A. and Gray, Alasdair J. G. and Tatakis, Eleftherios},
  booktitle = {Proceedings of the {ISWC} 2014 Posters {\&} Demonstrations Track a track within the 13th International Semantic Web Conference, {ISWC} 2014, Riva del Garda, Italy, October 21, 2014.},
  editor = {Horridge, Matthew and Rospocher, Marco and van Ossenbruggen, Jacco},
  month = oct,
  note = {(Demo paper)},
  pages = {29--32},
  publisher = {CEUR-WS.org},
  series = {{CEUR} Workshop Proceedings},
  title = {Help me describe my data: {A} demonstration of the Open {PHACTS} VoID Editor},
  url = {http://ceur-ws.org/Vol-1272/paper\_33.pdf},
  volume = {1272},
  year = {2014}
}
```
A Framework for Evaluating and Utilizing Medical Terminology Mappings
Hussain, Sajjad and Sun, Hong and Sinaci, Ali Anil and Erturkmen, Gokce Banu Laleci and Mead, Charles N. and Gray, Alasdair J. G. and McGuinness, Deborah L. and Prud’hommeaux, Eric and Daniel, Christel and Forsberg, Kerstin
In e-Health - For Continuity of Care - Proceedings of MIE2014, the 25th European Medical Informatics Conference, Istanbul, Turkey, August 31 - September 3, 2014, Studies in Health Technology and Informatics, 205, pages 594–598, IOS Press, 2014
```
@inproceedings{Hussain:MedicalMappings:MIE2014,
  author = {Hussain, Sajjad and Sun, Hong and Sinaci, Ali Anil and Erturkmen, Gokce Banu Laleci and Mead, Charles N. and Gray, Alasdair J. G. and McGuinness, Deborah L. and Prud'hommeaux, Eric and Daniel, Christel and Forsberg, Kerstin},
  title = {A Framework for Evaluating and Utilizing Medical Terminology Mappings},
  booktitle = {e-Health - For Continuity of Care - Proceedings of MIE2014, the 25th
                 European Medical Informatics Conference, Istanbul, Turkey, August
                 31 - September 3, 2014},
  series = {Studies in Health Technology and Informatics},
  volume = {205},
  pages = {594--598},
  publisher = {{IOS} Press},
  month = sep,
  year = {2014},
  url = {https://doi.org/10.3233/978-1-61499-432-9-594},
  doi = {10.3233/978-1-61499-432-9-594}
}
```
SensorBench: benchmarking approaches to processing wireless sensor network data
Galpin, Ixent and Stokes, Alan B. and Valkanas, George and Gray, Alasdair J. G. and Paton, Norman W. and Fernandes, Alvaro A. A. and Sattler, Kai-Uwe and Gunopulos, Dimitrios
In Conference on Scientific and Statistical Database Management, SSDBM ’14, Aalborg, Denmark, June 30 - July 02, 2014, pages 21:1–21:12, ACM, 2014
```
@inproceedings{Galpin:SensorBench:SSDBM2014,
  author = {Galpin, Ixent and Stokes, Alan B. and Valkanas, George and Gray, Alasdair J. G. and Paton, Norman W. and Fernandes, Alvaro A. A. and Sattler, Kai{-}Uwe and Gunopulos, Dimitrios},
  title = {SensorBench: benchmarking approaches to processing wireless sensor
                 network data},
  booktitle = {Conference on Scientific and Statistical Database Management, {SSDBM}
                 '14, Aalborg, Denmark, June 30 - July 02, 2014},
  pages = {21:1--21:12},
  publisher = {{ACM}},
  month = jun,
  year = {2014},
  url = {https://doi.org/10.1145/2618243.2618252},
  doi = {10.1145/2618243.2618252}
}
```
Scientific Lenses over Linked Chemistry Data using BridgeDb and the Open PHACTS Chemistry Registration System
Batchelor, Colin and Brenninkmeijer, Christian and Evelo, Chris and Goble, Carole and Gray, Alasdair and Karapetyan, Ken and Tkachenko, Valery and Willighagen, Egon
In 10th ICCS, International Conference on Chemical Structures, Noordwijkerhout, the Netherlands, 2014
(Extended abstract)
```
@inproceedings{Batchelor:chem-lenses:ChemStruct2014,
  address = {Noordwijkerhout, the Netherlands},
  author = {Batchelor, Colin and Brenninkmeijer, Christian and Evelo, Chris and Goble, Carole and Gray, Alasdair and Karapetyan, Ken and Tkachenko, Valery and Willighagen, Egon},
  booktitle = {10th ICCS, International Conference on Chemical Structures},
  month = jun,
  note = {(Extended abstract)},
  title = {Scientific Lenses over Linked Chemistry Data using BridgeDb and the Open PHACTS Chemistry Registration System},
  year = {2014}
}
```
Dataset Descriptions for Linked Data Systems
Gray, Alasdair J. G.
IEEE Internet Computing, 18(4):66–69, 2014
```
@article{DBLP:journals/internet/Gray14,
  author = {Gray, Alasdair J. G.},
  title = {Dataset Descriptions for Linked Data Systems},
  journal = {{IEEE} Internet Computing},
  volume = {18},
  number = {4},
  pages = {66--69},
  year = {2014},
  url = {https://doi.org/10.1109/MIC.2014.66},
  doi = {10.1109/MIC.2014.66}
}
```
Applying linked data approaches to pharmacology: Architectural decisions and implementation
Gray, Alasdair J. G. and Groth, Paul T. and Loizou, Antonis and Askjaer, Sune and Brenninkmeijer, Christian Y. A. and Burger, Kees and Chichester, Christine and Evelo, Chris T. A. and Goble, Carole A. and Harland, Lee and Pettifer, Steve and Thompson, Mark and Waagmeester, Andra and Williams, Antony J.
Semantic Web Journal, 5(2):101–113, 2014

The discovery of new medicines requires pharmacologists to interact with a number of information sources ranging from tabular data to scientific papers, and other specialized formats. In this application report, we describe a linked data platform for integrating multiple pharmacology datasets that form the basis for several drug discovery applications. The functionality offered by the platform has been drawn from a collection of prioritised drug discovery business questions created as part of the Open PHACTS project, a collaboration of research institutions and major pharmaceutical companies. We describe the architecture of the platform focusing on seven design decisions that drove its development with the aim of informing others developing similar software in this or other domains. The utility of the platform is demonstrated by the variety of drug discovery applications being built to access the integrated data.
```
@article{Gray:OPS:SWJ,
  author = {Gray, Alasdair J. G. and Groth, Paul T. and Loizou, Antonis and Askjaer, Sune and Brenninkmeijer, Christian Y. A. and Burger, Kees and Chichester, Christine and Evelo, Chris T. A. and Goble, Carole A. and Harland, Lee and Pettifer, Steve and Thompson, Mark and Waagmeester, Andra and Williams, Antony J.},
  title = {Applying linked data approaches to pharmacology: Architectural decisions
                 and implementation},
  journal = {Semantic Web Journal},
  volume = {5},
  number = {2},
  pages = {101--113},
  year = {2014},
  url = {https://doi.org/10.3233/SW-2012-0088},
  doi = {10.3233/SW-2012-0088}
}
```
API-centric Linked Data integration: The Open PHACTS Discovery Platform case study
Groth, Paul T. and Loizou, Antonis and Gray, Alasdair J. G. and Goble, Carole A. and Harland, Lee and Pettifer, Steve
Journal of Web Semantics, 29:12–18, 2014
```
@article{DBLP:journals/ws/GrothLGGHP14,
  author = {Groth, Paul T. and Loizou, Antonis and Gray, Alasdair J. G. and Goble, Carole A. and Harland, Lee and Pettifer, Steve},
  title = {API-centric Linked Data integration: The Open {PHACTS} Discovery Platform
                 case study},
  journal = {Journal of Web Semantics},
  volume = {29},
  pages = {12--18},
  year = {2014},
  url = {https://doi.org/10.1016/j.websem.2014.03.003},
  doi = {10.1016/j.websem.2014.03.003}
}
```