metaphactory: A Platform for Knowledge Graph Management

Tracking #: 1950-3163

Peter Haase
Daniel Herzig
Artem Kozlov
Andriy Nikolov
Johannes Trame

Responsible editor: 
Guest Editors Knowledge Graphs 2018

Submission type: 
Tool/System Report
In this system paper we describe metaphactory, a platform for building knowledge graph management applications. The metaphactory platform aims at supporting different categories of knowledge graph users within the organization by realizing relevant services for knowledge graph data management tasks, providing a rich and customizable user interface, and enabling rapid building of use case-specific applications. The paper discusses how the platform architecture design built on open standards enables its reusability in various application domains and use cases as well as facilitates integration of the knowledge graph with other parts of the organizational data and software infrastructure. We highlight the capabilities of the platform by describing its usage in four different knowledge graph application domains and share the lessons learnt from the practical experience of building knowledge graph applications in the enterprise context.
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Solicited Reviews:
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Review #1
By Shimaa Ouf submitted on 10/Oct/2018
Minor Revision
Review Comment:

- It was a great pleasure that I invited to review the manuscript entitled " metaphactory: A Platform for Knowledge Graph Management "

- Quality: the quality is very good. The authors' approach to describe metaphactory platform for building knowledge graph management applications is clear and not novel. I suggests them to insert a matrix table, which includes criterias for successful Knowledge Management platform. This matrix will show the shortages and limitation on these platforms and show the difference and what gaps to fill in this suggested tool. This will confirm the power of their suggested metaphactory platform.

- The suggested tool is important and covers the limitations of most others knowledge management platforms. Metaphactory integrating different open standards like ontodia, which offer great flexibility in different usage scenarios and across various industries and application areas such as (culture heritage, life science, engineering, IoT infrastructure, and pharmaceutics).

- The suggested tool has a great impact on organizations due to offer capabilities and features to support the entire lifecycle of dealing with knowledge graphs and is used in production in a variety of use cases involving knowledge graph management in different application domains.

- The metaphactory platform is a powerful and successful knowledge management platform but authors should list the limitations of the suggested tool in their paper. Besides The results of this tool should be well discussed with the results of prior tools in order to manifest the contribution and value of this study.

Review #2
Anonymous submitted on 22/Oct/2018
Minor Revision
Review Comment:

In the submitted manuscript, the authors described the metaphactory system for managing knowledge graphs (KGs). The system provides covers a full life-cycle of KG creation, management, and provides high level interface for the end users. The paper describes the metaphactory in detail, and also provides a list of lessons learnt in the practical use cases. The paper is in general well-written. Below, I have a few minor suggestions to improve the paper:

1. In 'Reusability', the authors mentioned a few standards, such as RDF, SPARQL, and SHACL. It would be better to provide a complete list here. I believe for instance OWL, R2RML, GeoSPARQL are also relevant here.

2. The mataphactory systems rely heavily on opensource components developed in the Semantic Web community. Please explicitly enumerate them.

3. How about the performance? Is there any performance evaluation can be discussed?

4. The word 'data' is used as both singular and plural. Please stick to one.

Review #3
By Emmanuel Pietriga submitted on 23/Oct/2018
Major Revision
Review Comment:

This paper describes a platform called metaphactory that enables creating and managing knowledge graphs connected to heterogeneous data sources, and building application UIs to interact with these knowledge graphs and associated data sources.

The paper addresses an important problem and fits the scope of this special issue pretty well. I have little doubt that the described platform is useful to the type of organization targeted. However, I am having a very hard time seeing a research contribution in the paper as it is written, that would be of clear interest to the academic community. The lack of positioning with respect to related work is symptomatic of this problem, but had this been the only issue, I would have recommended a minor revision. The problem with the paper in its current form, however, is much deeper, as detailed below. Writing systems papers for academic venues is particularly challenging. There are many pitfalls, which the paper fails to completely avoid.

After reading the introduction, I was still not sure what is the contribution w.r.t the state of the art. What specific challenges have been addressed? How? This remains unclear as the introduction consists mostly of a wishlist at a very high level of abstraction. A clear contribution statement would be the minimum, but I believe the paper would benefit significantly from a complete rewrite of the introduction to make these things crystal clear.

It isn't clear where the Architecture section is going. What is novel here? This is a very flat, somewhat lengthy description, without any clear rationale for the choices made and what particular challenges have been tackled.

Section hints at where the research effort had focused (page 4), but this never developed, at least not to a significant extent. Not to mention that part of what seems to be novel in this research has already been the subject of publications at ISWC (albeit as posters or demos, as far as I understand). Related to the lack of positioning w.r.t related work, Section 3 fails to pinpoint specific limitations of existing solutions and to explain Ephedra addresses those limitations. The description remains too abstract. For instance, the last paragraph of Section 3 (page 5) hints at some interesting aspects of hybrid query processing, but remains far too vague for this to be informative to the interested readers.

Section 5, which deals with the user interface aspects of the platform, is maybe the weakest. Everything that is stated in this section is already known. The paper completely ignores (except for two anecdotal references) the very large body of work on visualization and user interfaces for semantic web/linked data, even failing to acknowledge the challenges related to generating meaningful representations of semantic data. While the issue of UI design and development in the context of such a platform is indeed key, the paper fails to provide any convincing solution, evidence, or even insightful discussion beyond what has already been said many times in the literature. One exception to this could be Section 5.2 about GraphScope, but again, this section give far too little information about it. It isn't clear how it works, and how users interact with it.

Finally, the use cases bear relatively little value. While it is certainly a good thing that the platform is used in various projects, it is unclear how the descriptions provided in Section 6 provide actual validation (from an academic/research perspective) of the approach investigated in this platform.

All of that said, my review is more about the paper's contents (how it is framed) rather than the platform itself, which might very well be worthy of publication in a scientific journal. The presentation of the work, however, needs significant revision.