7 Arian Rajh1 CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES Abstract Purpose: This paper explores the use of Description Logic (DL) in analysing and updating ontologies and examines the benefits of its applicability. Methodology: The section on DL and ontologies explains those terms and demonstrates DL’s syntaxes. Then, the author “manually” uses DL to analyse the construction of classes and properties of the Records in Contexts ontology as concepts and roles in the T-box. An A-box is constructed from an example pub- lished on the EGAD GitHub page. The author also demonstrates how DL is used to construct the main entities of an exemplar ontology, Daetika. Results: The results comprise modelling DL concepts according to ontology de- scriptions (rdfs:comment element in RDF/XML ontology file). When descriptions were insufficient to model DL concepts, scope notes or external elements were used. After presenting the results of harmonizing ontology entities with the DL structures, the author discusses the importance of such efforts. Conclusions: The author concludes with establishing a connection between DL used for analysis or construction purposes and the clarity and cohesion of on- tologies. He also provides recommendations for future work on ontologies and outlines general possibilities with RIC-O. Keywords: Daetika, description logic, knowledge, ontologies, OWL, Records in Contexts 1 Arian Rajh, PhD, Assoc. Prof., University of Zagreb, Faculty of Humanities and Social Sciences, Ivana Lučića 3, Zagreb, Croatia, arajh@m.ffzg.hr. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 8 1. INTRODUCTION The paper unveils the potential of Description Logic (DL) as a tool for analysing RIC ontology (RIC-O) and constructing ontologies of selected domains. Oth- er works have considered this potential more generally by tracing relationships between ontologies and DL knowledge bases (Horrocks et al., 2003, 10; Baader et al., 2017, 5). This article analyses the formal concepts and properties of the RIC-O, which is an already-developed ontology. This analysis is enhanced by manual mapping parts of definitions and scope notes of the concepts from that ontology to DL. In some cases, we felt it was necessary to add external concepts. The second ontology is being constructed according to the DL apparatus. This approach aims to analyze ontologies and alert if their concepts lack some clarity. Mapping of DL and ontology concepts could also serve as a foundation of reason- ing, not only for (re)formulating an ontology. 2. DL AND RIC-O DL is a set of formalisms that represent domain-related knowledge by defining its concepts (i.e., the world of a domain expressed by carefully designed vocabulary) and descriptions of individuals or their properties (Baader et al., 2003, 43). DL is also a cluster of languages (AL, SHIQ, SROIQ)2 that vary in expressivity and reasoning potential. It could be explained as an arena of scientific and practical activities that use constructors to describe concepts and roles and the logic to solve their complex semantics (Baader et al., 2017, 1; Baader et al., 2003, 43). DL, thus, works with concepts, roles, and constructors.3 Concepts and roles are intercon- nected in a T-box’s terminological axioms (equalities or subsumptions of concepts or roles). After defining concepts, the interrelations of terminological axioms pro- vide background knowledge of a domain (Baader et al., 2017, 17). We could, for example, define concepts of Person and Place and the role of hasBirthPlace in a 2 The broad family of AL (attributive) languages expresses concepts and primary constructors. SHIQ languages expand AL languages, as stated by Szeredy et al. (2014). The Semantic Web explained. Cambridge: CUP, pp. 188- 199, and Baader et al. (2017). An introduction to Description Logic. Cambridge: CUP, pp.11-12. SROIQ language works with the most complex constructors; see Szeredy et al., ibid., pp. 233, 243-5, and Horrocks et al. (2006). The even more irresistible SROIQ. 10th Int. Conference on Principles of Knowledge Representation and Reasoning, United Kingdom, June 2-5, 2006. 3 A concept is a set of individuals, and roles reflect concept relationships. Constructors assemble more compound concepts/roles in a T-box. For further explanation, see Baader et al. (2017). An introduction to Description Logic, Cambridge: CUP, p. 23. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 9 T-box. The A-box or assertion box is the other essential part of the DL knowledge base. An A-box includes individual names (i.e., Cook : Person, Vancouver : Place) and their relationships (i.e., individual name – role – individual name as role-filler: Cook hasBirthPlace Vancouver or (Cook, Vancouver) : hasBirthPlace). We could add some background knowledge about Vancouver. DL enables software agents to use reasoning on background knowledge. For example, if an information system has information about Terry Cook and Vancouver, we could ask in which country Terry Cook was born, and this information could be acquired without being explic- itly stated anywhere in the system and without human help. This way, DL assists software agents in reasoning and creating new knowledge. DL languages form the foundation of the Web Ontology Language (OWL) used for building ontologies (W3C, 2012a). DL concepts correspond to ontologies’ classes, and roles correspond to object properties. Ontologies are computer-readable spec- ifications of shared conceptualizations (Studer et al., 1998, 25). This paper will predominantly focus on DL as a tool to syntactically express and clarify elements of an archival ontology, RIC-O. Records in Contexts (RIC) is an advanced profes- sional descriptive standard that enables archivists to describe record resources and other essential entities and their attributes and relations. It consists of three parts at present: an introduction, a conceptual model (ICA EGAD, 2023), and an ontology (RIC-O) (ICA EGAD, 2024). The ontology represents a further development phase of the conceptual model or a more systematic application of syntactic and semantic formalisms to concepts. As demonstrated in this paper, conceptual models could also be created using DL, which can bring certain advantages. DL is an appropriate tool for conceptualization in the “conceptual model phase” of ontologies. RIC-O encompasses classes and individuals, as well as data and object properties related to archival entities – record resources, their instances, agents involved with creating records or thematized in records, dates, places, events, and other entities. RIC-O data properties describe those entities, and object properties connect them accord- ing to linked data (LD) principles, implementing the Semantic Web’s dispersed and decentralized but feasibly cooperative practices. RIC-O-based descriptions of archival entities lean on LD technologies like the Resource Description Framework (RDF) data model (W3C, 2024a) and its serializations (W3C, 2024b; W3C, 2024c) and query languages (W3C, 2024d). CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 10 3. APPROACH We want to consider the role of DL for an ontology such as RIC-O or any other ontol- ogy. Observing and handling RIC-O “through the DL prism” makes sense because RIC-O is based on the OWL 2 language (https://github.com/ICA-EGAD/RiC-O), mainly constructed according to the OWL RL profile4 (W3C, 2012b), and OWL 25 was derived from the SROIQ DL language (W3C, 2012a; Horrocks et al., 2006). The approach of this paper focuses on the manual mapping of DL concepts, roles, and assertions with entities of an archival ontology, and we aim to analyse and reformat the archival world by constructing its knowledge base and axiomatization. In other words, by building descriptions and hierarchies of concepts and roles from an ontology and individuals from examples of its implementation. Two archival ontologies are examined – RIC-O and another smaller and simpler one, Daetika. For RIC-O, whenever possible, descriptions of concepts will be based on RIC-O class-IRIs’ definitions (https://www.ica.org/standards/RiC/RiC-O_1-0-1.html), also expressed by rdfs:comment element in ontology’s RDF/XML file, and RIC-O property-IRIs’ definitions and domains and ranges related restrictions. This means building RIC-O’s T-box and exemplar A-box. An RIC-O-compatible A-box is provided by a description, i.e., one of the descriptions on the EGAD RIC-O GitHub page: https://github.com/ICA-EGAD/RiC-O/blob/master/exam- ples/examples_v1-0/Matterhorn-Switzerland/IP-RiC-O/metadata.ttl description serialized in RDF Turtle file. The same thing is achievable by using any other RIC-O harmonized description. This example file contains descriptions in the 4 As stated in a discussion of the RIC-O Google group, the post from July 12, 2024, https://groups.google.com/g/ Records_in_Contexts_users/c/mhAkB6k-E9c. The W3C 212b document states, “[t]he RL acronym reflects the fact that reasoning in this profile can be implemented using a standard Rule Language.” In addition, “OWL 1 DL can also be viewed as a profile of OWL 2.”, W3C. (2012b). OWL 2 Web Ontology Language (2nd ed.), Introduction. 5 The first W3C OWL recommendation dates to 2004 when the OWL DL sublanguage and OWL Lite were spec- ified. OWL DL has several constraints on concept usage and is focused on reasoning and specific domains, as DuCharme noticed in his book from 2013 (page 424). OWL Lite has additional restrictions and limits OWL expressivity for more manageable software implementations, as explained in section 8.3 of the 2004 OWL W3C recommendation. In OWL DL, a class is separated from an individual, and an object property is separated from a data property; plus, some constraints are related to types of properties and axioms, as stated in section 8.2 of the same W3C recommendation. The first version of OWL also includes OWL Full, the most expressive use of OWL. Besides OWL Full language and its OWL DL subset, the second version of the W3C OWL recommendation (OWL 2), dated from 2009 and updated in 2012, specifies OWL 2 RL, EL, and QL profiles. Each profile or sublanguage performs best in different use cases: RL (rules) facilitates rule-based scalable reasoning, EL (expressiveness) fa- cilitates reasoning with complex ontologies, and QL (queries) facilitates querying assertions recorded in relational databases, as stated in the 2012 W3C recommendation. OWL 2 EL and OWL 2 RL can be considered like DL in their approach, whereas OWL 2 QL follows OWL 1 Lite’s simplicity. Ultimately, there are multiple profiles and sublanguages within the OWL 2 framework to suit various needs. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 11 form of sentence-resembling triples of subjects, predicates, and objects. Subjects that appear before predicates “a” (e.g., rdf:type) in the RIC-O example Turtle file are instances that occupy A-boxes. Baader and his colleagues consider such RDF triples as DL concept assertations (subject-predicate-object = instance : Concept, if predicate = a or rdf:type) (Baader et al., 2017, 207). According to Baader and his co-authors, RDF triples can also be DL role assertions, DL T-box axioms, or non-DL statements (rdfs:comment) (Baader et al., 2017, 213). Another ontology, Daetika, created by the author of this paper, will also be ex- pressed in DL. Daetika is an archival ethical ontology that combines deontolo- gy, or ethics of behaviour and procedures, with aretaic ethics of characteristics.6 Here, we will explore the notion of archivists behaving justly: focused on the empathic understanding of others’ positions, inclusive acceptance of their values, and transparency to legitimize their duties. Daetika’s knowledge base consists of concepts, rules, and hypothetical examples of instances. The Daetika ontology will provide the T-box, and the A-box should be provided by making exemplary statements about individuals. 4. RESULTS Part 4.1 relates to the DL analysis of RIC-O, which provides an example of what can be achieved on already-built ontologies. Part 4.2 relates to the Daetika ontol- ogy, a new ontology designed from scratch. 4.1. AN EXCERPT OF THE RIC-O 1.0.1. KNOWLEDGE BASE Figure 1 and 2 below compare certain ontology classes and their definitions (or rd- fs:comment elements, W3C, 2024e, §3.7) with equations in DL. A part of RIC-O consisting of Agent subclasses was selected from the ontology. The strategy was to represent concepts using their ontology definition whenever feasible. For some classes, it was challenging to create concept axioms out of original RIC-O’s IRI descriptions published on the EGAD website or embedded in the rdfs:comment 6 The theoretical background of the Daetika ontology is described in detail in Rajh, A. (2024). Prilog arhivističkoj etici: osobine arhivista, perspektiva pravednosti i vrednovanje. Arhivski vjesnik 67 (Contribution to archival eth- ics: Characteristics of archivists, justice perspective, and appraisal). Daetika is based on Rawls’s theory of justice, with self-reflexivity as a starting point for just behavior instead of his primary position and the veil of ignorance. The final effect is similar to Rawls’s principles of justice, but in the “archival world,” and it is accomplished with selected characteristics and behavior of the archivists. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 12 nodes of the RDF/XML file. Hence, it was necessary to use broader, similar, or just meaningful other object properties or classes outside RIC-O rdfs:comment ele- ment or even RIC-O itself to supplement RIC-O concepts. For the Mechanism class concept, the first choice for linking a mechanism to a person or group who creates it was property “isRelatedTo,” because RIC-O’s property “hasCreator” refers to different domains. If the “hasCreator” property included the mechanism class in its domain, we would use it to model the concept. Still, the property “isRelatedTo” was too broad. A new object property, “createdBy,” non-existing in RIC-O, was used as suggested during the review of this work and paper. The Position class was challenging to model in DL using the definition (rdfs:comment from the ontology RDF/XML file). This class was more manageable to model from the skos:scope- Node7 information; adding its name and relations to the mandate and activity was possible. Reaching for the non-RIC-O class “Project” was necessary to state that it could relate to projects. The position class is an example where it was convenient to reach for information outside the class definition and RIC-O ontology. Figure 1: Figure 2: Classes in RIC-O 1.01 (Protégé) DL representation of RIC-O classes Additional classes of record set, record, record part, and documentary form type were modelled, too–all these classes are well-known among archivists. 7 Please see https://www.w3.org/2012/09/odrl/semantic/draft/doco/skos_scopeNote.html (accessed 6.10.2024 CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 13 RecordSet ⊑ ∃ isRecordResourceAssociatedWithRecordResource.Record The record set concept was defined above using RIC-O entities alone. Using in- ternal entities solely was not the best option for modelling the record and record part concepts below. Regarding the record class, RIC-O does not define the infor- mation content class, although the ontological definition of the record mentions it. The equation is modelled by combining rdfs:comment and supplementary skos:- scopeNote. However, the statement that records could be evidence of activity was avoided because RIC-O links evidence-related concepts with the top relation class (not to the activity class). Regarding the record part class, its DL equation contains the concept of the complete record from RIC-O’s ontological definition (“intellectual completeness”). Record≡InformationContent⊓(∃documents.Activity)⊓(∃hasCreator.Agent) ⊓(∃hasOrHadInstantiation.Instantiation) RecordPart≡RecordResource⊓¬CompleteRecord. Modelling RecordResource as a DL concept directly from the RIC-O class would be very demanding. This complex class uses a simple, constitutive class of In- formation and roles of “producing,” “acquiring,” and “retaining,” which were not modelled anywhere in the ontology. Also note that the RecordResource uses the “Information” concept, and the Record class, as shown, uses the “Information- Content” concept. These simple, constitutive concepts act as synonyms. DocumentaryFormType ≡(∃isOrWasCategoryOf.(Record⊔RecordPart) ⊓(ExtrinsicElement⊔IntrinsicElement)⊓∃communicates(Content) ⊔AdminstrativeContext⊔DocumentaryContext⊔Authority). The ontological definition of the “documentary form type” complex class has elements like ExtrinsicElement and IntrinsicElement, as well as the aspect of communication of the content, administrative and documentary context, and au- thority. Concepts of the extrinsic and intrinsic element, content, contexts, author- ity, and the object property “communicates” were derived from rdfs:comment of DocumentaryFormType class. They do not exist as RIC-O’s simple classes, although they constitute RIC-O’s complex class DocumentaryFormType. The equation may be partially redundant as the intrinsic element structured in the protocol already “contains administrative context of the action” and eschatocol CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 14 “contains the documentation context of the action” (Duranti, 1991:11). However, the main intention was to do the most literal “translation” of RIC-O’s definition to DL. Also, this equation covers all the aspects of the documentary form – not just those elements reflecting administrative and documentary context. An A-box that follows is selected from an EGAD example published on EGAD’s GitHub page: https://github.com/ICA-EGAD/RiC-O/blob/master/examples/ex- amples_v1-0/Matterhorn-Switzerland/IP-RiC-O/metadata.ttl. On the level of the record, A-box is constructed in the following standard manner: _20201118115821577∶ Record, (_20201118115821577,20030501)∶ isAssociatedWithDate, (_20201118115821577,20201231)∶ isAssociatedWithDate, (_20201118115821577,700)∶ isOrWasRegulatedBy, (_20201118115821577,701)∶ isOrWasRegulatedBy, (_20201118115821577,702)∶ isOrWasRegulatedBy, (_20201118115821577,Komplettübernahme)∶ isOrWasAffectedBy, (_20201118115821577,Direktübernahme)∶ isOrWasAffectedBy, (_20201118115821577,20201118115820159)∶ hasOrHadDigitalInstantiation. The triplet “<_20201118115821577> a rico:Record” from the metadata.ttl file was transformed to the concept assertion, following the rules Baader and his col- leagues stated. A similar principle was used for role assertions, with instances and DL roles: isAssociatedWithDate, isOrWasRegulatedBy, and isOrWasAffect- edBy. Constructing the T-box from the entire RIC-o in this paper was impossible because it is a relatively large ontology. This excerpt from T and A-boxes mod- eled according to RIC-O shows the relationships between RIC-O and DL. 4.2. DAETIKA’S KNOWLEDGE BASE It is possible to show the entire knowledge base of Daetika ontology due to its small size. The Daetika ontology consists of 12 classes besides Thing, and its purpose here is to show the first steps of constructing an ontology with the help of DL. The focus is on DL in the initial phase and modelling the main ontology classes and object properties. Firstly, the main concepts in the terminology can be defined as follows: CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 15 JustBehavior≡Behavior⊓Just. JustBehavior ⊑ ∀leadingTo^-.{Empathy}⊓ ∀leadingTo^-.{Inclusivity} ⊓ ∀leadingTo^-.{Self-reflexivity}⊓ ∀isLinkedTo.{Transparency}. TargetedCharacteristic ≡TargetedCharacteristicLeadingToJustBehavior ⊓TargetedCharacteristicLinkedToJustBehavior. TargetedCharacteristic⊑Characteristic. TargetedCharacteristicLeadingToJustBehavior ≡{Empathy}⊓{Inclusivity}⊓{Self-reflexivity}. TargetedCharacteristicLinkedToJustBehavior≡{Transparency}. ∃isLinkedTo.⊺⊑TargetedCharacteristicsLinkedToJustBehavior. Sym(isLinkedTo). ∃leadingTo.⊺⊑TargetedCharacteristicLeadingToJustBehavior. leadingTo≡comesFrom-. In the future, Daetika should be populated with definitions of the highest classes or merged with other ontologies that already have these classes defined, along with definitions of other entities that were not in the focus of this work. Figure 3 shows an as-is comprehensive view of Daetika’s ontology. The focus was on the classes of JustBehavior and TargetedCharacteristics with its subclasses. Behavior, Characteristics, and Process are classes taken from other domains. Empathy, in- clusivity, self-reflexivity, and transparency are characteristics (like Scott Cline’s archival virtues, Cline, 2021) modelled in the Daetika ontology as instances. A set of hypothetical personal characteristics is, of course, more extensive. Howev- er, these are the specific characteristics that lead to just behaviour or are associat- ed with just behaviour, as per the theoretical framework of the Daetika ontology (please see note 6). They are represented by DL as nominals so that they can be used in the T-box. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 16 Figure 3: The classes of Daetika ontology (Protégé) Furthermore, it is possible to model an A-box with individuals. Below is an ex- emplar A-box that describes an archivist who acts justly, using the instance of an Archivist and concepts defined in Daetika terminology. Before jumping to the A-box, the Archivist concept should be modelled and added to the T-box above. In one of the RIC-O Google group discussions, the Archivist entity was already considered in several ways.8 The concept of archivist could be defined throughout the concept of occupation type as its specialization. The archivist could be defined more strictly or loosely as a DL concept, matching a new subclass that can fit in the OccupationType class of RIC-O as the ontology with the same domain as Daetika. The Archivist could be defined as an accumu- lator of record resources and their manager because RIC-O has object properties isAccumulatorOf and isOrWasManagerOf, with agent class as the domain and record resources class in their range. However, an archivist’s job is not limited to the accumulation and management of records, so if the previous concept doesn’t suit us, for the time being, we could emphasize archivists’ distinctiveness among other occupation types.9 It is not a perfect solution, but more comprehensive. 8 Please see: https://groups.google.com/g/Records_in_Contexts_users/c/qc4PqaZVF24 (accessed 12.7.2024). 9 As mentioned in the previous paragraph and as documented in the literature on the level of more general principle, Baader et al. (2003). The Description Logic handbook. Cambridge: CUP, pp. 58-9. CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 17 Archivist≡OccupationType⊓∃isAccumulatorOf.RecordResource ⊓∃isOrWasManagerOf.RecordResource. Archivist⊑OccupationType. A-box with an instance of archivist could contain assertations like: terry∶Archivist⊓JustBehavior, (TargetedCharacteristicLeadingToJustBehavior,JustBehavior) ∶leadingTo, (JustBehavior,Process) ∶isLinkedTo, (JustBehavior,TargetedCharacteristicLinkedToJustBehavior) ∶isLinkedTo. A-box with an instance of archivist could contain assertations like: From all of this (the terminology combined with the A-box) it can be inferred by reasoning that archivist Terry is self-reflexive, empathic, inclusive, and transpar- ent while practicing archival processes. The given background knowledge sup- ports this. 5. CONCLUSIONS AND FUTURE WORK DL can analyse, construct, consolidate, update, and revise an ontology. This pa- per showcased the use of DL to analyse or construct RIC-O and Daetika ontolo- gies. Some conclusions from a limited set of analysed entities suggest that using simple interconnected concepts to explain complex ideas would be best. The defi- nitions of concepts should be clear and comprehensive rather than unnecessarily complex and overly elaborated using many undescribed concepts. Generally, the DL terminology and, thus, the ontology classes and properties should be careful- ly coordinated and logically organized. Concepts should be economically reused throughout the knowledge base. When constructing a new ontology, a good ap- proach is to define the concepts and roles using DL and then derive and publish the definitions. Ontology definitions should be interrelated and form a solid foun- dation of background knowledge. This interconnectedness ensures the ontology’s consistency and facilitates automated reasoning. RIC-O is based on OWL 2, which could be “roughly speaking…mapped…into SROIQ“ DL (Badder et al., 2017, 206). The length of this paper did not allow for an all-comprehensive RIC terminology analysis; however, this short DL analysis showed that establishing a clear T-box using just RIC-O ontology’s definitions was not always possible. RIC-O requires more use of primary, constitutive con- CONSIDERING DESCRIPTION LOGIC FOR ANALYZING AND CLARIFYING ARCHIVAL ONTOLOGIES ARIAN RAJH 18 cepts, and defining complex concepts in DL for some RIC-O classes was chal- lenging due to RIC-O’s disconnected definitions. A set of fundamental simple concepts is needed to model more complex archival entities or the building blocks of archival description. This doesn’t mean adding a multitude of banal concepts to the ontology. It is advisable to create simple, essential classes for use in defin- ing complex classes – systematically yet efficiently by managing synonymy and avoiding overabundance. Revising ontology definitions that are “DL-problemat- ic” in RIC-O can enhance the ontology’s cohesion and should be considered part of its normal life cycle. The same conclusions would apply if the characteristics of people behaving justly in Daetika had not been modelled as instances. For ontology instances, rdfs:comment elements are used less frequently than classes and properties (W3C, 2024e, §3.7). However, as a good practice, rdfs:comment elements should be added to the instances in Daetika in the future, and if this on- tology does not integrate with others, its higher-level classes – Behaviour, Char- acteristic, and Process – should also be unambiguously defined. 6. GENERAL POSSIBILITY IN THE FUTURE Matching DL structures with ontology entities could enhance ontology clarity and consistency and enable automatic reasoning and the generation of new infor- mation. Defining DL terminology before ontology construction may streamline this process, and for established ontologies like RIC-O, reverse engineering of concepts and roles using DL tools could improve expressiveness and decidabil- ity. The potential for creating new knowledge through the automatic processing of archival entities is promising. RIC-O facilitates far more advanced usage of archival information beyond the limits of the ISAD(G) family of standards. This represents more than evolution in the archival profession. Because of the integra- tion of semantic web concepts in RIC, its potential is very promising. Automatic reasoning and generating information not explicitly written by archivists can be a powerful tool for archive users. Finally, DL and ontologies like RIC can make archival terms and concepts in pro- fessional dictionaries more distinct and neater, thus making our discourse more explicit and precise. Archivists may consider all of this for future work. 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